List of References

A free and open platform for sharing MRI, MEG, EEG, iEEG, ECoG, ASL, and PET data—OpenNeuro. (n.d.). OpenNeuro. Retrieved 9 July 2021, from https://openneuro.org/

Abele-Brehm, A. E., Gollwitzer, M., Steinberg, U., & Schönbrodt, F. D. (2019). Attitudes Toward Open Science and Public Data Sharing: A Survey Among Members of the German Psychological Society. Social Psychology, 50(4), 252–260. https://doi.org/10.1027/1864-9335/a000384

Aczel, B., Szaszi, B., Nilsonne, G., Van den Akker, O., Albers, C. J., van Assen, M. A. L. M., Bastiaansen, J. A., Benjamin, D. J., Boehm, U., Botvinik-Nezer, R., Bringmann, L. F., Busch, N., Caruyer, E., Cataldo, A. M., Cowan, N., Delios, A., van Dongen, N. N. N., Donkin, C., van Doorn, J., … Wagenmakers, E.-J. (2021). Guidance for conducting and reporting multi-analyst studies [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/5ecnh

Aczel, B., Szaszi, B., Sarafoglou, A., Kekecs, Z., Kucharský, Š., Benjamin, D., Chambers, C. D., Fisher, A., Gelman, A., Gernsbacher, M. A., Ioannidis, J. P., Johnson, E., Jonas, K., Kousta, S., Lilienfeld, S. O., Lindsay, D. S., Morey, C. C., Munafò, M., Newell, B. R., … Wagenmakers, E.-J. (2020). A consensus-based transparency checklist. Nature Human Behaviour, 4(1), 4–6. https://doi.org/10.1038/s41562-019-0772-6

Albayrak-Aydemir, N. (2018a, April 16). Diversity helps but decolonisation is the key to equality in higher education. Contemporary Issues in Teaching and Learning. https://lsepgcertcitl.wordpress.com/2018/04/16/diversity-helps-but-decolonisation-is-the-key-to-equality-in-higher-education/

Albayrak-Aydemir, N. (2018b, November 29). Academics’ role on the future of higher education: Important but unrecognised. Contemporary Issues in Teaching and Learning. https://lsepgcertcitl.wordpress.com/2018/11/29/academics-role-on-the-future-of-higher-education-important-but-unrecognised/

Albayrak-Aydemir, N. (2020, February 20). ‘The hidden costs of being a scholar from the Global South’ is locked The hidden costs of being a scholar from the Global South. LSE Higher Education. https://blogs.lse.ac.uk/highereducation/2020/02/20/the-hidden-costs-of-being-a-scholar-from-the-global-south/

Albayrak-Aydemir, N., & Okoroji, C. (n.d.). Facing the challenges of postgraduate study as a minority student (A Guide for Psychology Postgraduates: Surviving Postgraduate Study, pp. 63–66). The British Psychological Society.

Ali, M. J. (2021). Understanding the Altmetrics. Seminars in Ophthalmology, 1–3. https://doi.org/10.1080/08820538.2021.1930806

ALLEA - All European Academies. (2017). The European Code of Conduct for Research Integrity (Revised Edition). ALLEA. https://allea.org/code-of-conduct/

American Psychological Association,Task Force on Socioeconomic Status. (2007). Report of the APA task force on Socioeconomic status. American Psychological Association.

Anderson, A. A., Scheufele, D. A., Brossard, D., & Corley, E. A. (2012). The Role of Media and Deference to Scientific Authority in Cultivating Trust in Sources of Information about Emerging Technologies. International Journal of Public Opinion Research, 24(2), 225–237. https://doi.org/10.1093/ijpor/edr032

Angrist, J. D., & Pischke, J.-S. (2010). The Credibility Revolution in Empirical Economics: How Better Research Design is Taking the Con out of Econometrics. Journal of Economic Perspectives, 24(2), 3–30. https://doi.org/10.1257/jep.24.2.3

Arslan, R. C. (2019). How to Automatically Document Data With the codebook Package to Facilitate Data Reuse. Advances in Methods and Practices in Psychological Science, 2(2), 169–187. https://doi.org/10.1177/2515245919838783

Australian Reproducibility Network. (n.d.). Australian Reproducibility Network. Retrieved 10 July 2021, from http://www.aus-rn.org/

Authorship & contributorship | The BMJ. (n.d.). The British Medical Journal. https://www.bmj.com/about-bmj/resources-authors/article-submission/authorship-contributorship

Azevedo, F. (n.d.). Ideology May Help Explain Anti-Scientific Attitudes | Psychology Today. Retrieved 11 July 2021, from https://www.psychologytoday.com/intl/blog/social-justice-pacifists/202107/ideology-may-help-explain-anti-scientific-attitudes

Azevedo, F., & Jost, J. T. (2021). The ideological basis of antiscientific attitudes: Effects of authoritarianism, conservatism, religiosity, social dominance, and system justification. Group Processes & Intergroup Relations, 24(4), 518–549. https://doi.org/10.1177/1368430221990104

Bak, H.-J. (2001). Education and Public Attitudes toward Science: Implications for the ‘Deficit Model’ of Education and Support for Science and Technology. Social Science Quarterly, 82(4), 779–795. https://www.jstor.org/stable/42955760

Banks, G. C., Rogelberg, S. G., Woznyj, H. M., Landis, R. S., & Rupp, D. E. (2016). Editorial: Evidence on Questionable Research Practices: The Good, the Bad, and the Ugly. Journal of Business and Psychology, 31(3), 323–338. https://doi.org/10.1007/s10869-016-9456-7

Barba, L. A. (2018). Terminologies for Reproducible Research. ArXiv:1802.03311 [Cs]. http://arxiv.org/abs/1802.03311

Bardsley, N. (2018). What lessons does the “replication crisis”  in psychology hold for experimental economics? In A. Lewis (Ed.), The Cambridge Handbook of Psychology and Economic Behavior (2nd ed.). CAMBRIDGE UNIVERSITY PRESS.

Barnes, R. M., Johnston, H. M., MacKenzie, N., Tobin, S. J., & Taglang, C. M. (2018). The effect of ad hominem attacks on the evaluation of claims promoted by scientists. PLOS ONE, 13(1), e0192025. https://doi.org/10.1371/journal.pone.0192025

Bartoš, F., & Schimmack, U. (2020). Z-Curve.2.0: Estimating Replication Rates and Discovery Rates [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/urgtn

Bateman, I., Kahneman, D., Munro, A., Starmer, C., & Sugden, R. (2005). Testing competing models of loss aversion: An adversarial collaboration. Journal of Public Economics, 89(8), 1561–1580. https://doi.org/10.1016/j.jpubeco.2004.06.013

Baturay, M. H. (2015). An Overview of the World of MOOCs. Procedia - Social and Behavioral Sciences, 174, 427–433. https://doi.org/10.1016/j.sbspro.2015.01.685

Bazeley, P. (2003). Defining ‘Early Career’ in Research. Higher Education, 45(3), 257–279. https://doi.org/10.1023/A:1022698529612

