Метаисследование как пишется

Metascience (also known as meta-research) is the use of scientific methodology to study science itself. Metascience seeks to increase the quality of scientific research while reducing inefficiency. It is also known as «research on research» and «the science of science«, as it uses research methods to study how research is done and find where improvements can be made. Metascience concerns itself with all fields of research and has been described as «a bird’s eye view of science».^[1] In the words of John Ioannidis, «Science is the best thing that has happened to human beings … but we can do it better.»^[2]

In 1966, an early meta-research paper examined the statistical methods of 295 papers published in ten high-profile medical journals. It found that «in almost 73% of the reports read … conclusions were drawn when the justification for these conclusions was invalid.» Meta-research in the following decades found many methodological flaws, inefficiencies, and poor practices in research across numerous scientific fields. Many scientific studies could not be reproduced, particularly in medicine and the soft sciences. The term «replication crisis» was coined in the early 2010s as part of a growing awareness of the problem.^[3]

Measures have been implemented to address the issues revealed by metascience. These measures include the pre-registration of scientific studies and clinical trials as well as the founding of organizations such as CONSORT and the EQUATOR Network that issue guidelines for methodology and reporting. There are continuing efforts to reduce the misuse of statistics, to eliminate perverse incentives from academia, to improve the peer review process, to systematically collect data about the scholarly publication system,^[4] to combat bias in scientific literature, and to increase the overall quality and efficiency of the scientific process.

History[edit]

In 1966, an early meta-research paper examined the statistical methods of 295 papers published in ten high-profile medical journals. It found that, «in almost 73% of the reports read … conclusions were drawn when the justification for these conclusions was invalid.»^[6] In 2005, John Ioannidis published a paper titled «Why Most Published Research Findings Are False», which argued that a majority of papers in the medical field produce conclusions that are wrong.^[5] The paper went on to become the most downloaded paper in the Public Library of Science^[7][8] and is considered foundational to the field of metascience.^[9] In a related study with Jeremy Howick and Despina Koletsi, Ioannidis showed that only a minority of medical interventions are supported by ‘high quality’ evidence according to The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. ^[10] Later meta-research identified widespread difficulty in replicating results in many scientific fields, including psychology and medicine. This problem was termed «the replication crisis». Metascience has grown as a reaction to the replication crisis and to concerns about waste in research.^[11]

Many prominent publishers are interested in meta-research and in improving the quality of their publications. Top journals such as Science, The Lancet, and Nature, provide ongoing coverage of meta-research and problems with reproducibility.^[12] In 2012 PLOS ONE launched a Reproducibility Initiative. In 2015 Biomed Central introduced a minimum-standards-of-reporting checklist to four titles.

The first international conference in the broad area of meta-research was the Research Waste/EQUATOR conference held in Edinburgh in 2015; the first international conference on peer review was the Peer Review Congress held in 1989.^[13] In 2016, Research Integrity and Peer Review was launched. The journal’s opening editorial called for «research that will increase our understanding and suggest potential solutions to issues related to peer review, study reporting, and research and publication ethics».^[14]

Fields and topics of meta-research[edit]

Metascience can be categorized into five major areas of interest: Methods, Reporting, Reproducibility, Evaluation, and Incentives. These correspond, respectively, with how to perform, communicate, verify, evaluate, and reward research.^[1]

Methods[edit]

Metascience seeks to identify poor research practices, including biases in research, poor study design, abuse of statistics, and to find methods to reduce these practices.^[1] Meta-research has identified numerous biases in scientific literature.^[15] Of particular note is the widespread misuse of p-values and abuse of statistical significance.^[16]

Scientific data science[edit]

Scientific data science is the use of data science to analyse research papers. It encompasses both qualitative and quantitative methods. Research in scientific data science includes fraud detection^[17] and citation network analysis.^[18]

Journalology[edit]

Journalology, also known as publication science, is the scholarly study of all aspects of the academic publishing process.^[19][20] The field seeks to improve the quality of scholarly research by implementing evidence-based practices in academic publishing.^[21] The term «journalology» was coined by Stephen Lock, the former editor-in-chief of The BMJ. The first Peer Review Congress, held in 1989 in Chicago, Illinois, is considered a pivotal moment in the founding of journalology as a distinct field.^[21] The field of journalology has been influential in pushing for study pre-registration in science, particularly in clinical trials. Clinical-trial registration is now expected in most countries.^[21]

Reporting[edit]

Meta-research has identified poor practices in reporting, explaining, disseminating and popularizing research, particularly within the social and health sciences. Poor reporting makes it difficult to accurately interpret the results of scientific studies, to replicate studies, and to identify biases and conflicts of interest in the authors. Solutions include the implementation of reporting standards, and greater transparency in scientific studies (including better requirements for disclosure of conflicts of interest). There is an attempt to standardize reporting of data and methodology through the creation of guidelines by reporting agencies such as CONSORT and the larger EQUATOR Network.^[1]

Reproducibility[edit]

The replication crisis is an ongoing methodological crisis in which it has been found that many scientific studies are difficult or impossible to replicate.^[22][23] While the crisis has its roots in the meta-research of the mid- to late-1900s, the phrase «replication crisis» was not coined until the early 2010s^[24] as part of a growing awareness of the problem.^[1] The replication crisis particularly affects psychology (especially social psychology) and medicine,^[25][26] including cancer research.^[27][28] Replication is an essential part of the scientific process, and the widespread failure of replication puts into question the reliability of affected fields.^[29]

Moreover, replication of research (or failure to replicate) is considered less influential than original research, and is less likely to be published in many fields. This discourages the reporting of, and even attempts to replicate, studies.^[30][31]

Evaluation and incentives[edit]

Metascience seeks to create a scientific foundation for peer review. Meta-research evaluates peer review systems including pre-publication peer review, post-publication peer review, and open peer review. It also seeks to develop better research funding criteria.^[1]

Metascience seeks to promote better research through better incentive systems. This includes studying the accuracy, effectiveness, costs, and benefits of different approaches to ranking and evaluating research and those who perform it.^[1] Critics argue that perverse incentives have created a publish-or-perish environment in academia which promotes the production of junk science, low quality research, and false positives.^[32][33] According to Brian Nosek, «The problem that we face is that the incentive system is focused almost entirely on getting research published, rather than on getting research right.»^[34] Proponents of reform seek to structure the incentive system to favor higher-quality results.^[35] For example, by quality being judged on the basis of narrative expert evaluations («rather than [only or mainly] indices»), institutional evaluation criteria, guaranteeing of transparency, and professional standards.^[36]

Contributorship

Studies proposed machine-readable standards and (a taxonomy of) badges for science publication management systems that hones in on contributorship – who has contributed what and how much of the research labor – rather that using traditional concept of plain authorship – who was involved in any way creation of a publication.^{[37][38][39][40]} A study pointed out one of the problems associated with the ongoing neglect of contribution nuanciation – it found that «the number of publications has ceased to be a good metric as a result of longer author lists, shorter papers, and surging publication numbers».^[41]

Assessment factors

Factors other than a submission’s merits can substantially influence peer reviewers’ evaluations.^[42] Such factors may however also be important such as the use of track-records about the veracity of a researchers’ prior publications and its alignment with public interests. Nevertheless, evaluation systems – include those of peer-review – may substantially lack mechanisms and criteria that are oriented or well-performingly oriented towards merit, real-world positive impact, progress and public usefulness rather than analytical indicators such as number of citations or altmetrics even when such can be used as partial indicators of such ends.^[43][44] Rethinking of the academic reward structure «to offer more formal recognition for intermediate products, such as data» could have positive impacts and reduce data withholding.^[45]

Recognition of training

A commentary noted that academic rankings don’t consider where (country and institute) the respective researchers were trained.^[46]

Scientometrics[edit]

Scientometrics concerns itself with measuring bibliographic data in scientific publications. Major research issues include the measurement of the impact of research papers and academic journals, the understanding of scientific citations, and the use of such measurements in policy and management contexts.^[47] Studies suggest that «metrics used to measure academic success, such as the number of publications, citation number, and impact factor, have not changed for decades» and have to some degrees «ceased» to be good measures,^[41] leading to issues such as «overproduction, unnecessary fragmentations, overselling, predatory journals (pay and publish), clever plagiarism, and deliberate obfuscation of scientific results so as to sell and oversell».^[48]

Novel tools in this area include systems to quantify how much the cited-node informs the citing-node.^[49] This can be used to convert unweighted citation networks to a weighted one and then for importance assessment, deriving «impact metrics for the various entities involved, like the publications, authors etc»^[50] as well as, among other tools, for search engine- and recommendation systems.

Science governance[edit]

Science funding and science governance can also be explored and informed by metascience.^[51]

Incentives[edit]

Various interventions such as prioritization can be important. For instance, the concept of differential technological development refers to deliberately developing technologies – e.g. control-, safety- and policy-technologies versus risky biotechnologies – at different precautionary paces to decrease risks, mainly global catastrophic risk, by influencing the sequence in which technologies are developed.^[52][53] Relying only on the established form of legislation and incentives to ensure the right outcomes may not be adequate as these may often be too slow^[54] or inappropriate.

Other incentives to govern science and related processes, including via metascience-based reforms, may include ensuring accountability to the public (in terms of e.g. accessibility of, especially publicly-funded, research or of it addressing various research topics of public interest in serious manners), increasing the qualified productive scientific workforce, improving the efficiency of science to improve problem-solving in general, and facilitating that unambiguous societal needs based on solid scientific evidence – such as about human physiology – are adequately prioritized and addressed. Such interventions, incentives and intervention-designs can be subjects of metascience.

Science funding and awards[edit]

Scientific awards are one category of science incentives. Metascience can explore existing and hypothetical systems of science awards. For instance, it found that work honored by Nobel prizes clusters in only a few scientific fields with only 36/71 having received at least one Nobel prize of the 114/849 domains science could be divided into according to their DC2 and DC3 classification systems. Five of the 114 domains were shown to make up over half of the Nobel prizes awarded 1995–2017 (particle physics [14%], cell biology [12.1%], atomic physics [10.9%], neuroscience [10.1%], molecular chemistry [5.3%]).^[56][57]

A study found that delegation of responsibility by policy-makers – a centralized authority-based top-down approach – for knowledge production and appropriate funding to science with science subsequently somehow delivering «reliable and useful knowledge to society» is too simple.^[51]

Measurements show that allocation of bio-medical resources can be more strongly correlated to previous allocations and research than to burden of diseases.^[58]

A study suggests that «[i]f peer review is maintained as the primary mechanism of arbitration in the competitive selection of research reports and funding, then the scientific community needs to make sure it is not arbitrary».^[42]

Studies indicate there to is a need to «reconsider how we measure success» (see #Factors of success and progress).^[41]

Funding data

Funding information from grant databases and funding acknowledgment sections can be sources of data for scientometrics studies, e.g. for investigating or recognition of the impact of funding entities on the development of science and technology.^[59]

Research questions and coordination[edit]

Risk governance[edit]

See also: § Differential R&D

Science communication and public use[edit]

It has been argued that «science has two fundamental attributes that underpin its value as a global public good: that knowledge claims and the evidence on which they are based are made openly available to scrutiny, and that the results of scientific research are communicated promptly and efficiently».^[73] Metascientific research is exploring topics of science communication such as media coverage of science, science journalism and online communication of results by science educators and scientists.^{[74][75][76][77]} A study found that the «main incentive academics are offered for using social media is amplification» and that it should be «moving towards an institutional culture that focuses more on how these [or such] platforms can facilitate real engagement with research».^[78] Science communication may also involve the communication of societal needs, concerns and requests to scientists.

Alternative metrics tools

Alternative metrics tools can be used not only for help in assessment (performance and impact)^[58] and findability, but also aggregate many of the public discussions about a scientific paper in social media such as reddit, citations on Wikipedia, and reports about the study in the news media which can then in turn be analyzed in metascience or provided and used by related tools.^[79] In terms of assessment and findability, altmetrics rate publications’ performance or impact by the interactions they receive through social media or other online platforms,^[80] which can for example be used for sorting recent studies by measured impact, including before other studies are citing them. The specific procedures of established altmetrics are not transparent^[80] and the used algorithms can not be customized or altered by the user as open source software can. A study has described various limitations of altmetrics and points «toward avenues for continued research and development».^[81] They are also limited in their use as a primary tool for researchers to find received constructive feedback. (see above)

Societal implications and applications

It has been suggested that it may benefit science if «intellectual exchange—particularly regarding the societal implications and applications of science and technology—are better appreciated and incentivized in the future».^[58]

Knowledge integration

Primary studies «without context, comparison or summary are ultimately of limited value» and various types^{[additional citation(s) needed]} of research syntheses and summaries integrate primary studies.^[82] Progress in key social-ecological challenges of the global environmental agenda is «hampered by a lack of integration and synthesis of existing scientific evidence», with a «fast-increasing volume of data», compartmentalized information and generally unmet evidence synthesis challenges.^[83] According to Khalil, researchers are facing the problem of too many papers – e.g. in March 2014 more than 8,000 papers were submitted to arXiv – and to «keep up with the huge amount of literature, researchers use reference manager software, they make summaries and notes, and they rely on review papers to provide an overview of a particular topic». He notes that review papers are usually (only)» for topics in which many papers were written already, and they can get outdated quickly» and suggests «wiki-review papers» that get continuously updated with new studies on a topic and summarize many studies’ results and suggest future research.^[84] A study suggests that if a scientific publication is being cited in a Wikipedia article this could potentially be considered as an indicator of some form of impact for this publication,^[80] for example as this may, over time, indicate that the reference has contributed to a high-level of summary of the given topic.

