Literature DB >> 26168125

Why Science Is Not Necessarily Self-Correcting.

John P A Ioannidis1.   

Abstract

The ability to self-correct is considered a hallmark of science. However, self-correction does not always happen to scientific evidence by default. The trajectory of scientific credibility can fluctuate over time, both for defined scientific fields and for science at-large. History suggests that major catastrophes in scientific credibility are unfortunately possible and the argument that "it is obvious that progress is made" is weak. Careful evaluation of the current status of credibility of various scientific fields is important in order to understand any credibility deficits and how one could obtain and establish more trustworthy results. Efficient and unbiased replication mechanisms are essential for maintaining high levels of scientific credibility. Depending on the types of results obtained in the discovery and replication phases, there are different paradigms of research: optimal, self-correcting, false nonreplication, and perpetuated fallacy. In the absence of replication efforts, one is left with unconfirmed (genuine) discoveries and unchallenged fallacies. In several fields of investigation, including many areas of psychological science, perpetuated and unchallenged fallacies may comprise the majority of the circulating evidence. I catalogue a number of impediments to self-correction that have been empirically studied in psychological science. Finally, I discuss some proposed solutions to promote sound replication practices enhancing the credibility of scientific results as well as some potential disadvantages of each of them. Any deviation from the principle that seeking the truth has priority over any other goals may be seriously damaging to the self-correcting functions of science.
© The Author(s) 2012.

Entities:  

Keywords:  replication; self-correction

Year:  2012        PMID: 26168125     DOI: 10.1177/1745691612464056

Source DB:  PubMed          Journal:  Perspect Psychol Sci        ISSN: 1745-6916


  77 in total

1.  Optimization of cellular ELISA for assay of surface antigens on human synoviocytes.

Authors:  D D Smith; C B Cohick; H B Lindsley
Journal:  Biotechniques       Date:  1997-05       Impact factor: 1.993

2.  Standards of Evidence for Efficacy, Effectiveness, and Scale-up Research in Prevention Science: Next Generation.

Authors:  Denise C Gottfredson; Thomas D Cook; Frances E M Gardner; Deborah Gorman-Smith; George W Howe; Irwin N Sandler; Kathryn M Zafft
Journal:  Prev Sci       Date:  2015-10

3.  Competition for priority harms the reliability of science, but reforms can help.

Authors:  Leonid Tiokhin; Minhua Yan; Thomas J H Morgan
Journal:  Nat Hum Behav       Date:  2021-01-28

4.  Fortifying the Corrective Nature of Post-publication Peer Review: Identifying Weaknesses, Use of Journal Clubs, and Rewarding Conscientious Behavior.

Authors:  Jaime A Teixeira da Silva; Aceil Al-Khatib; Judit Dobránszki
Journal:  Sci Eng Ethics       Date:  2016-12-01       Impact factor: 3.525

5.  Using the Coefficient of Confidence to Make the Philosophical Switch From A Posteriori to A Priori Inferential Statistics.

Authors:  David Trafimow
Journal:  Educ Psychol Meas       Date:  2016-10-06       Impact factor: 2.821

6.  Grounds for Ambiguity: Justifiable Bases for Engaging in Questionable Research Practices.

Authors:  Donald F Sacco; Mitch Brown; Samuel V Bruton
Journal:  Sci Eng Ethics       Date:  2018-09-26       Impact factor: 3.525

7.  How to Tell the Truth with Statistics: The Case for Accountable Data Analyses in Team-based Science.

Authors:  Jonathan A L Gelfond; Craig M Klugman; Leah J Welty; Elizabeth Heitman; Christopher Louden; Brad H Pollock
Journal:  J Transl Med Epidemiol       Date:  2014

Review 8.  The academic, economic and societal impacts of Open Access: an evidence-based review.

Authors:  Jonathan P Tennant; François Waldner; Damien C Jacques; Paola Masuzzo; Lauren B Collister; Chris H J Hartgerink
Journal:  F1000Res       Date:  2016-04-11

Review 9.  Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning.

Authors:  Tal Yarkoni; Jacob Westfall
Journal:  Perspect Psychol Sci       Date:  2017-08-25

10.  Training behavioural therapists in presession pairing skills to evaluate the impact on children's life skill acquisition rates.

Authors:  Laura Gormley; Heidi Penrose; Maeve Bracken; Brittany Barron
Journal:  Int J Dev Disabil       Date:  2020-10-27
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