Beffara Bret, B., Beffara Bret, A., & Nalborczyk, L. (2021). A fully automated, transparent, reproducible, and blind protocol for sequential analyses. Meta-Psychology, 5. https://doi.org/10.15626/MP.2018.869

Behrens, J. T. (1997). Principles and procedures of exploratory data analysis. Psychological Methods, 2(2), 131–160. https://doi.org/10.1037/1082-989X.2.2.131

Beller, S., & Bender, A. (2017). Theory, the Final Frontier? A Corpus-Based Analysis of the Role of Theory in Psychological Articles. Frontiers in Psychology, 8, 951. https://doi.org/10.3389/fpsyg.2017.00951

Benoit, K., Conway, D., Lauderdale, B. E., Laver, M., & Mikhaylov, S. (2016). Crowd-sourced Text Analysis: Reproducible and Agile Production of Political Data. American Political Science Review, 110(2), 278–295. https://doi.org/10.1017/S0003055416000058

Bhopal, R., Rankin, J., McColl, E., Thomas, L., Kaner, E., Stacy, R., Pearson, P., Vernon, B., & Rodgers, H. (1997). The vexed question of authorship: Views of researchers in a British medical faculty. BMJ, 314(7086), 1009–1009. https://doi.org/10.1136/bmj.314.7086.1009

BIAS | Definition of BIAS by Oxford Dictionary on Lexico.com also meaning of BIAS. (n.d.). Lexico Dictionaries | English. Retrieved 9 July 2021, from https://www.lexico.com/definition/bias

BIDS. (2020a). About BIDS. Brain Imaging Data Structure. https://bids.neuroimaging.io/

BIDS. (2020b). Modality agnostic files—Brain Imaging Data Structure v1.6.0. Brain Imaging Data Structure. https://bids-specification.readthedocs.io/en/stable/03-modality-agnostic-files.html

Bik, E. M., Casadevall, A., & Fang, F. C. (2016). The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications. MBio, 7(3). https://doi.org/10.1128/mBio.00809-16

Bilder, G. (2013, September 20). DOIs unambiguously and persistently identify published, trustworthy, citable online scholarly literature. Right? [Website]. Crossref. https://www.crossref.org/blog/dois-unambiguously-and-persistently-identify-published-trustworthy-citable-online-scholarly-literature-right/

Bishop, D. V. (2020). The psychology of experimental psychologists: Overcoming cognitive constraints to improve research: The 47th Sir Frederic Bartlett Lecture. Quarterly Journal of Experimental Psychology, 73(1), 1–19. https://doi.org/10.1177/1747021819886519

Björneborn, L., & Ingwersen, P. (2004). Toward a basic framework for webometrics. Journal of the American Society for Information Science and Technology, 55(14), 1216–1227. https://doi.org/10.1002/asi.20077

Blohowiak, B. B., Cohoon, J., de-Wit, L., Eich, E., Farach, F. J., Hasselman, F., Holcombe, A. O., Humphreys, M., Lewis, M., & Nosek, B. A. (2013). Badges to Acknowledge Open Practices. https://osf.io/tvyxz/

BMJ. (2015, September 22). Introducing ‘How to write and publish a Study Protocol’ using BMJ’s new eLearning programme: Research to Publication. BMJ Open. https://blogs.bmj.com/bmjopen/2015/09/22/introducing-how-to-write-and-publish-a-study-protocol-using-bmjs-new-elearning-programme-research-to-publication/

Boivin, A., Richards, T., Forsythe, L., Grégoire, A., L’Espérance, A., Abelson, J., & Carman, K. L. (2018). Evaluating patient and public involvement in research. BMJ, k5147. https://doi.org/10.1136/bmj.k5147

Bol, T., de Vaan, M., & van de Rijt, A. (2018). The Matthew effect in science funding. Proceedings of the National Academy of Sciences, 115(19), 4887–4890. https://doi.org/10.1073/pnas.1719557115

Bollen, K. A. (1989). Structural equations with latent variables. Wiley.

Borenstein, M. (Ed.). (2009). Introduction to meta-analysis. John Wiley & Sons.

Bornmann, L., Ganser, C., Tekles, A., & Leydesdorff, L. (2019). Does the $h_\alpha$ index reinforce the Matthew effect in science? Agent-based simulations using Stata and R. ArXiv:1905.11052 [Physics]. http://arxiv.org/abs/1905.11052

Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2004). The Concept of Validity. Psychological Review, 111(4), 1061–1071. https://doi.org/10.1037/0033-295X.111.4.1061

Borsboom, D., van der Maas, H., Dalege, J., Kievit, R., & Haig, B. (2020). Theory Construction Methodology: A practical framework for theory formation in psychology [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/w5tp8

Bortoli, S. (2021, April 1). NIHR Guidance on co-producing a research project. Learning For Involvement. https://www.learningforinvolvement.org.uk/?opportunity=nihr-guidance-on-co-producing-a-research-project

Bourne, P. E., Polka, J. K., Vale, R. D., & Kiley, R. (2017). Ten simple rules to consider regarding preprint submission. PLOS Computational Biology, 13(5), e1005473. https://doi.org/10.1371/journal.pcbi.1005473

Bouvy, J. C., & Mujoomdar, M. (2019). All-Male Panels and Gender Diversity of Issue Panels and Plenary Sessions at ISPOR Europe. PharmacoEconomics - Open, 3(3), 419–422. https://doi.org/10.1007/s41669-019-0153-0

Box, G. E. P. (1976). Science and Statistics. Journal of the American Statistical Association, 71(356), 791–799. https://doi.org/10.1080/01621459.1976.10480949

Bramoulle, Y., & Saint-Paul, G. (2007). Research Cycles. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.965816

Brand, A., Allen, L., Altman, M., Hlava, M., & Scott, J. (2015). Beyond authorship: Attribution, contribution, collaboration, and credit. Learned Publishing, 28(2), 151–155. https://doi.org/10.1087/20150211

Brandt, M. J., IJzerman, H., Dijksterhuis, A., Farach, F. J., Geller, J., Giner-Sorolla, R., Grange, J. A., Perugini, M., Spies, J. R., & van ’t Veer, A. (2014). The Replication Recipe: What makes for a convincing replication? Journal of Experimental Social Psychology, 50, 217–224. https://doi.org/10.1016/j.jesp.2013.10.005

Braun, V., & Clarke, V. (2013). Successful qualitative research: A practical guide for beginners. Sage. https://books.google.co.uk/books?hl=en&lr=&id=nYMQAgAAQBAJ&oi=fnd&pg=PP2&ots=SqJAD7C-5w&sig=6hBnRUj4z31CbylBTRzfIudISME#v=onepage&q&f=false

Brembs, B., Button, K., & Munafò, M. (2013). Deep impact: Unintended consequences of journal rank. Frontiers in Human Neuroscience, 7. https://doi.org/10.3389/fnhum.2013.00291

Brewer, P. R., & Ley, B. L. (2013). Whose Science Do You Believe? Explaining Trust in Sources of Scientific Information About the Environment. Science Communication, 35(1), 115–137. https://doi.org/10.1177/1075547012441691