Further information: § Knowledge integration and living documents

Science journalism

Science journalists play an important role in the scientific ecosystem and in science communication to the public and need to «know how to use, relevant information when deciding whether to trust a research finding, and whether and how to report on it», vetting the findings that get transmitted to the public.^[85]

Science education[edit]

Some studies investigate science education, e.g. the teaching about selected scientific controversies^[86] and historical discovery process of major scientific conclusions,^[87] and common scientific misconceptions.^[88] Education can also be a topic more generally such as how to improve the quality of scientific outputs and reduce the time needed before scientific work or how to enlarge and retain various scientific workforces.

Science misconceptions and anti-science attitudes[edit]

Many students have misconceptions about what science is and how it works.^[89] Anti-science attitudes and beliefs are also a subject of research.^[90][91] Hotez suggests antiscience «has emerged as a dominant and highly lethal force, and one that threatens global security», and that there is a need for «new infrastructure» that mitigates it.^[92]

Evolution of sciences[edit]

Scientific practice[edit]

Metascience can investigate how scientific processes evolve over time. A study found that teams are growing in size, «increasing by an average of 17% per decade».^[58] (see labor advantage below)

It was found that prevalent forms of non-open access publication and prices charged for many conventional journals – even for publicly funded papers – are unwarranted, unnecessary – or suboptimal – and detrimental barriers to scientific progress.^{[73][95][96][97]} Open access can save considerable amounts of financial resources, which could be used otherwise, and level the playing field for researchers in developing countries.^[98] There are substantial expenses for subscriptions, gaining access to specific studies, and for article processing charges. Paywall: The Business of Scholarship is a documentary on such issues.^[99]

Another topic are the established styles of scientific communication (e.g. long text-form studies and reviews) and the scientific publishing practices – there are concerns about a «glacial pace» of conventional publishing.^[100] The use of preprint-servers to publish study-drafts early is increasing and open peer review,^[101] new tools to screen studies,^[102] and improved matching of submitted manuscripts to reviewers^[103] are among the proposals to speed up publication.

Science overall and intrafield developments[edit]

Studies have various kinds of metadata which can be utilized, complemented and made accessible in useful ways. OpenAlex is a free online index of over 200 million scientific documents that integrates and provides metadata such as sources, citations, author information, scientific fields and research topics. Its API and open source website can be used for metascience, scientometrics and novel tools that query this semantic web of papers.^{[105][106][107]} Another project under development, Scholia, uses metadata of scientific publications for various visualizations and aggregation features such as providing a simple user interface summarizing literature about a specific feature of the SARS-CoV-2 virus using Wikidata’s «main subject» property.^[108]

Subject-level resolutions

Beyond metadata explicitly assigned to studies by humans, natural language processing and AI can be used to assign research publications to topics – one study investigating the impact of science awards used such to associate a paper’s text (not just keywords) with the linguistic content of Wikipedia’s scientific topics pages («pages are created and updated by scientists and users through crowdsourcing»), creating meaningful and plausible classifications of high-fidelity scientific topics for further analysis or navigability.^[109]

Further information: § Topic mapping

Growth or stagnation of science overall[edit]

Metascience research is investigating the growth of science overall, using e.g. data on the number of publications in bibliographic databases. A study found segments with different growth rates appear related to phases of «economic (e.g., industrialization)» – money is considered as necessary input to the science system – «and/or political developments (e.g., Second World War)». It also confirmed a recent exponential growth in the volume of scientific literature and calculated an average doubling period of 17.3 years.^[111]

However, others have pointed out that is difficult to measure scientific progress in meaningful ways, partly because it’s hard to accurately evaluate how important any given scientific discovery is. A variety of perspectives of the trajectories of science overall (impact, number of major discoveries, etc) have been described in books and articles, including that science is becoming harder (per dollar or hour spent), that if science «slowing today, it is because science has remained too focused on established fields», that papers and patents are increasingly less likely to be «disruptive» in terms of breaking with the past as measured by the «CD index»,^[93] and that there is a great stagnation – possibly as part of a larger trend^[112] – whereby e.g. «things haven’t changed nearly as much since the 1970s» when excluding the computer and the Internet.

Better understanding of potential slowdowns according to some measures could be a major opportunity to improve humanity’s future.^[113] For example, emphasis on citations in the measurement of scientific productivity, information overloads,^[112] reliance on a narrower set of existing knowledge (which may include narrow specialization and related contemporary practices) ,^[93] and risk-avoidant funding structures^[114] may have «toward incremental science and away from exploratory projects that are more likely to fail».^[115] The study that introduced the «CD index» suggests the overall number of papers has risen while the total of «highly disruptive» papers as measured by the index hasn’t (notably, the 1998 discovery of the accelerating expansion of the universe has a CD index of 0). Their results also suggest scientists and inventors «may be struggling to keep up with the pace of knowledge expansion».^[116][93]

Various ways of measuring «novelty» of studies, novelty metrics,^[115] have been proposed to balance a potential anti-novelty bias – such as textual analysis^[115] or measuring whether it makes first-time-ever combinations of referenced journals, taking into account the difficulty.^[117] Other approaches include pro-actively funding risky projects.^[58] (see above)

Topic mapping[edit]

Science maps could show main interrelated topics within a certain scientific domain, their change over time, and their key actors (researchers, institutions, journals). They may help find factors determine the emergence of new scientific fields and the development of interdisciplinary areas and could be relevant for science policy purposes.^[118] (see above) Theories of scientific change could guide «the exploration and interpretation of visualized intellectual structures and dynamic patterns».^[119] The maps can show the intellectual, social or conceptual structure of a research field.^[120] Beyond visual maps, expert survey-based studies and similar approaches could identify understudied or neglected societally important areas, topic-level problems (such as stigma or dogma), or potential misprioritizations.^{[additional citation(s) needed]} Examples of such are studies about policy in relation to public health^[121] and the social science of climate change mitigation where it has been estimated that only 0.12% of all funding for climate-related research is spent on such despite the most urgent puzzle at the current juncture being working out how to mitigate climate change, whereas the natural science of climate change is already well established.

There are also studies that map a scientific field or a topic such as the study of the use of research evidence in policy and practice, partly using surveys.^[123]

Controversies, current debates and disagreement[edit]

See also: § scite.ai, and § Topic mapping

Some research is investigating scientific controversy or controveries, and may identify currently ongoing major debates (e.g. open questions), and disagreement between scientists or studies.^{[additional citation(s) needed]} One study suggests the level of disagreement was highest in the social sciences and humanities (0.61%), followed by biomedical and health sciences (0.41%), life and earth sciences (0.29%); physical sciences and engineering (0.15%), and mathematics and computer science (0.06%).^[124] Such research may also show, where the disagreements are, especially if they cluster, including visually such as with cluster diagrams.

Challenges of interpretation of pooled results[edit]

Studies about a specific research question or research topic are often reviewed in the form of higher-level overviews in which results from various studies are integrated, compared, critically analyzed and interpreted. Examples of such works are scientific reviews and meta-analyses. These and related practices face various challenges and are a subject of metascience.

Various issues with included or available studies such as, for example, heterogeneity of methods used may lead to faulty conclusions of the meta-analysis.^[129]

Knowledge integration and living documents[edit]

Various problems require swift integration of new and existing science-based knowledge. Especially setting where there are a large number of loosely related projects and initiatives benefit from a common ground or «commons».^[108]

Evidence synthesis can be applied to important and, notably, both relatively urgent and certain global challenges: «climate change, energy transitions, biodiversity loss, antimicrobial resistance, poverty eradication and so on». It was suggested that a better system would keep summaries of research evidence up to date via living systematic reviews – e.g. as living documents. While the number of scientific papers and data (or information and online knowledge) has risen substantially,^{[additional citation(s) needed]} the number of published academic systematic reviews has risen from «around 6,000 in 2011 to more than 45,000 in 2021».^[130] An evidence-based approach is important for progress in science, policy, medical and other practices. For example, meta-analyses can quantify what is known and identify what is not yet known^[82] and place «truly innovative and highly interdisciplinary ideas» into the context of established knowledge which may enhance their impact.^[58] (see above)

Factors of success and progress[edit]

See also: § Growth or stagnation of science overall

It has been hypothesized that a deeper understanding of factors behind successful science could «enhance prospects of science as a whole to more effectively address societal problems».^[58]

Novel ideas and disruptive scholarship

Two metascientists reported that «structures fostering disruptive scholarship and focusing attention on novel ideas» could be important as in a growing scientific field citation flows disproportionately consolidate to already well-cited papers, possibly slowing and inhibiting canonical progress.^[131][132] A study concluded that to enhance impact of truly innovative and highly interdisciplinary novel ideas, they should be placed in the context of established knowledge.^[58]

Mentorship, partnerships and social factors

Other researchers reported that the most successful – in terms of «likelihood of prizewinning, National Academy of Science (NAS) induction, or superstardom» – protégés studied under mentors who published research for which they were conferred a prize after the protégés’ mentorship. Studying original topics rather than these mentors’ research-topics was also positively associated with success.^[133][134] Highly productive partnerships are also a topic of research – e.g. «super-ties» of frequent co-authorship of two individuals who can complement skills, likely also the result of other factors such as mutual trust, conviction, commitment and fun.^[135][58]

Study of successful scientists and processes, general skills and activities

The emergence or origin of ideas by successful scientists is also a topic of research, for example reviewing existing ideas on how Mendel made his discoveries,^[136] – or more generally, the process of discovery by scientists. Science is a «multifaceted process of appropriation, copying, extending, or combining ideas and inventions» [and other types of knowledge or information], and not an isolated process.^[58] There are also few studies investigating scientists’ habits, common modes of thinking, reading habits, use of information sources, digital literacy skills, and workflows.^{[137][138][139][140][141]}

Labor advantage

A study theorized that in many disciplines, larger scientific productivity or success by elite universities can be explained by their larger pool of available funded laborers.^{[142][143][further explanation needed]}

Ultimate impacts

Success (in science) is often measured in terms of metrics like citations, not in terms of the eventual or potential impact on lives and society, which awards (see above) sometimes do.^{[additional citation(s) needed]} Problems with such metrics are roughly outlined elsewhere in this article and include that reviews replace citations to primary studies.^[82] There are also proposals for changes to the academic incentives systems that increase the recognition of societal impact in the research process.^[144]

Progress studies

A proposed field of «Progress Studies» could investigate how scientists (or funders or evaluators of scientists) should be acting, «figuring out interventions» and study progress itself.^[145] The field was explicitly proposed in a 2019 essay and described as an applied science that prescribes action.^[146]

As and for acceleration of progress

A study suggests that improving the way science is done could accelerate the rate of scientific discovery and its applications which could be useful for finding urgent solutions to humanity’s problems, improve humanity’s conditions, and enhance understanding of nature. Metascientific studies can seek to identify aspects of science that need improvement, and develop ways to improve them.^[84] If science is accepted as the fundamental engine of economic growth and social progress, this could raise «the question of what we – as a society – can do to accelerate science, and to direct science toward solving society’s most important problems.»^[147] However, one of the authors clarified that a one-size-fits-all approach is not thought to be right answer – for example, in funding, DARPA models, curiosity-driven methods, allowing «a single reviewer to champion a project even if his or her peers do not agree», and various other approaches all have their uses. Nevertheless, evaluation of them can help build knowledge of what works or works best.^[114]

Reforms[edit]

Meta-research identifying flaws in scientific practice has inspired reforms in science. These reforms seek to address and fix problems in scientific practice which lead to low-quality or inefficient research.

A 2015 study lists «fragmented» efforts in meta-research.^[1]

Pre-registration[edit]

The practice of registering a scientific study before it is conducted is called pre-registration. It arose as a means to address the replication crisis. Pregistration requires the submission of a registered report, which is then accepted for publication or rejected by a journal based on theoretical justification, experimental design, and the proposed statistical analysis. Pre-registration of studies serves to prevent publication bias (e.g. not publishing negative results), reduce data dredging, and increase replicability.^[148][149]

Reporting standards[edit]

Studies showing poor consistency and quality of reporting have demonstrated the need for reporting standards and guidelines in science, which has led to the rise of organisations that produce such standards, such as CONSORT (Consolidated Standards of Reporting Trials) and the EQUATOR Network.

The EQUATOR (Enhancing the QUAlity and Transparency Of health Research)^[150] Network is an international initiative aimed at promoting transparent and accurate reporting of health research studies to enhance the value and reliability of medical research literature.^[151] The EQUATOR Network was established with the goals of raising awareness of the importance of good reporting of research, assisting in the development, dissemination and implementation of reporting guidelines for different types of study designs, monitoring the status of the quality of reporting of research studies in the health sciences literature, and conducting research relating to issues that impact the quality of reporting of health research studies.^[152] The Network acts as an «umbrella» organisation, bringing together developers of reporting guidelines, medical journal editors and peer reviewers, research funding bodies, and other key stakeholders with a mutual interest in improving the quality of research publications and research itself.

Applications[edit]

The areas of application of metascience include ICTs, medicine, psychology and physics.

