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.
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
An exemplary visualization of a conception of scientific knowledge generation structured by layers, with the "Institution of Science" being the subject of metascience.
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.[15]
Methods
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.[15] Meta-research has identified numerous biases in scientific literature.[16] Of particular note is the widespread misuse of p-values and abuse of statistical significance.[17]
The field of causality has evolved in an attempt to understand reality in terms of data-generating models as opposed to the distribution of observed variables. This is pertinent in the field of machine learning where trustworthy AI systems capable of explaining the logic involved in its predictions are becoming of focus, especially in applications where highly-sensitive data is involved such as finance. The term black box is commonly used in this field to describe models which lack interpretability of their internal structure. Causal discovery and causal inference both provide axiom-based frameworks to deal with such problems, with the former involved in identifying the causal structure inherent in a dataset, while the latter aims to estimate the causal effect of a specific variable (treatment) over a certain outcome of interest. Causality is also becoming common knowledge in the empirical research such as the social sciences, where causal conclusions are often drawn from observational data without conclusive justification.
Journalology, also known as publication science, is the scholarly study of all aspects of the academic publishing process.[18][19] The field seeks to improve the quality of scholarly research by implementing evidence-based practices in academic publishing.[20] 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.[20] 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.[20]
Reporting
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.[15]
Barriers to conducting replications of experiment in cancer research, The Reproducibility Project: Cancer Biology
The replication crisis is an ongoing methodological crisis in which it has been found that many scientific studies are difficult or impossible to replicate.[21][22] 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[23] as part of a growing awareness of the problem.[15] The replication crisis particularly affects psychology (especially social psychology) and medicine,[24][25] including cancer research.[26][27] Replication is an essential part of the scientific process, and the widespread failure of replication puts into question the reliability of affected fields.[28]
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.[29][30]
Evaluation and incentives
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.[15]
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.[15] 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.[31][32] 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."[33] Proponents of reform seek to structure the incentive system to favor higher-quality results.[34]
Studies proposed machine-readable standards 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.[35][36][37] 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".[38]
Factors other than a submission's merits can substantially influence peer reviewers' evaluations.[39] 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 altmetric even when such can be used as partial indicators of such ends.[40][41]
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.[42] 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.[38]
Science funding and science governance can also be explored by metascience.[43]
Incentives
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.[44][45] 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[46] 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.
Cluster network of scientific publications in relation to Nobel prizes.
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%]).[47][48]
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.[43]
Measurements show that allocation of bio-medical resources can be more strongly correlated to previous allocations and research than to burden of diseases.[49]
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".[39]
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".[50] 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.[51][52][53][54] 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".[55] Science communication may also involve the communication of societal needs, concerns and requests to scientists.
Alternative metrics tools can be used not only for help in assessment 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.[56]
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".[49]
ArXiv's yearly submission rate growth over 30 years.
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.[50][59][60][61]
Science overall and intrafield developments
A visualization of scientific outputs by field in OpenAlex. A study can be part of multiple fields and lower numbers of papers is not necessarily detrimental for fields.
Number of PubMed search results for "coronavirus" by year from 1949 to 2020.
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.[62][63][64] 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.[65]
Challenges of interpretation of pooled results
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.
Knowledge integration and living documents
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".[65]
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".[66]
A meta-analysis of several small studies does not always predict the results of a single large study.[67] Some have argued that a weakness of the method is that sources of bias are not controlled by the method: a good meta-analysis cannot correct for poor design or bias in the original studies.[68] This would mean that only methodologically sound studies should be included in a meta-analysis, a practice called 'best evidence synthesis'.[68] Other meta-analysts would include weaker studies, and add a study-level predictor variable that reflects the methodological quality of the studies to examine the effect of study quality on the effect size.[69] However, others have argued that a better approach is to preserve information about the variance in the study sample, casting as wide a net as possible, and that methodological selection criteria introduce unwanted subjectivity, defeating the purpose of the approach.[70]
Various issues with included or available studies such as, for example, heterogeneity of methods used may lead to faulty conclusions of the meta-analysis.[71]
Factors of success and progress
Two metascientists reported that "structures fostering disruptive scholarship and focusing attention on novel ideas" could be important as in a growing scientific fieldcitation flows disproportionately consolidate to already well-cited papers, possibly slowing and inhibiting canonical progress.[72][73] A study found to enhance impact of truly innovative and highly interdisciplinary novel ideas, they should be placed in the context of established knowledge.[49]
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.[74][75]
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".[49]
Reforms
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.
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.[76][77]
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)[78] 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.[79] 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.[80] 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
The areas of application of metascience include ICTs, medicine, psychology and physics.
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"[81][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.[49] 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.[82][83] The tool scite.ai aims to track and link citations of papers as 'Supporting', 'Mentioning' or 'Contrasting' the study.[84]
Clinical research in medicine is often of low quality, and many studies cannot be replicated.[85][86] An estimated 85% of research funding is wasted.[87] Additionally, the presence of bias affects research quality.[88] The pharmaceutical industry exerts substantial influence on the design and execution of medical research. Conflicts of interest are common among authors of medical literature[89] 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.[90] 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.[91]
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.[92] Furthermore, failure of blinding is rarely measured or reported.[93] Research showing the failure of blinding in antidepressant trials has led some scientists to argue that antidepressants are no better than placebo.[94][95] In light of meta-research showing failures of blinding, CONSORT standards recommend that all clinical trials assess and report the quality of blinding.[96]
Studies have shown that systematic reviews of existing research evidence are sub-optimally used in planning a new research or summarizing the results.[97] 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.[98][99][100] For example, Lau et al.[98] 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[101] 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.[101]
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.[102][103]
Metascience has revealed significant problems in psychological research. The field suffers from high bias, low reproducibility, and widespread misuse of statistics.[104][105][106] 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.[107] Meta-research finds that 80-95% of psychological studies support their initial hypotheses, which strongly implies the existence of publication bias.[108]
The replication crisis has led to renewed efforts to re-test important findings.[109][110] 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.[111] 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.[108]
Psychologists routinely confuse statistical significance with practical importance, enthusiastically reporting great certainty in unimportant facts.[112] Some psychologists have responded with an increased use of effect size statistics, rather than sole reliance on the p values.[citation needed]
Physics
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.[113]
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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.)
![John Ioannidis (2005), "Why Most Published Research Findings Are False"[5]](http://upload.wikimedia.org/wikipedia/commons/thumb/8/8e/Ioannidis_%282005%29_Why_Most_Published_Research_Findings_Are_False.pdf/page1-440px-Ioannidis_%282005%29_Why_Most_Published_Research_Findings_Are_False.pdf.jpg)