Breznau, N., Rinke, E. M., Wuttke, A., Adem, M., Adriaans, J., Alvarez-Benjumea, A., Andersen, H. K., Auer, D., Azevedo, F., Bahnsen, O., Balzer, D., Bauer, G., Bauer, P., Baumann, M., Baute, S., Benoit, V., Bernauer, J., Berning, C., Berthold, A., … Nguyen, H. H. V. (2021). Observing Many Researchers Using the Same Data and Hypothesis Reveals a Hidden Universe of Uncertainty [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/cd5j9

Breznau, N., Rinke, E. M., Wuttke, A., Nguyen, H. H. V., Adem, M., Adriaans, J., Akdeniz, E., Alvarez-Benjumea, A., Andersen, H. K., Auer, D., Azevedo, F., Bahnsen, O., Bai, L., Balzer, D., Bauer, G., Bauer, P., Baumann, M., Baute, S., Benoit, V., … Żółtak, T. (2021). How Many Replicators Does It Take to Achieve Reliability? Investigating Researcher Variability in a Crowdsourced Replication [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/j7qta

Brod, M., Tesler, L. E., & Christensen, T. L. (2009). Qualitative research and content validity: Developing best practices based on science and experience. Quality of Life Research, 18(9), 1263–1278. https://doi.org/10.1007/s11136-009-9540-9

Brooks, T. A. (1985). Private acts and public objects: An investigation of citer motivations. Journal of the American Society for Information Science, 36(4), 223–229. https://doi.org/10.1002/asi.4630360402

Brown, J. (2010). An introduction to overlay journals (Repositories Support Project, pp. 1–6). University College London.

Brown, N. J. L., & Heathers, J. A. J. (2017). The GRIM Test: A Simple Technique Detects Numerous Anomalies in the Reporting of Results in Psychology. Social Psychological and Personality Science, 8(4), 363–369. https://doi.org/10.1177/1948550616673876

Brown, N., Thompson, P., & Leigh, J. S. (2018). Making Academia More Accessible. Journal of Perspectives in Applied Academic Practice, 6(2), 82–90. https://doi.org/10.14297/jpaap.v6i2.348

Brulé, J. F., & Blount, A. (1989). Knowledge acquisition. McGraw-Hill.

Brunner, J., & Schimmack, U. (2020). Estimating Population Mean Power Under Conditions of Heterogeneity and Selection for Significance. Meta-Psychology, 4. https://doi.org/10.15626/MP.2018.874

Bruns, S. B., & Ioannidis, J. P. A. (2016). P-Curve and p-Hacking in Observational Research. PLOS ONE, 11(2), e0149144. https://doi.org/10.1371/journal.pone.0149144

Budapest Open Access Initiative | Read the Budapest Open Access Initiative. (2002, February 14). https://www.budapestopenaccessinitiative.org/read

Busse, C., Kach, A. P., & Wagner, S. M. (2017). Boundary Conditions: What They Are, How to Explore Them, Why We Need Them, and When to Consider Them. Organizational Research Methods, 20(4), 574–609. https://doi.org/10.1177/1094428116641191

Button, K. S., Chambers, C. D., Lawrence, N., & Munafò, M. R. (2020). Grassroots Training for Reproducible Science: A Consortium-Based Approach to the Empirical Dissertation. Psychology Learning & Teaching, 19(1), 77–90. https://doi.org/10.1177/1475725719857659

Button, K. S., Lawrence, N., Chambers, C. D., & Munafò, M. R. (2016). Instilling scientific rigour at the grassroots. The Psychologist, 29(16), 158–167.

Byrne, J. A., & Christopher, J. (2020). Digital magic, or the dark arts of the 21 ^st century—How can journals and peer reviewers detect manuscripts and publications from paper mills? FEBS Letters, 594(4), 583–589. https://doi.org/10.1002/1873-3468.13747

Campbell, D. T. (1957). Factors relevant to the validity of experiments in social settings. Psychological Bulletin, 54(4), 297–312. https://doi.org/10.1037/h0040950

Campbell, D. T., & Stanley, J. C. (2011). Experimental and quasi-experimental designs for research. Wadsworth.

Carp, J. (2012). On the Plurality of (Methodological) Worlds: Estimating the Analytic Flexibility of fMRI Experiments. Frontiers in Neuroscience, 6. https://doi.org/10.3389/fnins.2012.00149

Carsey, T. M. (2014). Making DA-RT a Reality. PS: Political Science & Politics, 47(01), 72–77. https://doi.org/10.1017/S1049096513001753

Carter, A., Tilling, K., & Munafo, M. R. (2021). Considerations of sample size and power calculations given a range of analytical scenarios [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/tcqrn

Case, C. M. (1928). Scholarship in sociology. Sociology and Social Research, 12, 323–340.

Cassidy, S. A., Dimova, R., Giguère, B., Spence, J. R., & Stanley, D. J. (2019). Failing Grade: 89% of Introduction-to-Psychology Textbooks That Define or Explain Statistical Significance Do So Incorrectly. Advances in Methods and Practices in Psychological Science, 2(3), 233–239. https://doi.org/10.1177/2515245919858072

Center for Open Science. (n.d.). Registered Reports. Retrieved 10 July 2021, from https://www.cos.io/initiatives/registered-reports

Centre for Open Science. (n.d.). Show Your Work. Share Your Work. Centre for Open Science. https://www.cos.io/

Chambers, C. D. (2013). Registered Reports: A new publishing initiative at Cortex. Cortex, 49(3), 609–610. https://doi.org/10.1016/j.cortex.2012.12.016

Chambers, C. D., Dienes, Z., McIntosh, R. D., Rotshtein, P., & Willmes, K. (2015). Registered Reports: Realigning incentives in scientific publishing. Cortex, 66, A1–A2. https://doi.org/10.1016/j.cortex.2015.03.022

Chambers, C. D., & Tzavella, L. (2020). The past, present, and future of Registered Reports [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/43298

Chartier, C. R., Riegelman, A., & McCarthy, R. J. (2018). StudySwap: A Platform for Interlab Replication, Collaboration, and Resource Exchange. Advances in Methods and Practices in Psychological Science, 1(4), 574–579. https://doi.org/10.1177/2515245918808767

Chuard, P. J. C., Vrtílek, M., Head, M. L., & Jennions, M. D. (2019). Evidence that nonsignificant results are sometimes preferred: Reverse P-hacking or selective reporting? PLOS Biology, 17(1), e3000127. https://doi.org/10.1371/journal.pbio.3000127

CKAN - The open source data management system. (n.d.). Ckan. Retrieved 9 July 2021, from https://ckan.org/

Claerbout, J. F., & Karrenbach, M. (1992). Electronic documents give reproducible research a new meaning. SEG Technical Program Expanded Abstracts 1992, 601–604. https://doi.org/10.1190/1.1822162

Clark, H., Elsherif, M. M., & Leavens, D. A. (2019). Ontogeny vs. phylogeny in primate/canid comparisons: A meta-analysis of the object choice task. Neuroscience & Biobehavioral Reviews, 105, 178–189. https://doi.org/10.1016/j.neubiorev.2019.06.001

Closed access. (n.d.). CASRAI. Retrieved 9 July 2021, from https://casrai.org/term/closed-access/

Cohen, J. (1962). The statistical power of abnormal-social psychological research: A review. The Journal of Abnormal and Social Psychology, 65(3), 145–153. https://doi.org/10.1037/h0045186

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). L. Erlbaum Associates.