ICTs[edit]

Metascience is used in the creation and improvement of technical systems (ICTs) and standards of science evaluation, incentivation, communication, commissioning, funding, regulation, production, management, use and publication. Such can be called «applied metascience»^{[153][better source needed]} and may seek to explore ways to increase quantity, quality and positive impact of research. One example for such is the development of alternative metrics.^[58]

Study screening and feedback

Various websites or tools also identify inappropriate studies and/or enable feedback such as PubPeer, Cochrane’s Risk of Bias Tool^[154] and RetractionWatch. Medical and academic disputes are as ancient as antiquity and a study calls for research into «constructive and obsessive criticism» and into policies to «help strengthen social media into a vibrant forum for discussion, and not merely an arena for gladiator matches».^[155] Feedback to studies can be found via altmetrics which is often integrated at the website of the study – most often as an embedded Altmetrics badge – but may often be incomplete, such as only showing social media discussions that link to the study directly but not those that link to news reports about the study. (see above)

Tools used, modified, extended or investigated

Tools may get developed with metaresearch or can be used or investigated by such. Notable examples may include:

• The tool scite.ai aims to track and link citations of papers as ‘Supporting’, ‘Mentioning’ or ‘Contrasting’ the study.^{[156][157][158]}
• The Scite Reference Check bot is an extension of scite.ai that scans new article PDFs «for references to retracted papers, and posts both the citing and retracted papers on Twitter» and also «flags when new studies cite older ones that have issued corrections, errata, withdrawals, or expressions of concern».^[158] Studies have suggested as few as 4% of citations to retracted papers clearly recognize the retraction.^[158]
• Search engines like Google Scholar are used to find studies and the notification service Google Alerts enables notifications for new studies matching specified search terms. Scholarly communication infrastructure includes search databases.^[159]
• Shadow library Sci-hub is a topic of metascience^[160]
• Personal knowledge management systems for research-, knowledge- and task management, such as saving information in organized ways^[161] with multi-document text editors for future use^[162][163] Such systems could be described as part of, along with e.g. Web browser (tabs-addons^[164] etc) and search software,^{[additional citation(s) needed]} «mind-machine partnerships» that could be investigated by metascience for how they could improve science.^[58]
• Scholia – efforts to open scholarly publication metadata and use it via Wikidata.^[165] (see above)
• Various software enables common metascientific practices such as bibliometric analysis.^[166]

Development

According to a study «a simple way to check how often studies have been repeated, and whether or not the original findings are confirmed» is needed due to reproducibility issues in science.^[167][168] A study suggests a tool for screening studies for early warning signs for research fraud.^[169]

Medicine[edit]

Clinical research in medicine is often of low quality, and many studies cannot be replicated.^[170][171] An estimated 85% of research funding is wasted.^[172] Additionally, the presence of bias affects research quality.^[173] The pharmaceutical industry exerts substantial influence on the design and execution of medical research. Conflicts of interest are common among authors of medical literature^[174] and among editors of medical journals. While almost all medical journals require their authors to disclose conflicts of interest, editors are not required to do so.^[175] Financial conflicts of interest have been linked to higher rates of positive study results. In antidepressant trials, pharmaceutical sponsorship is the best predictor of trial outcome.^[176]

Blinding is another focus of meta-research, as error caused by poor blinding is a source of experimental bias. Blinding is not well reported in medical literature, and widespread misunderstanding of the subject has resulted in poor implementation of blinding in clinical trials.^[177] Furthermore, failure of blinding is rarely measured or reported.^[178] Research showing the failure of blinding in antidepressant trials has led some scientists to argue that antidepressants are no better than placebo.^[179][180] In light of meta-research showing failures of blinding, CONSORT standards recommend that all clinical trials assess and report the quality of blinding.^[181]

Studies have shown that systematic reviews of existing research evidence are sub-optimally used in planning a new research or summarizing the results.^[182] Cumulative meta-analyses of studies evaluating the effectiveness of medical interventions have shown that many clinical trials could have been avoided if a systematic review of existing evidence was done prior to conducting a new trial.^{[183][184][185]} For example, Lau et al.^[183] analyzed 33 clinical trials (involving 36974 patients) evaluating the effectiveness of intravenous streptokinase for acute myocardial infarction. Their cumulative meta-analysis demonstrated that 25 of 33 trials could have been avoided if a systematic review was conducted prior to conducting a new trial. In other words, randomizing 34542 patients was potentially unnecessary. One study^[186] analyzed 1523 clinical trials included in 227 meta-analyses and concluded that «less than one quarter of relevant prior studies» were cited. They also confirmed earlier findings that most clinical trial reports do not present systematic review to justify the research or summarize the results.^[186]

Many treatments used in modern medicine have been proven to be ineffective, or even harmful. A 2007 study by John Ioannidis found that it took an average of ten years for the medical community to stop referencing popular practices after their efficacy was unequivocally disproven.^[187][188]

Psychology[edit]

Metascience has revealed significant problems in psychological research. The field suffers from high bias, low reproducibility, and widespread misuse of statistics.^{[189][190][191]} The replication crisis affects psychology more strongly than any other field; as many as two-thirds of highly publicized findings may be impossible to replicate.^[192] Meta-research finds that 80-95% of psychological studies support their initial hypotheses, which strongly implies the existence of publication bias.^[193]

The replication crisis has led to renewed efforts to re-test important findings.^[194][195] In response to concerns about publication bias and p-hacking, more than 140 psychology journals have adopted result-blind peer review, in which studies are pre-registered and published without regard for their outcome.^[196] An analysis of these reforms estimated that 61 percent of result-blind studies produce null results, in contrast with 5 to 20 percent in earlier research. This analysis shows that result-blind peer review substantially reduces publication bias.^[193]

Psychologists routinely confuse statistical significance with practical importance, enthusiastically reporting great certainty in unimportant facts.^[197] Some psychologists have responded with an increased use of effect size statistics, rather than sole reliance on the p values.^{[citation needed]}

Physics[edit]

Richard Feynman noted that estimates of physical constants were closer to published values than would be expected by chance. This was believed to be the result of confirmation bias: results that agreed with existing literature were more likely to be believed, and therefore published. Physicists now implement blinding to prevent this kind of bias.^[198]

Organizations and institutes[edit]

There are several organizations and universities across the globe which work on meta-research – these include the Meta-Research Innovation Center at Berlin,^[199] the Meta-Research Innovation Center at Stanford,^[200][201] the Meta-Research Center at Tilburg University, the Meta-research & Evidence Synthesis Unit, The George Institute for Global Health at India and Center for Open Science. Organizations that develop tools for metascience include Our Research, Center for Scientific Integrity and altmetrics companies. There is an annual Metascience Conference.^[202]

See also[edit]

References[edit]

Further reading[edit]

• Lydia Denworth, «A Significant Problem: Standard scientific methods are under fire. Will anything change?», Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67.
  • «The use of p values for nearly a century [since 1925] to determine statistical significance of experimental results has contributed to an illusion of certainty and [to] reproducibility crises in many scientific fields. There is growing determination to reform statistical analysis… Some [researchers] suggest changing statistical methods, whereas others would do away with a threshold for defining «significant» results.» (p. 63.)
• Harris, Richard (2017). Rigor Mortis: How Sloppy Science Creates Worthless Cures, Crushes Hopes, and Wastes Billions. Basic Books. ISBN 978-0465097913.
• Fortunato, Santo; Bergstrom, Carl T.; et al. (2 March 2018). «Science of science». Science. 359 (6379): eaao0185. doi:10.1126/science.aao0185. PMC 5949209. PMID 29496846.

External links[edit]

Journals

• Minerva: A Journal of Science, Learning and Policy
• Research Integrity and Peer Review
• Research Policy
• Science and Public Policy

Conferences

• Annual Metascience Conference

Metascience (also known as meta-research) is the use of scientific methodology to study science itself. Metascience seeks to increase the quality of scientific research while reducing inefficiency. It is also known as «research on research» and «the science of science«, as it uses research methods to study how research is done and find where improvements can be made. Metascience concerns itself with all fields of research and has been described as «a bird’s eye view of science».^[1] In the words of John Ioannidis, «Science is the best thing that has happened to human beings … but we can do it better.»^[2]

In 1966, an early meta-research paper examined the statistical methods of 295 papers published in ten high-profile medical journals. It found that «in almost 73% of the reports read … conclusions were drawn when the justification for these conclusions was invalid.» Meta-research in the following decades found many methodological flaws, inefficiencies, and poor practices in research across numerous scientific fields. Many scientific studies could not be reproduced, particularly in medicine and the soft sciences. The term «replication crisis» was coined in the early 2010s as part of a growing awareness of the problem.^[3]

Measures have been implemented to address the issues revealed by metascience. These measures include the pre-registration of scientific studies and clinical trials as well as the founding of organizations such as CONSORT and the EQUATOR Network that issue guidelines for methodology and reporting. There are continuing efforts to reduce the misuse of statistics, to eliminate perverse incentives from academia, to improve the peer review process, to systematically collect data about the scholarly publication system,^[4] to combat bias in scientific literature, and to increase the overall quality and efficiency of the scientific process.

History[edit]

In 1966, an early meta-research paper examined the statistical methods of 295 papers published in ten high-profile medical journals. It found that, «in almost 73% of the reports read … conclusions were drawn when the justification for these conclusions was invalid.»^[6] In 2005, John Ioannidis published a paper titled «Why Most Published Research Findings Are False», which argued that a majority of papers in the medical field produce conclusions that are wrong.^[5] The paper went on to become the most downloaded paper in the Public Library of Science^[7][8] and is considered foundational to the field of metascience.^[9] In a related study with Jeremy Howick and Despina Koletsi, Ioannidis showed that only a minority of medical interventions are supported by ‘high quality’ evidence according to The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. ^[10] Later meta-research identified widespread difficulty in replicating results in many scientific fields, including psychology and medicine. This problem was termed «the replication crisis». Metascience has grown as a reaction to the replication crisis and to concerns about waste in research.^[11]

Many prominent publishers are interested in meta-research and in improving the quality of their publications. Top journals such as Science, The Lancet, and Nature, provide ongoing coverage of meta-research and problems with reproducibility.^[12] In 2012 PLOS ONE launched a Reproducibility Initiative. In 2015 Biomed Central introduced a minimum-standards-of-reporting checklist to four titles.

The first international conference in the broad area of meta-research was the Research Waste/EQUATOR conference held in Edinburgh in 2015; the first international conference on peer review was the Peer Review Congress held in 1989.^[13] In 2016, Research Integrity and Peer Review was launched. The journal’s opening editorial called for «research that will increase our understanding and suggest potential solutions to issues related to peer review, study reporting, and research and publication ethics».^[14]

Fields and topics of meta-research[edit]

Metascience can be categorized into five major areas of interest: Methods, Reporting, Reproducibility, Evaluation, and Incentives. These correspond, respectively, with how to perform, communicate, verify, evaluate, and reward research.^[1]

Methods[edit]

Metascience seeks to identify poor research practices, including biases in research, poor study design, abuse of statistics, and to find methods to reduce these practices.^[1] Meta-research has identified numerous biases in scientific literature.^[15] Of particular note is the widespread misuse of p-values and abuse of statistical significance.^[16]

Scientific data science[edit]

Scientific data science is the use of data science to analyse research papers. It encompasses both qualitative and quantitative methods. Research in scientific data science includes fraud detection^[17] and citation network analysis.^[18]

Journalology[edit]

Journalology, also known as publication science, is the scholarly study of all aspects of the academic publishing process.^[19][20] The field seeks to improve the quality of scholarly research by implementing evidence-based practices in academic publishing.^[21] The term «journalology» was coined by Stephen Lock, the former editor-in-chief of The BMJ. The first Peer Review Congress, held in 1989 in Chicago, Illinois, is considered a pivotal moment in the founding of journalology as a distinct field.^[21] The field of journalology has been influential in pushing for study pre-registration in science, particularly in clinical trials. Clinical-trial registration is now expected in most countries.^[21]

Reporting[edit]

Meta-research has identified poor practices in reporting, explaining, disseminating and popularizing research, particularly within the social and health sciences. Poor reporting makes it difficult to accurately interpret the results of scientific studies, to replicate studies, and to identify biases and conflicts of interest in the authors. Solutions include the implementation of reporting standards, and greater transparency in scientific studies (including better requirements for disclosure of conflicts of interest). There is an attempt to standardize reporting of data and methodology through the creation of guidelines by reporting agencies such as CONSORT and the larger EQUATOR Network.^[1]

Reproducibility[edit]

The replication crisis is an ongoing methodological crisis in which it has been found that many scientific studies are difficult or impossible to replicate.^[22][23] While the crisis has its roots in the meta-research of the mid- to late-1900s, the phrase «replication crisis» was not coined until the early 2010s^[24] as part of a growing awareness of the problem.^[1] The replication crisis particularly affects psychology (especially social psychology) and medicine,^[25][26] including cancer research.^[27][28] Replication is an essential part of the scientific process, and the widespread failure of replication puts into question the reliability of affected fields.^[29]

Moreover, replication of research (or failure to replicate) is considered less influential than original research, and is less likely to be published in many fields. This discourages the reporting of, and even attempts to replicate, studies.^[30][31]

Evaluation and incentives[edit]

Metascience seeks to create a scientific foundation for peer review. Meta-research evaluates peer review systems including pre-publication peer review, post-publication peer review, and open peer review. It also seeks to develop better research funding criteria.^[1]

Metascience seeks to promote better research through better incentive systems. This includes studying the accuracy, effectiveness, costs, and benefits of different approaches to ranking and evaluating research and those who perform it.^[1] Critics argue that perverse incentives have created a publish-or-perish environment in academia which promotes the production of junk science, low quality research, and false positives.^[32][33] According to Brian Nosek, «The problem that we face is that the incentive system is focused almost entirely on getting research published, rather than on getting research right.»^[34] Proponents of reform seek to structure the incentive system to favor higher-quality results.^[35] For example, by quality being judged on the basis of narrative expert evaluations («rather than [only or mainly] indices»), institutional evaluation criteria, guaranteeing of transparency, and professional standards.^[36]

Contributorship

Studies proposed machine-readable standards and (a taxonomy of) badges for science publication management systems that hones in on contributorship – who has contributed what and how much of the research labor – rather that using traditional concept of plain authorship – who was involved in any way creation of a publication.^{[37][38][39][40]} A study pointed out one of the problems associated with the ongoing neglect of contribution nuanciation – it found that «the number of publications has ceased to be a good metric as a result of longer author lists, shorter papers, and surging publication numbers».^[41]

Assessment factors

Factors other than a submission’s merits can substantially influence peer reviewers’ evaluations.^[42] Such factors may however also be important such as the use of track-records about the veracity of a researchers’ prior publications and its alignment with public interests. Nevertheless, evaluation systems – include those of peer-review – may substantially lack mechanisms and criteria that are oriented or well-performingly oriented towards merit, real-world positive impact, progress and public usefulness rather than analytical indicators such as number of citations or altmetrics even when such can be used as partial indicators of such ends.^[43][44] Rethinking of the academic reward structure «to offer more formal recognition for intermediate products, such as data» could have positive impacts and reduce data withholding.^[45]

Recognition of training

A commentary noted that academic rankings don’t consider where (country and institute) the respective researchers were trained.^[46]

Scientometrics[edit]

Scientometrics concerns itself with measuring bibliographic data in scientific publications. Major research issues include the measurement of the impact of research papers and academic journals, the understanding of scientific citations, and the use of such measurements in policy and management contexts.^[47] Studies suggest that «metrics used to measure academic success, such as the number of publications, citation number, and impact factor, have not changed for decades» and have to some degrees «ceased» to be good measures,^[41] leading to issues such as «overproduction, unnecessary fragmentations, overselling, predatory journals (pay and publish), clever plagiarism, and deliberate obfuscation of scientific results so as to sell and oversell».^[48]

Novel tools in this area include systems to quantify how much the cited-node informs the citing-node.^[49] This can be used to convert unweighted citation networks to a weighted one and then for importance assessment, deriving «impact metrics for the various entities involved, like the publications, authors etc»^[50] as well as, among other tools, for search engine- and recommendation systems.

Science governance[edit]

Science funding and science governance can also be explored and informed by metascience.^[51]

Incentives[edit]

Various interventions such as prioritization can be important. For instance, the concept of differential technological development refers to deliberately developing technologies – e.g. control-, safety- and policy-technologies versus risky biotechnologies – at different precautionary paces to decrease risks, mainly global catastrophic risk, by influencing the sequence in which technologies are developed.^[52][53] Relying only on the established form of legislation and incentives to ensure the right outcomes may not be adequate as these may often be too slow^[54] or inappropriate.

Other incentives to govern science and related processes, including via metascience-based reforms, may include ensuring accountability to the public (in terms of e.g. accessibility of, especially publicly-funded, research or of it addressing various research topics of public interest in serious manners), increasing the qualified productive scientific workforce, improving the efficiency of science to improve problem-solving in general, and facilitating that unambiguous societal needs based on solid scientific evidence – such as about human physiology – are adequately prioritized and addressed. Such interventions, incentives and intervention-designs can be subjects of metascience.

Science funding and awards[edit]

Scientific awards are one category of science incentives. Metascience can explore existing and hypothetical systems of science awards. For instance, it found that work honored by Nobel prizes clusters in only a few scientific fields with only 36/71 having received at least one Nobel prize of the 114/849 domains science could be divided into according to their DC2 and DC3 classification systems. Five of the 114 domains were shown to make up over half of the Nobel prizes awarded 1995–2017 (particle physics [14%], cell biology [12.1%], atomic physics [10.9%], neuroscience [10.1%], molecular chemistry [5.3%]).^[56][57]

A study found that delegation of responsibility by policy-makers – a centralized authority-based top-down approach – for knowledge production and appropriate funding to science with science subsequently somehow delivering «reliable and useful knowledge to society» is too simple.^[51]

Measurements show that allocation of bio-medical resources can be more strongly correlated to previous allocations and research than to burden of diseases.^[58]

A study suggests that «[i]f peer review is maintained as the primary mechanism of arbitration in the competitive selection of research reports and funding, then the scientific community needs to make sure it is not arbitrary».^[42]

Studies indicate there to is a need to «reconsider how we measure success» (see #Factors of success and progress).^[41]

Funding data

Funding information from grant databases and funding acknowledgment sections can be sources of data for scientometrics studies, e.g. for investigating or recognition of the impact of funding entities on the development of science and technology.^[59]

Research questions and coordination[edit]

Risk governance[edit]

See also: § Differential R&D

Science communication and public use[edit]

It has been argued that «science has two fundamental attributes that underpin its value as a global public good: that knowledge claims and the evidence on which they are based are made openly available to scrutiny, and that the results of scientific research are communicated promptly and efficiently».^[73] Metascientific research is exploring topics of science communication such as media coverage of science, science journalism and online communication of results by science educators and scientists.^{[74][75][76][77]} A study found that the «main incentive academics are offered for using social media is amplification» and that it should be «moving towards an institutional culture that focuses more on how these [or such] platforms can facilitate real engagement with research».^[78] Science communication may also involve the communication of societal needs, concerns and requests to scientists.

Alternative metrics tools

Alternative metrics tools can be used not only for help in assessment (performance and impact)^[58] and findability, but also aggregate many of the public discussions about a scientific paper in social media such as reddit, citations on Wikipedia, and reports about the study in the news media which can then in turn be analyzed in metascience or provided and used by related tools.^[79] In terms of assessment and findability, altmetrics rate publications’ performance or impact by the interactions they receive through social media or other online platforms,^[80] which can for example be used for sorting recent studies by measured impact, including before other studies are citing them. The specific procedures of established altmetrics are not transparent^[80] and the used algorithms can not be customized or altered by the user as open source software can. A study has described various limitations of altmetrics and points «toward avenues for continued research and development».^[81] They are also limited in their use as a primary tool for researchers to find received constructive feedback. (see above)

Societal implications and applications

It has been suggested that it may benefit science if «intellectual exchange—particularly regarding the societal implications and applications of science and technology—are better appreciated and incentivized in the future».^[58]

Knowledge integration

Primary studies «without context, comparison or summary are ultimately of limited value» and various types^{[additional citation(s) needed]} of research syntheses and summaries integrate primary studies.^[82] Progress in key social-ecological challenges of the global environmental agenda is «hampered by a lack of integration and synthesis of existing scientific evidence», with a «fast-increasing volume of data», compartmentalized information and generally unmet evidence synthesis challenges.^[83] According to Khalil, researchers are facing the problem of too many papers – e.g. in March 2014 more than 8,000 papers were submitted to arXiv – and to «keep up with the huge amount of literature, researchers use reference manager software, they make summaries and notes, and they rely on review papers to provide an overview of a particular topic». He notes that review papers are usually (only)» for topics in which many papers were written already, and they can get outdated quickly» and suggests «wiki-review papers» that get continuously updated with new studies on a topic and summarize many studies’ results and suggest future research.^[84] A study suggests that if a scientific publication is being cited in a Wikipedia article this could potentially be considered as an indicator of some form of impact for this publication,^[80] for example as this may, over time, indicate that the reference has contributed to a high-level of summary of the given topic.

Further information: § Knowledge integration and living documents

Science journalism

Science journalists play an important role in the scientific ecosystem and in science communication to the public and need to «know how to use, relevant information when deciding whether to trust a research finding, and whether and how to report on it», vetting the findings that get transmitted to the public.^[85]

Science education[edit]

Some studies investigate science education, e.g. the teaching about selected scientific controversies^[86] and historical discovery process of major scientific conclusions,^[87] and common scientific misconceptions.^[88] Education can also be a topic more generally such as how to improve the quality of scientific outputs and reduce the time needed before scientific work or how to enlarge and retain various scientific workforces.

Science misconceptions and anti-science attitudes[edit]

Many students have misconceptions about what science is and how it works.^[89] Anti-science attitudes and beliefs are also a subject of research.^[90][91] Hotez suggests antiscience «has emerged as a dominant and highly lethal force, and one that threatens global security», and that there is a need for «new infrastructure» that mitigates it.^[92]

Evolution of sciences[edit]

Scientific practice[edit]

Metascience can investigate how scientific processes evolve over time. A study found that teams are growing in size, «increasing by an average of 17% per decade».^[58] (see labor advantage below)

It was found that prevalent forms of non-open access publication and prices charged for many conventional journals – even for publicly funded papers – are unwarranted, unnecessary – or suboptimal – and detrimental barriers to scientific progress.^{[73][95][96][97]} Open access can save considerable amounts of financial resources, which could be used otherwise, and level the playing field for researchers in developing countries.^[98] There are substantial expenses for subscriptions, gaining access to specific studies, and for article processing charges. Paywall: The Business of Scholarship is a documentary on such issues.^[99]

Another topic are the established styles of scientific communication (e.g. long text-form studies and reviews) and the scientific publishing practices – there are concerns about a «glacial pace» of conventional publishing.^[100] The use of preprint-servers to publish study-drafts early is increasing and open peer review,^[101] new tools to screen studies,^[102] and improved matching of submitted manuscripts to reviewers^[103] are among the proposals to speed up publication.

Science overall and intrafield developments[edit]

Studies have various kinds of metadata which can be utilized, complemented and made accessible in useful ways. OpenAlex is a free online index of over 200 million scientific documents that integrates and provides metadata such as sources, citations, author information, scientific fields and research topics. Its API and open source website can be used for metascience, scientometrics and novel tools that query this semantic web of papers.^{[105][106][107]} Another project under development, Scholia, uses metadata of scientific publications for various visualizations and aggregation features such as providing a simple user interface summarizing literature about a specific feature of the SARS-CoV-2 virus using Wikidata’s «main subject» property.^[108]

Subject-level resolutions

Beyond metadata explicitly assigned to studies by humans, natural language processing and AI can be used to assign research publications to topics – one study investigating the impact of science awards used such to associate a paper’s text (not just keywords) with the linguistic content of Wikipedia’s scientific topics pages («pages are created and updated by scientists and users through crowdsourcing»), creating meaningful and plausible classifications of high-fidelity scientific topics for further analysis or navigability.^[109]

Further information: § Topic mapping

Growth or stagnation of science overall[edit]

Metascience research is investigating the growth of science overall, using e.g. data on the number of publications in bibliographic databases. A study found segments with different growth rates appear related to phases of «economic (e.g., industrialization)» – money is considered as necessary input to the science system – «and/or political developments (e.g., Second World War)». It also confirmed a recent exponential growth in the volume of scientific literature and calculated an average doubling period of 17.3 years.^[111]

However, others have pointed out that is difficult to measure scientific progress in meaningful ways, partly because it’s hard to accurately evaluate how important any given scientific discovery is. A variety of perspectives of the trajectories of science overall (impact, number of major discoveries, etc) have been described in books and articles, including that science is becoming harder (per dollar or hour spent), that if science «slowing today, it is because science has remained too focused on established fields», that papers and patents are increasingly less likely to be «disruptive» in terms of breaking with the past as measured by the «CD index»,^[93] and that there is a great stagnation – possibly as part of a larger trend^[112] – whereby e.g. «things haven’t changed nearly as much since the 1970s» when excluding the computer and the Internet.

Better understanding of potential slowdowns according to some measures could be a major opportunity to improve humanity’s future.^[113] For example, emphasis on citations in the measurement of scientific productivity, information overloads,^[112] reliance on a narrower set of existing knowledge (which may include narrow specialization and related contemporary practices) ,^[93] and risk-avoidant funding structures^[114] may have «toward incremental science and away from exploratory projects that are more likely to fail».^[115] The study that introduced the «CD index» suggests the overall number of papers has risen while the total of «highly disruptive» papers as measured by the index hasn’t (notably, the 1998 discovery of the accelerating expansion of the universe has a CD index of 0). Their results also suggest scientists and inventors «may be struggling to keep up with the pace of knowledge expansion».^[116][93]

Various ways of measuring «novelty» of studies, novelty metrics,^[115] have been proposed to balance a potential anti-novelty bias – such as textual analysis^[115] or measuring whether it makes first-time-ever combinations of referenced journals, taking into account the difficulty.^[117] Other approaches include pro-actively funding risky projects.^[58] (see above)

Topic mapping[edit]

Science maps could show main interrelated topics within a certain scientific domain, their change over time, and their key actors (researchers, institutions, journals). They may help find factors determine the emergence of new scientific fields and the development of interdisciplinary areas and could be relevant for science policy purposes.^[118] (see above) Theories of scientific change could guide «the exploration and interpretation of visualized intellectual structures and dynamic patterns».^[119] The maps can show the intellectual, social or conceptual structure of a research field.^[120] Beyond visual maps, expert survey-based studies and similar approaches could identify understudied or neglected societally important areas, topic-level problems (such as stigma or dogma), or potential misprioritizations.^{[additional citation(s) needed]} Examples of such are studies about policy in relation to public health^[121] and the social science of climate change mitigation where it has been estimated that only 0.12% of all funding for climate-related research is spent on such despite the most urgent puzzle at the current juncture being working out how to mitigate climate change, whereas the natural science of climate change is already well established.