Cohn, J. P. (2008). Citizen Science: Can Volunteers Do Real Research? BioScience, 58(3), 192–197. https://doi.org/10.1641/B580303

Collaborative Assessment forTrustworthy Science|The repliCATS project. (n.d.). University of Melbourne. Retrieved 10 July 2021, from https://replicats.research.unimelb.edu.au/

Committee on Reproducibility and Replicability in Science, Board on Behavioral, Cognitive, and Sensory Sciences, Committee on National Statistics, Division of Behavioral and Social Sciences and Education, Nuclear and Radiation Studies Board, Division on Earth and Life Studies, Board on Mathematical Sciences and Analytics, Committee on Applied and Theoretical Statistics, Division on Engineering and Physical Sciences, Board on Research Data and Information, Committee on Science, Engineering, Medicine, and Public Policy, Policy and Global Affairs, & National Academies of Sciences, Engineering, and Medicine. (2019). Reproducibility and Replicability in Science (p. 25303). National Academies Press. https://doi.org/10.17226/25303

Confederation Of Open Access Repositories. (2020). COAR Community Framework for Best Practices in Repositories. (Version 1). Zenodo. https://doi.org/10.5281/ZENODO.4110829

Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design & analysis issues for field settings. Rand McNally College Pub. Co.

Corley, K. G., & Gioia, D. A. (2011). Building Theory about Theory Building: What Constitutes a Theoretical Contribution? Academy of Management Review, 36(1), 12–32. https://doi.org/10.5465/amr.2009.0486

Cornwall, A., & Jewkes, R. (1995). What is participatory research? Social Science & Medicine, 41(12), 1667–1676. https://doi.org/10.1016/0277-9536(95)00127-S

Correction or retraction? (2006). Nature, 444(7116), 123–124. https://doi.org/10.1038/444123b

Corti, L. (2019). Managing and sharing research data: A guide to good practice (2nd edition). SAGE Publications.

Cowan, N., Belletier, C., Doherty, J. M., Jaroslawska, A. J., Rhodes, S., Forsberg, A., Naveh-Benjamin, M., Barrouillet, P., Camos, V., & Logie, R. H. (2020). How Do Scientific Views Change? Notes From an Extended Adversarial Collaboration. Perspectives on Psychological Science, 15(4), 1011–1025. https://doi.org/10.1177/1745691620906415

CRediT - Contributor Roles Taxonomy. (n.d.). Casrai. Retrieved 9 July 2021, from https://casrai.org/credit/

Crenshaw, K. (1989). Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory and Antiracist Politics. University of Chicago Legal Forum, 1989(1), 8. https://chicagounbound.uchicago.edu/uclf/vol1989/iss1/8

Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302. https://doi.org/10.1037/h0040957

Cronin, B. (2001). Hyperauthorship: A postmodern perversion or evidence of a structural shift in scholarly communication practices? Journal of the American Society for Information Science and Technology, 52(7), 558–569. https://doi.org/10.1002/asi.1097

Crosetto, P. (2021, April 12). Is MDPI a predatory publisher? Paolo Crosetto. https://paolocrosetto.wordpress.com/2021/04/12/is-mdpi-a-predatory-publisher/

Crutzen, R., Ygram Peters, G.-J., & Mondschein, C. (2019). Why and how we should care about the General Data Protection Regulation. Psychology & Health, 34(11), 1347–1357. https://doi.org/10.1080/08870446.2019.1606222

Crüwell, S., van Doorn, J., Etz, A., Makel, M. C., Moshontz, H., Niebaum, J. C., Orben, A., Parsons, S., & Schulte-Mecklenbeck, M. (2019). Seven Easy Steps to Open Science: An Annotated Reading List. Zeitschrift Für Psychologie, 227(4), 237–248. https://doi.org/10.1027/2151-2604/a000387

Curran, P. J. (2009). The seemingly quixotic pursuit of a cumulative psychological science: Introduction to the special issue. Psychological Methods, 14(2), 77–80. https://doi.org/10.1037/a0015972

Curry, S. (2012, August 13). Sick of Impact Factors | Reciprocal Space. Reciprocal Space. http://occamstypewriter.org/scurry/2012/08/13/sick-of-impact-factors/

d’Espagnat, B. (2008). Is Science Cumulative? A Physicist Viewpoint. In L. Soler, H. Sankey, & P. Hoyningen-Huene (Eds.), Rethinking Scientific Change and Theory Comparison (pp. 145–151). Springer Netherlands. https://doi.org/10.1007/978-1-4020-6279-7_10

Data Management Expert Guide—CESSDA TRAINING. (n.d.). CESSDA. Retrieved 10 July 2021, from https://www.cessda.eu/Training/Training-Resources/Library/Data-Management-Expert-Guide

Data management plans | Stanford Libraries. (n.d.). Stanford Libraries. Retrieved 9 July 2021, from https://library.stanford.edu/research/data-management-services/data-management-plans

Data protection. (n.d.). [Text]. European Commission - European Commission. Retrieved 9 July 2021, from https://ec.europa.eu/info/law/law-topic/data-protection_en

Datacite Metadata Schema. (n.d.). DataCite Schema. Retrieved 9 July 2021, from https://schema.datacite.org/

Davies, G. M., & Gray, A. (2015). Don’t let spurious accusations of pseudoreplication limit our ability to learn from natural experiments (and other messy kinds of ecological monitoring). Ecology and Evolution, 5(22), 5295–5304. https://doi.org/10.1002/ece3.1782

Day, S., Rennie, S., Luo, D., & Tucker, J. D. (2020). Open to the public: Paywalls and the public rationale for open access medical research publishing. Research Involvement and Engagement, 6(1), 8. https://doi.org/10.1186/s40900-020-0182-y

Declaration on Research Assessment. (n.d.). Health Research Board. Retrieved 9 July 2021, from https://www.hrb.ie/funding/funding-schemes/before-you-apply/how-we-assess-applications/declaration-on-research-assessment/

Del Giudice, M., & Gangestad, S. W. (2021). A Traveler’s Guide to the Multiverse: Promises, Pitfalls, and a Framework for the Evaluation of Analytic Decisions. Advances in Methods and Practices in Psychological Science, 4(1), 251524592095492. https://doi.org/10.1177/2515245920954925

Deutsche Forschungsgemeinschaft. (2019). Guidelines for Safeguarding Good Research Practice. Code of Conduct. https://doi.org/10.5281/ZENODO.3923602

DeVellis, R. F. (2017). Scale development: Theory and applications (Fourth edition). SAGE.