There are also studies that map a scientific field or a topic such as the study of the use of research evidence in policy and practice, partly using surveys.^[123]

Controversies, current debates and disagreement[edit]

See also: § scite.ai, and § Topic mapping

Some research is investigating scientific controversy or controveries, and may identify currently ongoing major debates (e.g. open questions), and disagreement between scientists or studies.^{[additional citation(s) needed]} One study suggests the level of disagreement was highest in the social sciences and humanities (0.61%), followed by biomedical and health sciences (0.41%), life and earth sciences (0.29%); physical sciences and engineering (0.15%), and mathematics and computer science (0.06%).^[124] Such research may also show, where the disagreements are, especially if they cluster, including visually such as with cluster diagrams.

Challenges of interpretation of pooled results[edit]

Studies about a specific research question or research topic are often reviewed in the form of higher-level overviews in which results from various studies are integrated, compared, critically analyzed and interpreted. Examples of such works are scientific reviews and meta-analyses. These and related practices face various challenges and are a subject of metascience.

Various issues with included or available studies such as, for example, heterogeneity of methods used may lead to faulty conclusions of the meta-analysis.^[129]

Knowledge integration and living documents[edit]

Various problems require swift integration of new and existing science-based knowledge. Especially setting where there are a large number of loosely related projects and initiatives benefit from a common ground or «commons».^[108]

Evidence synthesis can be applied to important and, notably, both relatively urgent and certain global challenges: «climate change, energy transitions, biodiversity loss, antimicrobial resistance, poverty eradication and so on». It was suggested that a better system would keep summaries of research evidence up to date via living systematic reviews – e.g. as living documents. While the number of scientific papers and data (or information and online knowledge) has risen substantially,^{[additional citation(s) needed]} the number of published academic systematic reviews has risen from «around 6,000 in 2011 to more than 45,000 in 2021».^[130] An evidence-based approach is important for progress in science, policy, medical and other practices. For example, meta-analyses can quantify what is known and identify what is not yet known^[82] and place «truly innovative and highly interdisciplinary ideas» into the context of established knowledge which may enhance their impact.^[58] (see above)

Factors of success and progress[edit]

See also: § Growth or stagnation of science overall

It has been hypothesized that a deeper understanding of factors behind successful science could «enhance prospects of science as a whole to more effectively address societal problems».^[58]

Novel ideas and disruptive scholarship

Two metascientists reported that «structures fostering disruptive scholarship and focusing attention on novel ideas» could be important as in a growing scientific field citation flows disproportionately consolidate to already well-cited papers, possibly slowing and inhibiting canonical progress.^[131][132] A study concluded that to enhance impact of truly innovative and highly interdisciplinary novel ideas, they should be placed in the context of established knowledge.^[58]

Mentorship, partnerships and social factors

Other researchers reported that the most successful – in terms of «likelihood of prizewinning, National Academy of Science (NAS) induction, or superstardom» – protégés studied under mentors who published research for which they were conferred a prize after the protégés’ mentorship. Studying original topics rather than these mentors’ research-topics was also positively associated with success.^[133][134] Highly productive partnerships are also a topic of research – e.g. «super-ties» of frequent co-authorship of two individuals who can complement skills, likely also the result of other factors such as mutual trust, conviction, commitment and fun.^[135][58]

Study of successful scientists and processes, general skills and activities

The emergence or origin of ideas by successful scientists is also a topic of research, for example reviewing existing ideas on how Mendel made his discoveries,^[136] – or more generally, the process of discovery by scientists. Science is a «multifaceted process of appropriation, copying, extending, or combining ideas and inventions» [and other types of knowledge or information], and not an isolated process.^[58] There are also few studies investigating scientists’ habits, common modes of thinking, reading habits, use of information sources, digital literacy skills, and workflows.^{[137][138][139][140][141]}

Labor advantage

A study theorized that in many disciplines, larger scientific productivity or success by elite universities can be explained by their larger pool of available funded laborers.^{[142][143][further explanation needed]}

Ultimate impacts

Success (in science) is often measured in terms of metrics like citations, not in terms of the eventual or potential impact on lives and society, which awards (see above) sometimes do.^{[additional citation(s) needed]} Problems with such metrics are roughly outlined elsewhere in this article and include that reviews replace citations to primary studies.^[82] There are also proposals for changes to the academic incentives systems that increase the recognition of societal impact in the research process.^[144]

Progress studies

A proposed field of «Progress Studies» could investigate how scientists (or funders or evaluators of scientists) should be acting, «figuring out interventions» and study progress itself.^[145] The field was explicitly proposed in a 2019 essay and described as an applied science that prescribes action.^[146]

As and for acceleration of progress

A study suggests that improving the way science is done could accelerate the rate of scientific discovery and its applications which could be useful for finding urgent solutions to humanity’s problems, improve humanity’s conditions, and enhance understanding of nature. Metascientific studies can seek to identify aspects of science that need improvement, and develop ways to improve them.^[84] If science is accepted as the fundamental engine of economic growth and social progress, this could raise «the question of what we – as a society – can do to accelerate science, and to direct science toward solving society’s most important problems.»^[147] However, one of the authors clarified that a one-size-fits-all approach is not thought to be right answer – for example, in funding, DARPA models, curiosity-driven methods, allowing «a single reviewer to champion a project even if his or her peers do not agree», and various other approaches all have their uses. Nevertheless, evaluation of them can help build knowledge of what works or works best.^[114]

Reforms[edit]

Meta-research identifying flaws in scientific practice has inspired reforms in science. These reforms seek to address and fix problems in scientific practice which lead to low-quality or inefficient research.

A 2015 study lists «fragmented» efforts in meta-research.^[1]

Pre-registration[edit]

The practice of registering a scientific study before it is conducted is called pre-registration. It arose as a means to address the replication crisis. Pregistration requires the submission of a registered report, which is then accepted for publication or rejected by a journal based on theoretical justification, experimental design, and the proposed statistical analysis. Pre-registration of studies serves to prevent publication bias (e.g. not publishing negative results), reduce data dredging, and increase replicability.^[148][149]

Reporting standards[edit]

Studies showing poor consistency and quality of reporting have demonstrated the need for reporting standards and guidelines in science, which has led to the rise of organisations that produce such standards, such as CONSORT (Consolidated Standards of Reporting Trials) and the EQUATOR Network.

The EQUATOR (Enhancing the QUAlity and Transparency Of health Research)^[150] Network is an international initiative aimed at promoting transparent and accurate reporting of health research studies to enhance the value and reliability of medical research literature.^[151] The EQUATOR Network was established with the goals of raising awareness of the importance of good reporting of research, assisting in the development, dissemination and implementation of reporting guidelines for different types of study designs, monitoring the status of the quality of reporting of research studies in the health sciences literature, and conducting research relating to issues that impact the quality of reporting of health research studies.^[152] The Network acts as an «umbrella» organisation, bringing together developers of reporting guidelines, medical journal editors and peer reviewers, research funding bodies, and other key stakeholders with a mutual interest in improving the quality of research publications and research itself.

Applications[edit]

The areas of application of metascience include ICTs, medicine, psychology and physics.

ICTs[edit]

Metascience is used in the creation and improvement of technical systems (ICTs) and standards of science evaluation, incentivation, communication, commissioning, funding, regulation, production, management, use and publication. Such can be called «applied metascience»^{[153][better source needed]} and may seek to explore ways to increase quantity, quality and positive impact of research. One example for such is the development of alternative metrics.^[58]

Study screening and feedback

Various websites or tools also identify inappropriate studies and/or enable feedback such as PubPeer, Cochrane’s Risk of Bias Tool^[154] and RetractionWatch. Medical and academic disputes are as ancient as antiquity and a study calls for research into «constructive and obsessive criticism» and into policies to «help strengthen social media into a vibrant forum for discussion, and not merely an arena for gladiator matches».^[155] Feedback to studies can be found via altmetrics which is often integrated at the website of the study – most often as an embedded Altmetrics badge – but may often be incomplete, such as only showing social media discussions that link to the study directly but not those that link to news reports about the study. (see above)

Tools used, modified, extended or investigated

Tools may get developed with metaresearch or can be used or investigated by such. Notable examples may include:

• The tool scite.ai aims to track and link citations of papers as ‘Supporting’, ‘Mentioning’ or ‘Contrasting’ the study.^{[156][157][158]}
• The Scite Reference Check bot is an extension of scite.ai that scans new article PDFs «for references to retracted papers, and posts both the citing and retracted papers on Twitter» and also «flags when new studies cite older ones that have issued corrections, errata, withdrawals, or expressions of concern».^[158] Studies have suggested as few as 4% of citations to retracted papers clearly recognize the retraction.^[158]
• Search engines like Google Scholar are used to find studies and the notification service Google Alerts enables notifications for new studies matching specified search terms. Scholarly communication infrastructure includes search databases.^[159]
• Shadow library Sci-hub is a topic of metascience^[160]
• Personal knowledge management systems for research-, knowledge- and task management, such as saving information in organized ways^[161] with multi-document text editors for future use^[162][163] Such systems could be described as part of, along with e.g. Web browser (tabs-addons^[164] etc) and search software,^{[additional citation(s) needed]} «mind-machine partnerships» that could be investigated by metascience for how they could improve science.^[58]
• Scholia – efforts to open scholarly publication metadata and use it via Wikidata.^[165] (see above)
• Various software enables common metascientific practices such as bibliometric analysis.^[166]

Development

According to a study «a simple way to check how often studies have been repeated, and whether or not the original findings are confirmed» is needed due to reproducibility issues in science.^[167][168] A study suggests a tool for screening studies for early warning signs for research fraud.^[169]

Medicine[edit]

Clinical research in medicine is often of low quality, and many studies cannot be replicated.^[170][171] An estimated 85% of research funding is wasted.^[172] Additionally, the presence of bias affects research quality.^[173] The pharmaceutical industry exerts substantial influence on the design and execution of medical research. Conflicts of interest are common among authors of medical literature^[174] and among editors of medical journals. While almost all medical journals require their authors to disclose conflicts of interest, editors are not required to do so.^[175] Financial conflicts of interest have been linked to higher rates of positive study results. In antidepressant trials, pharmaceutical sponsorship is the best predictor of trial outcome.^[176]

Blinding is another focus of meta-research, as error caused by poor blinding is a source of experimental bias. Blinding is not well reported in medical literature, and widespread misunderstanding of the subject has resulted in poor implementation of blinding in clinical trials.^[177] Furthermore, failure of blinding is rarely measured or reported.^[178] Research showing the failure of blinding in antidepressant trials has led some scientists to argue that antidepressants are no better than placebo.^[179][180] In light of meta-research showing failures of blinding, CONSORT standards recommend that all clinical trials assess and report the quality of blinding.^[181]

Studies have shown that systematic reviews of existing research evidence are sub-optimally used in planning a new research or summarizing the results.^[182] Cumulative meta-analyses of studies evaluating the effectiveness of medical interventions have shown that many clinical trials could have been avoided if a systematic review of existing evidence was done prior to conducting a new trial.^{[183][184][185]} For example, Lau et al.^[183] analyzed 33 clinical trials (involving 36974 patients) evaluating the effectiveness of intravenous streptokinase for acute myocardial infarction. Their cumulative meta-analysis demonstrated that 25 of 33 trials could have been avoided if a systematic review was conducted prior to conducting a new trial. In other words, randomizing 34542 patients was potentially unnecessary. One study^[186] analyzed 1523 clinical trials included in 227 meta-analyses and concluded that «less than one quarter of relevant prior studies» were cited. They also confirmed earlier findings that most clinical trial reports do not present systematic review to justify the research or summarize the results.^[186]

Many treatments used in modern medicine have been proven to be ineffective, or even harmful. A 2007 study by John Ioannidis found that it took an average of ten years for the medical community to stop referencing popular practices after their efficacy was unequivocally disproven.^[187][188]

Psychology[edit]

Metascience has revealed significant problems in psychological research. The field suffers from high bias, low reproducibility, and widespread misuse of statistics.^{[189][190][191]} The replication crisis affects psychology more strongly than any other field; as many as two-thirds of highly publicized findings may be impossible to replicate.^[192] Meta-research finds that 80-95% of psychological studies support their initial hypotheses, which strongly implies the existence of publication bias.^[193]

The replication crisis has led to renewed efforts to re-test important findings.^[194][195] In response to concerns about publication bias and p-hacking, more than 140 psychology journals have adopted result-blind peer review, in which studies are pre-registered and published without regard for their outcome.^[196] An analysis of these reforms estimated that 61 percent of result-blind studies produce null results, in contrast with 5 to 20 percent in earlier research. This analysis shows that result-blind peer review substantially reduces publication bias.^[193]

Psychologists routinely confuse statistical significance with practical importance, enthusiastically reporting great certainty in unimportant facts.^[197] Some psychologists have responded with an increased use of effect size statistics, rather than sole reliance on the p values.^{[citation needed]}

Physics[edit]

Richard Feynman noted that estimates of physical constants were closer to published values than would be expected by chance. This was believed to be the result of confirmation bias: results that agreed with existing literature were more likely to be believed, and therefore published. Physicists now implement blinding to prevent this kind of bias.^[198]

Organizations and institutes[edit]

There are several organizations and universities across the globe which work on meta-research – these include the Meta-Research Innovation Center at Berlin,^[199] the Meta-Research Innovation Center at Stanford,^[200][201] the Meta-Research Center at Tilburg University, the Meta-research & Evidence Synthesis Unit, The George Institute for Global Health at India and Center for Open Science. Organizations that develop tools for metascience include Our Research, Center for Scientific Integrity and altmetrics companies. There is an annual Metascience Conference.^[202]

See also[edit]

References[edit]

Further reading[edit]

• Lydia Denworth, «A Significant Problem: Standard scientific methods are under fire. Will anything change?», Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67.
  • «The use of p values for nearly a century [since 1925] to determine statistical significance of experimental results has contributed to an illusion of certainty and [to] reproducibility crises in many scientific fields. There is growing determination to reform statistical analysis… Some [researchers] suggest changing statistical methods, whereas others would do away with a threshold for defining «significant» results.» (p. 63.)
• Harris, Richard (2017). Rigor Mortis: How Sloppy Science Creates Worthless Cures, Crushes Hopes, and Wastes Billions. Basic Books. ISBN 978-0465097913.
• Fortunato, Santo; Bergstrom, Carl T.; et al. (2 March 2018). «Science of science». Science. 359 (6379): eaao0185. doi:10.1126/science.aao0185. PMC 5949209. PMID 29496846.