Devezer, B., Navarro, D. J., Vandekerckhove, J., & Ozge Buzbas, E. (2021). The case for formal methodology in scientific reform. Royal Society Open Science, 8(3), rsos.200805, 200805. https://doi.org/10.1098/rsos.200805

Dickersin, K., & Min, Y.-I. (1993). Publication Bias: The Problem That Won’t Go Away. Annals of the New York Academy of Sciences, 703(1 Doing More Go), 135–148. https://doi.org/10.1111/j.1749-6632.1993.tb26343.x

Dienes, Z. (2008). Understanding Psychology as a Science: An Introduction to Scientific and Statistical Inference. Palgrave Macmillan. https://books.google.ca/books?id=qCQdBQAAQBAJ

Dienes, Z. (2011). Bayesian Versus Orthodox Statistics: Which Side Are You On? Perspectives on Psychological Science, 6(3), 274–290. https://doi.org/10.1177/1745691611406920

Dienes, Z. (2014). Using Bayes to get the most out of non-significant results. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00781

Dienes, Z. (2016). How Bayes factors change scientific practice. Journal of Mathematical Psychology, 72, 78–89. https://doi.org/10.1016/j.jmp.2015.10.003

Digital Object Identifier System Handbook. (n.d.). DOI. Retrieved 9 July 2021, from https://www.doi.org/hb.html

Directory of Open Access Journals. (n.d.). Retrieved 11 July 2021, from https://doaj.org/apply/transparency/

Doll, R., & Hill, A. B. (1954). The Mortality of Doctors in Relation to Their Smoking Habits. BMJ, 1(4877), 1451–1455. https://doi.org/10.1136/bmj.1.4877.1451

Domov | SKRN (Slovak Reproducibility network). (n.d.). SKRN. Retrieved 10 July 2021, from https://slovakrn.wixsite.com/skrn

Download JASP. (n.d.). JASP - Free and User-Friendly Statistical Software. Retrieved 9 July 2021, from https://jasp-stats.org/download/

Drost, E. A. (2011). Validity and reliability in social science research. Education Research and Perspectives, 38(1), 105–123.

Du Bois, W. E. B. (2018). The souls of Black folk: Essays and sketches.

Duval, S., & Tweedie, R. (2000a). A Nonparametric ‘Trim and Fill’ Method of Accounting for Publication Bias in Meta-Analysis. Journal of the American Statistical Association, 95(449), 89. https://doi.org/10.2307/2669529

Duval, S., & Tweedie, R. (2000b). Trim and Fill: A Simple Funnel-Plot-Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis. Biometrics, 56(2), 455–463. https://doi.org/10.1111/j.0006-341X.2000.00455.x

Duyx, B., Swaen, G. M. H., Urlings, M. J. E., Bouter, L. M., & Zeegers, M. P. (2019). The strong focus on positive results in abstracts may cause bias in systematic reviews: A case study on abstract reporting bias. Systematic Reviews, 8(1), 174. https://doi.org/10.1186/s13643-019-1082-9

Eagly, A. H., & Riger, S. (2014). Feminism and psychology: Critiques of methods and epistemology. American Psychologist, 69(7), 685–702. https://doi.org/10.1037/a0037372

Easterbrook, S. M. (2014). Open code for open science? Nature Geoscience, 7(11), 779–781. https://doi.org/10.1038/ngeo2283

Ebersole, C. R., Atherton, O. E., Belanger, A. L., Skulborstad, H. M., Allen, J. M., Banks, J. B., Baranski, E., Bernstein, M. J., Bonfiglio, D. B. V., Boucher, L., Brown, E. R., Budiman, N. I., Cairo, A. H., Capaldi, C. A., Chartier, C. R., Chung, J. M., Cicero, D. C., Coleman, J. A., Conway, J. G., … Nosek, B. A. (2016). Many Labs 3: Evaluating participant pool quality across the academic semester via replication. Journal of Experimental Social Psychology, 67, 68–82. https://doi.org/10.1016/j.jesp.2015.10.012

Editorial Director. (2021, May). What is a group author (collaborative author) and does it need an ORCID? JMIR Publications. https://support.jmir.org/hc/en-us/articles/115001449591-What-is-a-group-author-collaborative-author-and-does-it-need-an-ORCID-

Eldermire, E. (n.d.). LibGuides: Measuring your research impact: i10-Index. Retrieved 9 July 2021, from https://guides.library.cornell.edu/impact/author-impact-10

Eley, A. R. (Ed.). (2012). Becoming a successful early career researcher. Routledge.

Ellemers, N. (2021). Science as collaborative knowledge generation. British Journal of Social Psychology, 60(1), 1–28. https://doi.org/10.1111/bjso.12430

Elliott, K. C., & Resnik, D. B. (2019). Making Open Science Work for Science and Society. Environmental Health Perspectives, 127(7), 075002. https://doi.org/10.1289/EHP4808

Elm, E. von, Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007). Strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. BMJ, 335(7624), 806–808. https://doi.org/10.1136/bmj.39335.541782.AD

Elman, C., Gerring, J., & Mahoney, J. (Eds.). (2020). The production of knowledge: Enhancing progress in social science. Cambridge University Press.

Elmore, S. A. (2018). Preprints: What Role Do These Have in Communicating Scientific Results? Toxicologic Pathology, 46(4), 364–365. https://doi.org/10.1177/0192623318767322

Embargo (academic publishing). (2021). In Wikipedia. https://en.wikipedia.org/w/index.php?title=Embargo_(academic_publishing)&oldid=1016895567

Epskamp, S., & Nuijten, M. B. (2018). statcheck: Extract Statistics from Articles and Recompute p Values (1.3.0) [Computer software]. https://CRAN.R-project.org/package=statcheck

Esterling, K., Brady, D., & Schwitzgebel, E. (2021). The Necessity of Construct and External Validity for Generalized Causal Claims [Preprint]. Open Science Framework. https://doi.org/10.31219/osf.io/2s8w5

Etz, A., Gronau, Q. F., Dablander, F., Edelsbrunner, P. A., & Baribault, B. (2018). How to become a Bayesian in eight easy steps: An annotated reading list. Psychonomic Bulletin & Review, 25(1), 219–234. https://doi.org/10.3758/s13423-017-1317-5

European Commission. (2021). European Commission. Responsible Research & Innovation | Horizon 2020. https://ec.europa.eu/programmes/horizon2020/en/h2020-section/responsible-research-innovation

Evans, G., & Durant, J. (1995). The relationship between knowledge and attitudes in the public understanding of science in Britain. Public Understanding of Science, 4(1), 57–74. https://doi.org/10.1088/0963-6625/4/1/004

Evans, O., & Rubin, M. (2021). In a Class on Their Own: Investigating the Role of Social Integration in the Association Between Social Class and Mental Well-Being. Personality and Social Psychology Bulletin, 014616722110211. https://doi.org/10.1177/01461672211021190

Evidence Synthesis. (n.d.). LSHTM. Retrieved 9 July 2021, from https://www.lshtm.ac.uk/research/centres/centre-evaluation/evidence-synthesis

Fanelli, D. (2010). Do Pressures to Publish Increase Scientists’ Bias? An Empirical Support from US States Data. PLoS ONE, 5(4), e10271. https://doi.org/10.1371/journal.pone.0010271

Fanelli, D. (2018). Opinion: Is science really facing a reproducibility crisis, and do we need it to? Proceedings of the National Academy of Sciences, 115(11), 2628–2631. https://doi.org/10.1073/pnas.1708272114

Farrow, R. (2017). Open education and critical pedagogy. Learning, Media and Technology, 42(2), 130–146. https://doi.org/10.1080/17439884.2016.1113991

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146

Ferson, S., Joslyn, C. A., Helton, J. C., Oberkampf, W. L., & Sentz, K. (2004). Summary from the epistemic uncertainty workshop: Consensus amid diversity. Reliability Engineering & System Safety, 85(1–3), 355–369. https://doi.org/10.1016/j.ress.2004.03.023

Fiedler, K., Kutzner, F., & Krueger, J. I. (2012). The Long Way From α-Error Control to Validity Proper: Problems With a Short-Sighted False-Positive Debate. Perspectives on Psychological Science, 7(6), 661–669. https://doi.org/10.1177/1745691612462587

Fiedler, K., & Schwarz, N. (2016). Questionable Research Practices Revisited. Social Psychological and Personality Science, 7(1), 45–52. https://doi.org/10.1177/1948550615612150

Filipe, A., Renedo, A., & Marston, C. (2017). The co-production of what? Knowledge, values, and social relations in health care. PLOS Biology, 15(5), e2001403. https://doi.org/10.1371/journal.pbio.2001403

Findley, M. G., Jensen, N. M., Malesky, E. J., & Pepinsky, T. B. (2016). Can Results-Free Review Reduce Publication Bias? The Results and Implications of a Pilot Study. Comparative Political Studies, 49(13), 1667–1703. https://doi.org/10.1177/0010414016655539

Finlay, L., & Gough, B. (Eds.). (2003). Reflexivity: A practical guide for researchers in health and social sciences. Blackwell Science.

Flake, J. K., & Fried, E. I. (2020). Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them. Advances in Methods and Practices in Psychological Science, 3(4), 456–465. https://doi.org/10.1177/2515245920952393

Fletcher-Watson, S., Adams, J., Brook, K., Charman, T., Crane, L., Cusack, J., Leekam, S., Milton, D., Parr, J. R., & Pellicano, E. (2019). Making the future together: Shaping autism research through meaningful participation. Autism, 23(4), 943–953. https://doi.org/10.1177/1362361318786721

Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. (2013). emcee: The MCMC Hammer. Publications of the Astronomical Society of the Pacific, 125(925), 306–312. https://doi.org/10.1086/670067

Forrt. (2019). Introducing a Framework for Open and Reproducible Research Training (FORRT) [Preprint]. Open Science Framework. https://doi.org/10.31219/osf.io/bnh7p

FORRT - Framework for Open and Reproducible Research Training. (n.d.). FORRT. Retrieved 9 July 2021, from https://forrt.org/

Foster, MSLS, E. D., & Deardorff, MLIS, A. (2017). Open Science Framework (OSF). Journal of the Medical Library Association, 105(2). https://doi.org/10.5195/JMLA.2017.88

Franco, A., Malhotra, N., & Simonovits, G. (2014). Publication bias in the social sciences: Unlocking the file drawer. Science, 345(6203), 1502–1505. https://doi.org/10.1126/science.1255484

Frank, M. C., Bergelson, E., Bergmann, C., Cristia, A., Floccia, C., Gervain, J., Hamlin, J. K., Hannon, E. E., Kline, M., Levelt, C., Lew-Williams, C., Nazzi, T., Panneton, R., Rabagliati, H., Soderstrom, M., Sullivan, J., Waxman, S., & Yurovsky, D. (2017). A Collaborative Approach to Infant Research: Promoting Reproducibility, Best Practices, and Theory-Building. Infancy, 22(4), 421–435. https://doi.org/10.1111/infa.12182

Franzoni, C., & Sauermann, H. (2014). Crowd science: The organization of scientific research in open collaborative projects. Research Policy, 43(1), 1–20. https://doi.org/10.1016/j.respol.2013.07.005

Fraser, H., Bush, M., Wintle, B., Mody, F., Smith, E. T., Hanea, A., Gould, E., Hemming, V., Hamilton, D. G., Rumpff, L., Wilkinson, D. P., Pearson, R., Singleton Thorn, F., Ashton, raquel, Willcox, A., Gray, C. T., Head, A., Ross, M., Groenewegen, R., … Fidler, F. (2021). Predicting reliability through structured expert elicitation with repliCATS (Collaborative Assessments for Trustworthy Science) [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/2pczv

Free Our Knowledge. (n.d.). About. Free Our Knowledge. Retrieved 9 July 2021, from https://freeourknowledge.org/about/

Frigg, R., & Hartmann, S. (2020). Models in Science. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Spring 2020). Metaphysics Research Lab, Stanford University. https://plato.stanford.edu/archives/spr2020/entries/models-science/

Frith, U. (2020). Fast Lane to Slow Science. Trends in Cognitive Sciences, 24(1), 1–2. https://doi.org/10.1016/j.tics.2019.10.007

Galligan, F., & Dyas-Correia, S. (2013). Altmetrics: Rethinking the Way We Measure. Serials Review, 39(1), 56–61. https://doi.org/10.1080/00987913.2013.10765486

Garson, G. D. (2012). Testing Statistical Assumptions (2012 edition). North Carolina State University.

Gelman, A., & Carlin, J. (2014). Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors. Perspectives on Psychological Science, 9(6), 641–651. https://doi.org/10.1177/1745691614551642

Gelman, A., & Loken, E. (2013). The garden of forking paths: Why multiple comparisons can be a problem, even when there is no “fishing expedition” or “p-hacking” and the research hypothesis was posited ahead of time [Doctoral dissertation, Columbia University]. http://www.stat.columbia.edu/~gelman/research/unpublished/p_hacking.pdf

Gelman, A., & Stern, H. (2006). The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant. The American Statistician, 60(4), 328–331. https://doi.org/10.1198/000313006X152649

Generalizability. (2018). In B. B. Frey, The SAGE Encyclopedia of Educational Research, Measurement, and      Evaluation. SAGE Publications, Inc. https://doi.org/10.4135/9781506326139.n284

Gentleman, R. (2005). Reproducible Research: A Bioinformatics Case Study. Statistical Applications in Genetics and Molecular Biology, 4(1). https://doi.org/10.2202/1544-6115.1034

Get Involved—Creative Commons. (n.d.). Creative Commons. Retrieved 9 July 2021, from https://creativecommons.org/about/get-involved/

Geyer, C., J. (2003). Maximum Likelihood in R (pp. 1–9) [Preprint]. Open Science Framework.

Geyer, C., J. (2007). Stat 5102 Notes: Maximum Likelihood (pp. 1–8) [Preprint]. Open Science Framework.

Gilroy, P. (2002). The black Atlantic: Modernity and double consciousness (3. impr., reprint). Verso.