External links[edit]

Journals

• Minerva: A Journal of Science, Learning and Policy
• Research Integrity and Peer Review
• Research Policy
• Science and Public Policy

Conferences

• Annual Metascience Conference

Всего найдено: 4

Как правильно: мета-анализ или метаанализ?

Ответ справочной службы русского языка

Верно слитное написание.

Добрый день!
Подскажите, в медицинском тексте слово «метаанализ» пишется с двумя «а» ?

Ответ справочной службы русского языка

Верное написание: метаанализ.

Как правильно: мета-анализ или метаанализ?
Спасибо.

Ответ справочной службы русского языка

Приставка _мета…_ пишется слитно. Правильно: _метаанализ_.

Какое значение имеет приставка мета-? В слове мета(?)анализ «мета» — приставка? Мета(?)анализ слитно или через дефис? Спасибо.

Ответ справочной службы русского языка

_Мета_ — приставка, пишется слитно: _метаанализ_.

Разбор частей речи

Морфологический разбор существительного

План морфологического разбора существительного

Морфологический разбор прилагательного

План морфологического разбора прилагательного

Морфологические признаки глагола

Морфологический разбор глагола

Морфологический разбор глагола пример

Метанаука (также известная как мета-исследование или исследование, основанное на фактах ) — это использование научной методологии для изучения самой науки . Metascience стремится повысить качество научных исследований при одновременном сокращении отходов. Он также известен как « исследование в области исследований » и « наука о науке », поскольку использует методы исследования для изучения того, как проводятся исследования и где можно улучшить. Метанаука занимается всеми областями исследований и была описана как «взгляд на науку с высоты птичьего полета». По словам Джона Иоаннидиса , «Наука — лучшее, что случилось с людьми … но мы можем делать это лучше».

В 1966 году в одном из первых метаисследований были рассмотрены статистические методы 295 статей, опубликованных в десяти известных медицинских журналах. Было обнаружено, что «почти 73% прочитанных отчетов … выводы были сделаны, когда обоснование этих выводов было недействительным». Мета-исследования в последующие десятилетия выявили множество методологических недостатков, неэффективности и неэффективной практики в исследованиях во многих научных областях. Многие научные исследования не могли быть воспроизведены , особенно в медицине и мягких науках . Термин « кризис репликации » был придуман в начале 2010-х годов как часть растущего осознания проблемы.

Были приняты меры для решения проблем, выявленных метанаукой. Эти меры включают предварительную регистрацию научных исследований и клинических испытаний, а также создание таких организаций, как CONSORT и EQUATOR Network, которые издают руководящие принципы по методологии и отчетности. Продолжаются усилия по сокращению злоупотребления статистикой , устранению порочных стимулов со стороны академических кругов, совершенствованию процесса экспертной оценки , борьбе с предвзятостью в научной литературе и повышению общего качества и эффективности научного процесса.

Часть серии по
Доказательная практика
Оценка Сохранение дизайн Стоматология Образование Законодательство Библиотечно-информационная практика Управление Медицинская этика Лекарство Уход Аптека в развивающихся странах Филантропия Политика Полицейская Обвинение Исследовательская работа Планирование Токсикология
v т е

История

В 1966 году в одном из первых метаисследований были рассмотрены статистические методы 295 статей, опубликованных в десяти известных медицинских журналах. Было обнаружено, что «почти 73% прочитанных отчетов … выводы были сделаны, когда обоснование этих выводов было недействительным». В 2005 году Джон Иоаннидис опубликовал статью под названием « Почему большинство опубликованных результатов исследований ложны », в которой утверждалось, что большинство статей в области медицины приводят к ошибочным выводам. Статья стала самой загружаемой в Публичной научной библиотеке и считается основополагающей в области метанауки. Более поздние мета-исследования выявили широко распространенные трудности с воспроизведением результатов во многих областях науки, включая психологию и медицину . Эта проблема получила название « кризис репликации ». Метанаука выросла как реакция на кризис репликации и озабоченность по поводу расточительства в исследованиях.

Многие известные издатели заинтересованы в метаисследованиях и повышении качества своих публикаций. Ведущие журналы, такие как Science , The Lancet и Nature , постоянно освещают метаисследования и проблемы с воспроизводимостью. В 2012 году PLOS ONE запустила Инициативу воспроизводимости. В 2015 году Biomed Central представил контрольный список минимальных стандартов отчетности для четырех заголовков.

Первой международной конференцией в широкой области метаисследований была конференция Research Waste / EQUATOR, проведенная в Эдинбурге в 2015 году; Первой международной конференцией по экспертной оценке стал Конгресс по экспертной оценке, проведенный в 1989 году. В 2016 году была запущена конференция « Целостность исследований и экспертная оценка» . Вступительная редакционная статья журнала призвала к «исследованию, которое расширит наше понимание и предложит потенциальные решения проблем, связанных с рецензированием, отчетами об исследованиях и этикой исследований и публикаций».

Области мета-исследований

Метанауку можно разделить на пять основных областей интересов: методы, отчетность, воспроизводимость, оценка и стимулы. Они соответствуют, соответственно, тому, как проводить, общаться, проверять, оценивать и вознаграждать исследования.

Методы

Метанаука стремится выявить неэффективные методы исследований, в том числе предвзятость в исследованиях, плохой дизайн исследований, злоупотребление статистикой , и найти методы уменьшения этих практик. Мета-исследования выявили многочисленные предубеждения в научной литературе. Особо следует отметить широко распространенное неправильное использование p-значений и злоупотребление статистической значимостью .

Составление отчетов

Мета-исследования выявили неэффективные методы отчетности, объяснения, распространения и популяризации исследований, особенно в области социальных наук и наук о здоровье. Плохая отчетность затрудняет точную интерпретацию результатов научных исследований, тиражирование исследований и выявление предубеждений и конфликтов интересов у авторов. Решения включают внедрение стандартов отчетности и большую прозрачность научных исследований (включая более строгие требования к раскрытию информации о конфликтах интересов). Предпринята попытка стандартизировать отчетность по данным и методологии путем создания руководящих принципов такими агентствами, как CONSORT и более крупной сетью EQUATOR .

Воспроизводимость

Кризис репликации — это продолжающийся методологический кризис, в ходе которого было обнаружено, что многие научные исследования трудно или невозможно воспроизвести . Хотя корни кризиса уходят в мета-исследования середины и конца 1900-х годов, фраза «кризис репликации» не использовалась до начала 2010-х годов как часть растущего осознания проблемы. Кризис репликации особенно затрагивает психологию (особенно социальную психологию ) и медицину . Репликация — важная часть научного процесса, и широко распространенные сбои репликации ставят под сомнение надежность затронутых полей.

Более того, тиражирование исследования (или невозможность его тиражирования) считается менее влиятельным, чем оригинальное исследование, и с меньшей вероятностью будет опубликовано во многих областях. Это мешает сообщать об исследованиях и даже пытаться их воспроизвести.

Оценка

Metascience стремится создать научную основу для экспертной оценки. Мета-исследование оценивает системы рецензирования, включая рецензирование до публикации, рецензирование после публикации и открытое рецензирование . Он также стремится разработать лучшие критерии финансирования исследований.

Поощрения

Метанаука стремится продвигать лучшие исследования с помощью более эффективных систем стимулирования. Это включает изучение точности, эффективности, затрат и преимуществ различных подходов к ранжированию и оценке исследований и тех, кто их выполняет. Критики утверждают, что извращенные стимулы создали в академических кругах среду « опубликовай или исчезни», которая способствует производству мусорной науки , низкокачественных исследований и ложных срабатываний . По словам Брайана Носека , «проблема, с которой мы сталкиваемся, заключается в том, что система стимулирования почти полностью ориентирована на публикацию исследований, а не на их правильное проведение». Сторонники реформы стремятся структурировать систему стимулов для достижения более качественных результатов.

Реформы

Мета-исследования по выявлению недостатков в научной практике вдохновили на реформы в науке. Эти реформы направлены на решение и устранение проблем в научной практике, которые приводят к некачественным или неэффективным исследованиям.

Предварительная регистрация

Практика регистрации научного исследования до его проведения называется предварительной регистрацией . Он возник как средство преодоления кризиса репликации . Предварительная регистрация требует подачи зарегистрированного отчета, который затем принимается к публикации или отклоняется журналом на основе теоретического обоснования, экспериментального плана и предлагаемого статистического анализа. Предварительная регистрация исследований служит для предотвращения предвзятости публикации , уменьшения углубления данных и повышения воспроизводимости.

Стандарты отчетности

Исследования, демонстрирующие низкую согласованность и качество отчетности, продемонстрировали необходимость в стандартах отчетности и руководящих принципах в науке, что привело к появлению организаций, разрабатывающих такие стандарты, таких как CONSORT (Consolidated Standards of Reporting Trials) и EQUATOR Network .

ЭКВАТОР ( E nhancing в ква Лити и T ransparency O F здоровья R сследование) Сеть является международной инициативой , направленной на содействие прозрачной и точную отчетности исследований в области здравоохранения исследований с целью повышения ценности и надежности медицинской исследовательской литературы. Сеть EQUATOR была создана с целью повышения осведомленности о важности качественной отчетности об исследованиях, оказания помощи в разработке, распространении и реализации руководящих принципов отчетности для различных типов дизайнов исследований, мониторинга состояния качества отчетности об исследованиях в литература по наукам о здоровье и проведение исследований, касающихся вопросов, влияющих на качество отчетности об исследованиях в области здравоохранения. Сеть действует как «зонтичная» организация, объединяющая разработчиков руководств по составлению отчетов, редакторов медицинских журналов и рецензентов, органы, финансирующие исследования, и другие ключевые заинтересованные стороны, имеющие взаимный интерес в повышении качества исследовательских публикаций и самих исследований.

Приложения

Лекарство

Клинические исследования в медицине часто бывают низкого качества, и многие исследования невозможно воспроизвести. По оценкам, 85% финансирования исследований тратится впустую. Кроме того, наличие предвзятости влияет на качество исследования. Фармацевтическая промышленность оказывает существенное влияние на разработку и выполнение медицинских исследований. Конфликты интересов распространены среди авторов медицинской литературы и среди редакторов медицинских журналов. Хотя почти все медицинские журналы требуют, чтобы их авторы раскрывали информацию о конфликте интересов, редакторы не обязаны этого делать. Финансовые конфликты интересов связаны с более высокими показателями положительных результатов исследований. В исследованиях антидепрессантов спонсорство фармацевтических препаратов является лучшим предиктором результатов исследования.

Ослепление — еще одно направление метаисследований, поскольку ошибка, вызванная плохим ослеплением, является источником экспериментальной ошибки . В медицинской литературе мало информации о слепоте, и широко распространенное неправильное понимание предмета привело к плохой реализации ослепления в клинических испытаниях . Кроме того, неэффективность ослепления редко измеряется или сообщается. Исследования, показывающие неэффективность ослепления в испытаниях антидепрессантов , заставили некоторых ученых утверждать, что антидепрессанты не лучше плацебо . В свете мета-исследований, показывающих неэффективность ослепления, стандарты CONSORT рекомендуют, чтобы все клинические испытания оценивали и сообщали о качестве ослепления.

Исследования показали, что систематические обзоры существующих научных данных неоптимально используются при планировании нового исследования или подведении итогов. Кумулятивный метаанализ исследований, оценивающих эффективность медицинских вмешательств, показал, что многих клинических испытаний можно было бы избежать, если бы до проведения нового исследования был проведен систематический обзор существующих доказательств. Например, Lau et al. проанализировали 33 клинических испытания (с участием 36974 пациентов) по оценке эффективности внутривенной стрептокиназы при остром инфаркте миокарда . Их совокупный мета-анализ показал, что 25 из 33 испытаний можно было бы избежать, если бы систематический обзор проводился до проведения нового испытания. Другими словами, в рандомизации 34542 пациентов не было необходимости. Одно исследование проанализировало 1523 клинических испытания, включенных в 227 метаанализов, и пришло к выводу, что было процитировано «менее четверти соответствующих предыдущих исследований». Они также подтвердили ранее сделанные выводы о том, что в большинстве отчетов о клинических испытаниях нет систематического обзора для обоснования исследования или обобщения результатов.

Доказано, что многие методы лечения, используемые в современной медицине, неэффективны или даже вредны. Исследование, проведенное Джоном Иоаннидисом в 2007 году, показало, что медицинскому сообществу потребовалось в среднем десять лет, чтобы перестать ссылаться на популярные практики после того, как их эффективность была однозначно опровергнута.

Психология

Метанаука выявила значительные проблемы в психологических исследованиях. Поле страдает от высокой систематической ошибки, низкой воспроизводимости и широко распространенного неправильного использования статистических данных . Кризис репликации влияет на психологию сильнее, чем на любую другую область; Две трети получивших широкую огласку результатов невозможно воспроизвести. Мета-исследования показывают, что 80-95% психологических исследований подтверждают их первоначальные гипотезы, что явно подразумевает наличие предвзятости публикации .

Кризис репликации привел к возобновлению усилий по повторной проверке важных результатов. В ответ на опасения по поводу предвзятости публикаций и р- хакерства более 140 психологических журналов приняли независимое рецензирование результатов , в котором исследования предварительно регистрируются и публикуются без учета их результатов. Анализ этих реформ показал, что 61 процент слепых исследований дает нулевые результаты по сравнению с 5–20 процентами в более ранних исследованиях. Этот анализ показывает, что экспертная оценка, не зависящая от результатов, существенно снижает предвзятость публикации.

Психологи обычно путают статистическую значимость с практической значимостью, с энтузиазмом сообщая о большой уверенности в неважных фактах. Некоторые психологи ответили более частым использованием статистических данных о величине эффекта , вместо того, чтобы полагаться исключительно на значения p .

Физика

Ричард Фейнман отметил, что оценки физических констант были ближе к опубликованным значениям, чем можно было бы ожидать случайно. Считалось, что это результат предвзятости подтверждения : результаты, согласующиеся с существующей литературой, с большей вероятностью поверили и, следовательно, опубликовали. Физики теперь применяют ослепление, чтобы предотвратить такую ​​предвзятость.

Связанные поля

Журналистика

Журналистика, также известная как наука о публикациях, представляет собой научное исследование всех аспектов академического издательского процесса. Эта область направлена ​​на повышение качества научных исследований путем внедрения научно обоснованных практик в академические публикации. Термин «journalology» был придуман Стивеном Замка , бывший редактор главный из в BMJ . Первый Конгресс экспертных оценок , состоявшийся в 1989 году в Чикаго , штат Иллинойс , считается поворотным моментом в становлении журналистики как отдельной области. Журналистика сыграла важную роль в продвижении предварительной регистрации исследований в науке, особенно в клинических исследованиях . В большинстве стран сейчас ожидается регистрация клинических испытаний .

Наукометрия

Наукометрия занимается измерением библиографических данных в научных публикациях. Основные исследовательские проблемы включают измерение влияния исследовательских работ и академических журналов, понимание научных цитат и использование таких измерений в контексте политики и управления.

Научная наука о данных

Научная наука о данных — это использование науки о данных для анализа исследовательских работ. Он включает как качественные, так и количественные методы. Исследования в области науки о данных включают обнаружение мошенничества и анализ сети цитирования .

Смотрите также

Ссылки

дальнейшее чтение

• Лидия Денуорт, «Серьезная проблема: стандартные научные методы подвергаются критике. Изменится ли что-нибудь?», Scientific American , vol. 321, нет. 4 (октябрь 2019 г.), стр. 62–67. «Использование р значений в течение почти столетия [после 1925] для определения статистической значимости из экспериментальных результатов способствовало иллюзии определенности и [к] воспроизводимости кризисам во многих областях науки . Существует растущая решимость реформ статистического анализ … Некоторые [исследователи] предлагают изменить статистические методы, в то время как другие отказались бы от порога для определения «значимых» результатов ». (стр.63)
• Харрис, Ричард (2017). Rigor Mortis: Как небрежная наука создает бесполезные лекарства, разрушает надежды и тратит впустую миллиарды . Основные книги. ISBN 9780465097913.

внешние ссылки

Журналы

• Минерва: журнал науки, обучения и политики
• Целостность исследования и экспертная оценка
• Политика исследования
• Наука и государственная политика

Конференции

• Симпозиум Metascience2019 в Стэнфорде

Мета-анализ (англ. meta-analysis) — в статистике это объединение результатов нескольких исследований для анализа набора связанных между собой научных гипотез.

В разных случаях для повторного статистического анализа отдельных исследований используют либо первичные данные оригинальных исследований либо обобщают опубликованные (вторичные) результаты исследований, посвященных одной проблеме.^[1] Мета-анализ является частым, но не обязательным компонентом систематического обзора (en:systematic review).

Термин «мета-анализ» был предложен американским статистиком Джином Глассом.^[2]

История

Первый мета-анализ был осуществлен Карлом Пирсоном в 1904 году, который пытался разрешить проблему низкой статистической мощности в исследованиях с небольшим размером выборки. Пирсон анализировал результаты нескольких исследований для того, чтобы получить более точные данные.^[3][4] Первый мета-анализ был проведен в 1940 году в издании Шестьдесят лет экстрасенсорного восприятия (англ. Extra-sensory perception after sixty years), в котором были объединены результаты идентичных экспериментов, выполненных независимыми исследователями. Авторы книги — психологи Университета Дьюка — Джозеф Пратт и Джозеф Райн с соавторами.^[5] Мета-анализ был выполнен на основе 145 статей об экстрасенсорном восприятии, опубликованных в период с 1882 по 1939 год и содержал оценку влияния неопубликованных данных. Хотя мета-анализ в настоящее время широко используется в эпидемиологии и доказательной медицине, подобных исследований в области медицины не проводили до 1955 году. В 1970-е годы более сложные аналитические методы были введены в исследования в области образования Д. В. Глассом, Ф. Л. Шмидтом, Дж. Е. Хантером.

Джин Гласс был первым современным статистиком, формализовавшим использование мета-анализа, и считается современным основателем этого метода. Первое использование термина согласно Oxford English Dictionary было совершено Глассом в 1976 году.^[2][6] Статистические теории, посвященные мета-анализу были значительно развиты в работах Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt.

Преимущества

Преимущества мета-анализа (над обзорами литературы и др.):

• указывает, что выборка более разнообразна, чем предполагалось исходя из разнообразия образцов
• обобщение нескольких исследований
• контроль разнообразия между исследованиями
• может объяснять разнообразие между данными
• увеличение статистической мощности
• работает в условиях избытка информации — каждый год публикуется большое количество статей
• обобщает несколько исследований и поэтому меньше зависит от отдельных находок, чем индивидуальные исследования
• может обнаруживать систематические ошибки

Этапы

1. Формулирование задачи
2. Изучение литературных данных
3. Отбор исследований (критерии включения)
   • Включение основано на качественных критериях, например, наличие рандомизации и слепого контроля в клинических исследованиях
   • Отбор отдельных исследований, (по объектам), например, лечение рака молочной железы
   • Включение или невключение неопубликованных данных
4. Решение о том, какие зависимые не включаются в мета-анализ
   • Различия (дискретные данные)
   • Средние (непрерывные данные)
5. Выбор модели (см далее)

Примечания

Литература

• Cornell, J. E. & Mulrow, C. D. (1999). Meta-analysis. In: H. J. Adèr & G. J. Mellenbergh (Eds). Research Methodology in the social, behavioral and life sciences (pp. 285—323). London: Sage.
• Norman, S.-L. T. (1999). Tutorial in Biostatistics. Meta-Analysis: Formulating, Evaluating, Combining, and Reporting. Statistics in Medicine, 18, 321—359.
• Sutton, A.J., Jones, D.R., Abrams, K.R., Sheldon, T.A., & Song, F. (2000). Methods for Meta-analysis in Medical Research. London: John Wiley. ISBN 0-471-49066-0

• Wilson, D. B., & Lipsey, M. W. (2001). Practical meta-analysis. Thousand Oaks: Sage publications. ISBN 0761921680
• Owen, A. B. (2009). «Karl Pearson’s meta-analysis revisited». Annals of Statistics, 37 (6B), 3867—3892. Supplementary report.
• Ellis, Paul D. (2010). The Essential Guide to Effect Sizes: An Introduction to Statistical Power, Meta-Analysis and the Interpretation of Research Results. United Kingdom: Cambridge University Press. ISBN 0521142466
• Bonett, D.G. (2009). Meta-analytic interval estimation for standardized and unstandardized mean differences, Psychological Methods, 14, 225—238.

Ссылки

• Пособие Cochrane для систематического анализа

Статистические показатели
Описательная статистика	Непрерывные данные Коэффициент сдвига Среднее (Арифметическое, Геометрическое, Гармоническое) · Медиана · Мода · Размах Вариация Ранг · Среднеквадратическое отклонение · Коэффициент вариации · Квантиль (Дециль, Процентиль/Перцентиль/Центиль) Моменты Математическое ожидание · Дисперсия · Асимметрия · Эксцесс Дискретные данные Частота · Таблица контингентности
Статистический вывод и проверка гипотез	Статистический вывод Доверительный интервал (Частотная вероятность) · Достоверный интервал (Байесовский вывод) · Статистическая значимость · Мета-анализ Планирование эксперимента Генеральная совокупность · Планирование выборки · Районированная выборка · Репликация · Группировка · Чувствительность и специфичность Объём выборки Статистическая мощность · Мера эффекта · Стандартная ошибка Общая оценка Байесовская оценка решения · Метод максимального правдоподобия · Метод моментов нахождения оценок · Оценка минимального расстояния · Оценка максимального интервала Статистические критерии Z-тест · t-критерий Стьюдента · Критерий Фишера · Критерий Пирсона (Хи-квадрат) · Критерий согласия Колмогорова · Тест Вальда · U-критерий Манна — Уитни · Критерий Уилкоксона · Критерий Краскела — Уоллиса · Критерий Кохрена · Критерий Лиллиефорса Анализ выживания Функция выживания · Оценка Каплана — Мейера · Логранк-тест · Интенсивность отказов · Пропорциональная модель опасностей
Корреляция	Коэффициент корреляции Пирсона · Ранг корреляций (Коэффициент Спирмана для ранга корреляций, Коэффициент тау Кендалла для ранга корреляций) · Переменная смешивания
Линейные модели	Основная линейная модель · Обобщённая линейная модель · Анализ вариаций · Ковариационный анализ
Регрессия	Линейная · Нелинейная · Непараметрическая регрессия · Полупараметрическая регрессия · Логистическая регрессия

Столбчатая диаграмма · Совмещённая диаграмма · Диаграмма управления · Лесная диаграмма · Гистограмма · Q-Q диаграмма · Диаграмма выполнения · Диаграмма разброса · Стебель-листья · Ящик с усами

Использование научной методологии для изучения самой науки

Метанаука (также известная как мета-исследование или научно-обоснованное исследование ) — это использование научной методологии для изучения самой науки. Metascience стремится повысить качество научных исследований при одновременном сокращении отходов. Он также известен как «исследование в области исследований» и «наука о науке», так как использует методы исследования для изучения того, как исследования проводятся и где можно улучшить. Метанаука занимается всеми областями исследований и была описана как «взгляд на науку с высоты птичьего полета». По словам Джона Иоаннидиса, «Наука — лучшее, что случилось с людьми… но мы можем делать это лучше».

В 1966 году было проведено раннее метаисследование В статье исследованы статистические методы 295 статей, опубликованных в десяти известных медицинских журналах. Было обнаружено, что «почти 73% прочитанных отчетов… выводы были сделаны, когда обоснование этих выводов было недействительным». Мета-исследования в последующие десятилетия выявили множество методологических недостатков, неэффективности и неэффективной практики в исследованиях во многих научных областях. Многие научные исследования не могли быть воспроизведены, особенно в медицине и мягких науках. Термин «кризис репликации » был придуман в начале 2010-х годов как часть растущего осознания проблемы.

Были приняты меры для решения проблем, выявленных метанаукой. Эти меры включают предварительную регистрацию научных исследований и клинических испытаний, а также создание таких организаций, как CONSORT и EQUATOR Network которые издают руководящие принципы по методологии и отчетности. Продолжаются усилия по сокращению злоупотребления статистикой, устранению порочных стимулов со стороны академических кругов, совершенствованию процесса экспертной оценки, борьбе с предвзятостью в научной литературе, а также для повышения общего качества и эффективности научного процесса.

Содержание

• 1 История
• 2 Области метаисследований
  • 2.1 Методы
  • 2.2 Отчетность
  • 2.3 Воспроизводимость
  • 2.4 Оценка
  • 2.5 Стимулы
• 3 Реформы
  • 3.1 Предварительная регистрация
  • 3.2 Стандарты отчетности
• 4 Приложения
  • 4.1 Медицина
  • 4.2 Психология
  • 4.3 Физика
• 5 Связанные области
  • 5.1 Журналистика
  • 5.2 Наукометрия
  • 5.3 Научная наука о данных
• 6 См. Также
• 7 Ссылки
• 8 Дополнительная литература
• 9 Внешние ссылки

История

Джон Иоаннидис (2005), «Почему большинство публикаций Результаты исследований ложны «.