Giner-Sorolla, R., Carpenter, T., Montoya, A., & Neil Lewis, J. (2019). SPSP Power Analysis Working Group 2019. https://osf.io/9bt5s/

Ginsparg, P. (1997). Winners and Losers in the Global Research Village. The Serials Librarian, 30(3–4), 83–95. https://doi.org/10.1300/J123v30n03_13

Ginsparg, P. (2001, February 20). Creating a global knowledge network. Cornell University. http://www.cs.cornell.edu/~ginsparg/physics/blurb/pg01unesco.html

Gioia, D. A., & Pitre, E. (1990). Multiparadigm Perspectives on Theory Building. Academy of Management Review, 15(4), 584–602. https://doi.org/10.5465/amr.1990.4310758

Git—About Version Control. (n.d.). Git. Retrieved 9 July 2021, from https://git-scm.com/book/en/v2/Getting-Started-About-Version-Control

Glass, D. J., & Hall, N. (2008). A Brief History of the Hypothesis. Cell, 134(3), 378–381. https://doi.org/10.1016/j.cell.2008.07.033

Gollwitzer, M., Abele-Brehm, A., Fiebach, C., Ramthun, R., Scheel, A. M., Schönbrodt, F. D., & Steinberg, U. (2020). Data Management and Data Sharing in Psychological Science: Revision of the DGPs Recommendations [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/24ncs

Goodman, S. N., Fanelli, D., & Ioannidis, J. P. A. (2016). What does research reproducibility mean? Science Translational Medicine, 8(341), 341ps12-341ps12. https://doi.org/10.1126/scitranslmed.aaf5027

Goodman, S. W., & Pepinsky, T. B. (2019). Gender Representation and Strategies for Panel Diversity: Lessons from the APSA Annual Meeting. PS: Political Science & Politics, 52(4), 669–676. https://doi.org/10.1017/S1049096519000908

Gorgolewski, K. J., Auer, T., Calhoun, V. D., Craddock, R. C., Das, S., Duff, E. P., Flandin, G., Ghosh, S. S., Glatard, T., Halchenko, Y. O., Handwerker, D. A., Hanke, M., Keator, D., Li, X., Michael, Z., Maumet, C., Nichols, B. N., Nichols, T. E., Pellman, J., … Poldrack, R. A. (2016). The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Scientific Data, 3(1), 160044. https://doi.org/10.1038/sdata.2016.44

Graham, I. D., McCutcheon, C., & Kothari, A. (2019). Exploring the frontiers of research co-production: The Integrated Knowledge Translation Research Network concept papers. Health Research Policy and Systems, 17(1), 88, s12961-019-0501–0507. https://doi.org/10.1186/s12961-019-0501-7

GRN · German Reproducibility Network. (n.d.). German Reproducibility Network. Retrieved 10 July 2021, from https://reproducibilitynetwork.de/

Grossmann, A., & Brembs, B. (2021). Current market rates for scholarly publishing services. F1000Research, 10, 20. https://doi.org/10.12688/f1000research.27468.1

Grzanka, P. R., Flores, M. J., VanDaalen, R. A., & Velez, G. (2020). Intersectionality in psychology: Translational science for social justice. Translational Issues in Psychological Science, 6(4), 304–313. https://doi.org/10.1037/tps0000276

Guenther, E. A., & Rodriguez, J. K. (2020, October 14). What’s wrong with ‘manels’ and what can we do about them. The Conversation. http://theconversation.com/whats-wrong-with-manels-and-what-can-we-do-about-them-148068

Guest, O. (2017, June 5). @BrianNosek @ctitusbrown @StuartBuck1 @DaniRabaiotti @Julie_B92 @jeroenbosman @blahah404 @OSFramework Thanks! Hopefully this thread & many other similar discussions & blogs will help make it less Bropen Science and more Open Science. *hides* [Tweet]. @o_guest. https://twitter.com/o_guest/status/871675631062458368

Guest, O., & Martin, A. E. (2021). How Computational Modeling Can Force Theory Building in Psychological Science. Perspectives on Psychological Science, 174569162097058. https://doi.org/10.1177/1745691620970585

Guide to the UK General Data Protection Regulation (UK GDPR). (2021, July 1). ICO. https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/

Haak, L. L., Fenner, M., Paglione, L., Pentz, E., & Ratner, H. (2012). ORCID: A system to uniquely identify researchers. Learned Publishing, 25(4), 259–264. https://doi.org/10.1087/20120404

Hackett, R., & Kelly, S. (2020). Publishing ethics in the era of paper mills. Biology Open, 9(10), bio056556. https://doi.org/10.1242/bio.056556

Hahn, G. J., & Meeker, W. Q. (1993). Assumptions for Statistical Inference. The American Statistician, 47(1), 1–11. https://doi.org/10.1080/00031305.1993.10475924

Hardwicke, T. E., Bohn, M., MacDonald, K., Hembacher, E., Nuijten, M. B., Peloquin, B. N., deMayo, B. E., Long, B., Yoon, E. J., & Frank, M. C. (2021). Analytic reproducibility in articles receiving open data badges at the journal Psychological Science: An observational study. Royal Society Open Science, 8(1), 201494. https://doi.org/10.1098/rsos.201494

Hardwicke, T. E., Jameel, L., Jones, M., Walczak, E. J., & Magis-Weinberg, L. (2014). Only Human: Scientists, Systems, and Suspect Statistics. Opticon1826, 16. https://doi.org/10.5334/opt.ch

Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., … Oliphant, T. E. (2020). Array programming with NumPy. Nature, 585(7825), 357–362. https://doi.org/10.1038/s41586-020-2649-2

Hart, D., & Silka, L. (n.d.). Rebuilding the Ivory Tower: A Bottom-Up Experiment in Aligning Research With Societal Needs. Issues in Science and Technology, 36(3), 79–85. https://issues.org/aligning-research-with-societal-needs/

Hartgerink, C. H. J., Wicherts, J. M., & van Assen, M. A. L. M. (2017). Too Good to be False: Nonsignificant Results Revisited. Collabra: Psychology, 3(1), 9. https://doi.org/10.1525/collabra.71

Hayes, B. C., & Tariq, V. N. (2000). Gender differences in scientific knowledge and attitudes toward science: A comparative study of four Anglo-American nations. Public Understanding of Science, 9(4), 433–447. https://doi.org/10.1088/0963-6625/9/4/306

Haynes, S. N., Richard, D. C. S., & Kubany, E. S. (1995). Content validity in psychological assessment: A functional approach to concepts and methods. Psychological Assessment, 7(3), 238–247. https://doi.org/10.1037/1040-3590.7.3.238

Healy, K. (2018). Data visualization: A practical introduction. Princeton University Press.