В 1966 году в одном из первых метаисследований были рассмотрены статистические методы 295 статей, опубликованных в десяти известных медицинских журналах. Было обнаружено, что «почти в 73% отчетов прочтите… выводы были сделаны, когда обоснование этих выводов было недействительным «. В 2005 году Джон Иоаннидис опубликовал статью под названием» Почему большинство опубликованных результатов исследований ложны «, в которой утверждалось что большинство документов в Медицинская сфера дает неверные выводы. Статья стала самой загружаемой в Публичной научной библиотеке и считается основополагающей в области метанауки. Более поздние мета-исследования выявили широко распространенные трудности в воспроизведении результатов во многих областях науки, включая психологию и медицину. Эта проблема была названа «кризис репликации ». Метанаука выросла как реакция на кризис репликации и озабоченность по поводу расточительства в исследованиях.

Многие известные издатели заинтересованы в метаисследованиях и повышении качества своих публикаций. Ведущие журналы, такие как Science, The Lancet и Nature, постоянно освещают мета-исследования и проблемы с воспроизводимостью. В 2012 году PLOS ONE запустила Инициативу воспроизводимости. В 2015 году Biomed Central ввел контрольный список минимальных стандартов отчетности для четырех заголовков.

Первой международной конференцией в широкой области метаисследований была конференция Research Waste / EQUATOR, проведенная в Эдинбурге в 2015 году; первая международная конференция по экспертной оценке была проведена в 1989 году. В 2016 году была запущена программа Research Integrity and Peer Review. Вступительная редакционная статья журнала призвала к «исследованию, которое расширит наше понимание и предложит возможные решения проблем, связанных с рецензированием, составлением отчетов об исследованиях, а также этикой исследований и публикаций».

Области мета-исследований

Метанауку можно разделить на пять основных областей интересов: методы, отчетность, воспроизводимость, оценка и стимулы. Они соотносятся, соответственно, с тем, как проводить, сообщать, проверять, оценивать и вознаграждать исследования.

Методы

Метанаука стремится выявить неэффективные методы исследования, включая предубеждения в исследования, плохой дизайн исследования, злоупотребление статистикой, и поиск методов, позволяющих сократить эту практику. Мета-исследования выявили многочисленные предубеждения в научной литературе. Особо следует отметить широко распространенное неправильное использование p-значений и злоупотребление статистической значимостью.

Отчетность

Мета-исследования выявили неэффективные методы отчетности, объяснения, распространения и популяризации исследования, особенно в области социальных и медицинских наук. Плохая отчетность затрудняет точную интерпретацию результатов научных исследований, тиражирование исследований и выявление предубеждений и конфликтов интересов у авторов. Решения включают внедрение стандартов отчетности и большую прозрачность научных исследований (включая более строгие требования к раскрытию информации о конфликтах интересов). Предпринята попытка стандартизировать представление данных и методологию путем создания руководящих принципов такими агентствами, как CONSORT и более крупными EQUATOR Network.

Воспроизводимость

Кризис репликации продолжающийся методологический кризис, в ходе которого было обнаружено, что многие научные исследования трудно или невозможно воспроизвести. Хотя корни кризиса лежат в метаисследованиях середины и конца 1900-х годов, фраза «кризис репликации» не появлялась до начала 2010-х годов как часть растущего осознания проблемы. Кризис репликации особенно затрагивает психологию (особенно социальную психологию ) и медицину. Репликация является неотъемлемой частью научного процесса, и широко распространенный отказ репликации ставит под сомнение надежность затронутых полей.

Более того, репликация исследования (или отказ от репликации) считается менее влиятельной, чем исходное исследование, и менее вероятно, что он будет опубликован во многих областях. Это препятствует публикации и даже попыткам воспроизвести исследования.

Оценка

Метанаука стремится создать научную основу для экспертной оценки. Мета-исследование оценивает системы рецензирования, включая рецензирование до публикации, рецензирование после публикации и открытое рецензирование. Он также стремится разработать более совершенные критерии финансирования исследований.

Стимулы

Метанаука стремится продвигать лучшие исследования с помощью более совершенных систем стимулирования. Это включает изучение точности, эффективности, затрат и преимуществ различных подходов к ранжированию и оценке исследований и тех, кто их выполняет. Критики утверждают, что извращенные стимулы создали среду «опубликовай или исчезни» в академических кругах, которая способствует производству мусорной науки, низкокачественных исследований и ложные срабатывания. По словам Брайана Носека : «Проблема, с которой мы сталкиваемся, заключается в том, что система стимулирования почти полностью ориентирована на публикацию исследований, а не на их правильность». Сторонники реформы стремятся структурировать систему стимулов, чтобы способствовать более качественным результатам.

Реформы

Мета-исследования, выявляющие недостатки в научной практике, вдохновили на реформы в науке. Эти реформы направлены на решение и устранение проблем в научной практике, которые приводят к некачественным или неэффективным исследованиям.

Предварительная регистрация

Практика регистрации научного исследования до его проведения называется предварительной регистрацией. Он возник как средство решения проблемы кризиса репликации. Предварительная регистрация требует подачи зарегистрированного отчета, который затем принимается к публикации или отклоняется журналом на основе теоретического обоснования, экспериментального плана и предлагаемого статистического анализа. Предварительная регистрация исследований служит для предотвращения предвзятости публикации, уменьшения извлечения данных и повышения воспроизводимости.

Стандарты отчетности

Исследования, показывающие низкую согласованность и Качество отчетности продемонстрировало потребность в стандартах отчетности и руководящих принципах в науке, что привело к появлению организаций, которые разрабатывают такие стандарты, такие как CONSORT (Консолидированные стандарты отчетности по испытаниям) и EQUATOR Сеть.

EQUATOR (E n Повышение качества QUA и T прозрачности O для здоровья R esearch) Network — это международная инициатива, направленная на продвижение прозрачной и точной отчетности об исследованиях в области здравоохранения для повышения ценности и надежности медицинской литературы. Сеть EQUATOR была создана с целью повышения осведомленности о важности качественной отчетности об исследованиях, оказания помощи в разработке, распространении и реализации руководящих принципов отчетности для различных типов дизайнов исследований, мониторинга состояния качества отчетности об исследованиях в литературу по наукам о здоровье и проведение исследований, касающихся вопросов, влияющих на качество отчетности об исследованиях в области здравоохранения. Сеть действует как «зонтичная» организация, объединяющая разработчиков руководств по составлению отчетов, редакторов медицинских журналов и рецензентов, органы, финансирующие исследования, и другие ключевые заинтересованные стороны, имеющие взаимный интерес в улучшении качества исследовательских публикаций и самих исследований.

Приложения

Медицина

Клинические исследования в медицине часто бывают низкого качества, и многие исследования невозможно воспроизвести. По оценкам, 85% финансирования исследований тратится впустую. Кроме того, наличие предвзятости влияет на качество исследования. Фармацевтическая промышленность оказывает существенное влияние на разработку и проведение медицинских исследований. Конфликты интересов распространены среди авторов медицинской литературы и среди редакторов медицинских журналов. Хотя почти все медицинские журналы требуют, чтобы их авторы раскрывали информацию о конфликте интересов, редакторы не обязаны этого делать. Финансовые конфликты интересов были связаны с более высокими показателями положительных результатов исследований. В испытаниях антидепрессантов спонсорство фармацевтических препаратов является лучшим предиктором результатов испытаний.

Ослепление — еще один объект мета-исследований, поскольку ошибка, вызванная плохим ослеплением, является источником экспериментальной ошибки. В медицинской литературе мало информации о слепоте, и широко распространенное неправильное понимание предмета привело к плохой реализации ослепления в клинических испытаниях. Кроме того, неэффективность ослепления редко измеряется или сообщается. Исследования, показывающие неэффективность ослепления в исследованиях антидепрессантов, привели некоторых ученых к утверждению, что антидепрессанты не лучше плацебо. В свете мета-исследований, показывающих неэффективность ослепления, стандарты CONSORT рекомендуют, чтобы во всех клинических испытаниях оценивалось качество ослепления и сообщалось о нем.

Исследования показали, что систематические обзоры существующих научных доказательств являются недостаточными. -Оптимально используется при планировании нового исследования или подведении итогов. Кумулятивный метаанализ исследований, оценивающих эффективность медицинских вмешательств, показал, что многих клинических испытаний можно было бы избежать, если бы до проведения нового исследования был проведен систематический обзор имеющихся данных. Например, Lau et al. проанализировали 33 клинических испытания (с участием 36974 пациентов) по оценке эффективности внутривенного введения стрептокиназы при остром инфаркте миокарда. Их совокупный мета-анализ показал, что 25 из 33 испытаний можно было бы избежать, если бы систематический обзор проводился до проведения нового испытания. Другими словами, в рандомизации 34542 пациентов не было необходимости. Одно исследование проанализировало 1523 клинических испытания, включенных в 227 метаанализов, и пришло к выводу, что было процитировано «менее четверти соответствующих предыдущих исследований». Они также подтвердили ранее сделанные выводы о том, что в большинстве отчетов о клинических испытаниях нет систематических обзоров для обоснования исследований или обобщения результатов.

Многие методы лечения, используемые в современной медицине, оказались неэффективными или даже вредными. Исследование 2007 года, проведенное Джоном Иоаннидисом, показало, что медицинскому сообществу потребовалось в среднем десять лет, чтобы перестать ссылаться на популярные практики после того, как их эффективность была однозначно опровергнута.

Психология

Метанаука выявила значительные проблемы в психологическое исследование. Поле страдает от высокой систематической ошибки, низкой воспроизводимости и широко распространенного неправильного использования статистики. Кризис репликации влияет на психологию сильнее, чем на любую другую область; Две трети получивших широкую огласку результатов невозможно воспроизвести. Мета-исследования показывают, что 80-95% психологических исследований подтверждают их первоначальные гипотезы, что настоятельно подразумевает наличие предвзятости публикации.

Кризис репликации привел к возобновлению усилий по повторной проверке важных результатов. В ответ на опасения по поводу предвзятости публикаций и р-хакинга более 140 психологических журналов приняли экспертную оценку без учета результатов, в которой исследования предварительно зарегистрированные и опубликованные без учета их результатов. Анализ этих реформ показал, что 61 процент слепых исследований дает нулевые результаты, по сравнению с 5–20 процентами в более ранних исследованиях. Этот анализ показывает, что рецензирование, слепое к результатам, существенно снижает предвзятость публикации.

Психологи обычно путают статистическую значимость с практической важностью, с энтузиазмом сообщая о большой уверенности в неважных фактах. Некоторые психологи ответили более частым использованием статистики размера эффекта, вместо того, чтобы полагаться исключительно на значения p.

Physics

Ричард Фейнман отметил, что оценки физического константы были ближе к опубликованным значениям, чем можно было ожидать случайно. Считалось, что это результат систематической ошибки подтверждения : результаты, согласующиеся с существующей литературой, с большей вероятностью поверили и, следовательно, опубликовали. Теперь физики применяют ослепление для предотвращения такого рода предвзятости.

Связанные области

Журналистика

Журналистика, также известная как публикационная наука, — это научное исследование всех аспектов академический издательский процесс. Эта область направлена ​​на повышение качества научных исследований путем внедрения научно-обоснованных практик в академические публикации. Термин «журналистика» был придуман Стивеном Локком, бывшим главным редактором журнала BMJ. Первое, проведенное в 1989 г. в Чикаго, Иллинойс, считается поворотным моментом в становлении журналистики как отдельной области. Журналистика сыграла важную роль в продвижении исследования предварительной регистрации в науке, особенно в клинических испытаниях. Регистрация клинических испытаний теперь ожидается в большинстве стран.

Наукометрия

Наукометрия занимается измерением библиографических данных в научных публикациях. Основные исследовательские проблемы включают измерение влияния научных статей и академических журналов, понимание научных цитат и использование таких показателей в контексте политики и управления.

Научные данные

Научные наука о данных — это использование науки о данных для анализа исследовательских работ. Он включает как качественные, так и количественные методы. Исследования в области науки о данных включают обнаружение мошенничества и анализ сети цитирования.

См. Также

• Эпистемология
• Практика, основанная на фактах
• Основанная на фактах медицина
• Политика, основанная на фактах
• Необходимы дальнейшие исследования
• HARKing
• Список исследовательских центров метанауки
• Логология (наука)
• Метатеория
• Открытая наука
• Политика в области науки и науки
• Социология научного знания
• Самоорганизованное распределение финансирования

Ссылки

Дополнительная литература

• Лидия Денворт, «Существенная проблема: стандартные научные методы подвергаются критике. Что-нибудь изменится?», Scientific American, т. 321, нет. 4 (октябрь 2019 г.), стр. 62–67. «Использование значений p в течение почти столетия [с 1925 года] для определения статистической значимости экспериментальных результатов способствовало созданию иллюзии достоверности и [to] кризис воспроизводимости во многих научных областях. Растет решимость реформировать статистический анализ… Некоторые [исследователи] предлагают изменить статистические методы, в то время как другие отказались бы с порогом для определения «значимых» результатов ». (стр. 63.)
• Харрис, Ричард (2017). Rigor Mortis: Как небрежная наука создает бесполезные лекарства, разрушает надежды и растрачивает миллиарды. Основные книги. ISBN 9780465097913.

Внешние ссылки

Журналы

• Minerva: журнал науки, обучения и политики
• Целостность исследований и экспертная оценка
• Политика исследований
• Наука и публичная политика

Конференции

• Симпозиум Metascience2019 в Стэнфорде