Heathers, J. A., Anaya, J., van der Zee, T., & Brown, N. J. (2018). Recovering data from summary statistics: Sample Parameter Reconstruction via Iterative TEchniques (SPRITE) [Preprint]. PeerJ Preprints. https://doi.org/10.7287/peerj.preprints.26968v1

Hendriks, F., Kienhues, D., & Bromme, R. (2016). Trust in Science and the Science of Trust. In B. Blöbaum (Ed.), Trust and Communication in a Digitized World (pp. 143–159). Springer International Publishing. https://doi.org/10.1007/978-3-319-28059-2_8

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83. https://doi.org/10.1017/S0140525X0999152X

Henrich, J. P. (2020). The WEIRDest people in the world: How the West Became Psychologically Peculiar and Particularly Prosperous. Farrar, Straus and Giroux.

Herrmannova, D., & Knoth, P. (2016). Semantometrics: Towards Fulltext-based Research Evaluation. Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries, 235–236. https://doi.org/10.1145/2910896.2925448

Heyman, T., Moors, P., & Rabagliati, H. (2020). The benefits of adversarial collaboration for commentaries. Nature Human Behaviour, 4(12), 1217–1217. https://doi.org/10.1038/s41562-020-00978-6

Higgins, J. P. T., & Cochrane Collaboration (Eds.). (2020). Cochrane handbook for systematic reviews of interventions (Second edition). Wiley-Blackwell.

Himmelstein, D. S., Rubinetti, V., Slochower, D. R., Hu, D., Malladi, V. S., Greene, C. S., & Gitter, A. (2019). Open collaborative writing with Manubot. PLOS Computational Biology, 15(6), e1007128. https://doi.org/10.1371/journal.pcbi.1007128

Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572. https://doi.org/10.1073/pnas.0507655102

Hitchcock, C., Meyer, A., Rose, D., & Jackson, R. (2002). Providing New Access to the General Curriculum: Universal Design for Learning. TEACHING Exceptional Children, 35(2), 8–17. https://doi.org/10.1177/004005990203500201

Hoekstra, R., Kiers, H., & Johnson, A. (2012). Are Assumptions of Well-Known Statistical Techniques Checked, and Why (Not)? Frontiers in Psychology, 3. https://doi.org/10.3389/fpsyg.2012.00137

Hogg, D. W., Bovy, J., & Lang, D. (2010). Data analysis recipes: Fitting a model to data. ArXiv:1008.4686 [Astro-Ph, Physics:Physics]. http://arxiv.org/abs/1008.4686

Hoijtink, H., Mulder, J., van Lissa, C., & Gu, X. (2019). A tutorial on testing hypotheses using the Bayes factor. Psychological Methods, 24(5), 539–556. https://doi.org/10.1037/met0000201

Holcombe, A. O. (2019). Contributorship, Not Authorship: Use CRediT to Indicate Who Did What. Publications, 7(3), 48. https://doi.org/10.3390/publications7030048

Holden, R. R. (2010). Face Validity. In I. B. Weiner & W. E. Craighead (Eds.), The Corsini Encyclopedia of Psychology (p. corpsy0341). John Wiley & Sons, Inc. https://doi.org/10.1002/9780470479216.corpsy0341

Home | re3data.org. (n.d.). DataCite Schema. Retrieved 10 July 2021, from https://www.re3data.org/

Homepage. (n.d.). Open Science MOOC. Retrieved 9 July 2021, from https://opensciencemooc.eu/

Houtkoop, B. L., Chambers, C., Macleod, M., Bishop, D. V. M., Nichols, T. E., & Wagenmakers, E.-J. (2018). Data Sharing in Psychology: A Survey on Barriers and Preconditions. Advances in Methods and Practices in Psychological Science, 1(1), 70–85. https://doi.org/10.1177/2515245917751886

How to Make Inclusivity More Than Just an Office Buzzword. (n.d.). Kellogg Insight. Retrieved 9 July 2021, from https://insight.kellogg.northwestern.edu/article/how-to-make-inclusivity-more-than-just-an-office-buzzword

Https://improvingpsych.org/. (n.d.). Retrieved 10 July 2021, from https://improvingpsych.org/

Huber, B., Barnidge, M., Gil de Zúñiga, H., & Liu, J. (2019). Fostering public trust in science: The role of social media. Public Understanding of Science, 28(7), 759–777. https://doi.org/10.1177/0963662519869097

Huber, C. (2016a, November 1). The Stata Blog » Introduction to Bayesian statistics, part 1: The basic concepts. The Stata Blog. https://blog.stata.com/2016/11/01/introduction-to-bayesian-statistics-part-1-the-basic-concepts/

Huber, C. (2016b, November 15). Introduction to Bayesian statistics, part 2: MCMC and the Metropolis–Hastings algorithm. The Stata Blog. https://blog.stata.com/2016/11/15/introduction-to-bayesian-statistics-part-2-mcmc-and-the-metropolis-hastings-algorithm/

Huelin, R., Iheanacho, I., Payne, K., & Sandman, K. (2015). What’s in a Name? Systematic and Non-Systematic Literature Reviews, and Why the Distinction Matters—Evidera (The Evidence Forum, pp. 34–37). https://www.evidera.com/resource/whats-in-a-name-systematic-and-non-systematic-literature-reviews-and-why-the-distinction-matters/

Hüffmeier, J., Mazei, J., & Schultze, T. (2016). Reconceptualizing replication as a sequence of different studies: A replication typology. Journal of Experimental Social Psychology, 66, 81–92. https://doi.org/10.1016/j.jesp.2015.09.009

Hunter, J. E., & Schmidt, F. L. (2015). Methods of meta-analysis: Correcting error and bias in research findings (Third edition). SAGE.

Hurlbert, S. H. (1984). Pseudoreplication and the Design of Ecological Field Experiments. Ecological Monographs, 54(2), 187–211. https://doi.org/10.2307/1942661

ICMJE | Home. (n.d.). International Committee of Medical Journal Editors. Retrieved 11 July 2021, from http://www.icmje.org/

Ikeda A., Xu H., Fuji N., Zhu S., & Yamada Y. (2019). Questionable research practices following pre-registration. 心理学評論刊行会. https://doi.org/10.24602/sjpr.62.3_281

Initial revision of ‘git’, the information manager from hell · git/git@e83c516. (n.d.). GitHub. Retrieved 9 July 2021, from https://github.com/git/git/commit/e83c5163316f89bfbde7d9ab23ca2e25604af290

International Committee of Medical Journal Editors. (n.d.). ICMJE | Recommendations | Author Responsibilities—Disclosure of Financial and Non-Financial Relationships and Activities, and Conflicts of Interest. ICJME. http://www.icmje.org/recommendations/browse/roles-and-responsibilities/author-responsibilities--conflicts-of-interest.html

INVOLVE – INVOLVE Supporting public involvement in NHS, public health and social care research. (n.d.). Retrieved 9 July 2021, from https://www.invo.org.uk/

Ioannidis, J. P. A. (2005). Why Most Published Research Findings Are False. PLoS Medicine, 2(8), e124. https://doi.org/10.1371/journal.pmed.0020124

Ioannidis, J. P. A., Fanelli, D., Dunne, D. D., & Goodman, S. N. (2015). Meta-research: Evaluation and Improvement of Research Methods and Practices. PLOS Biology, 13(10), e1002264. https://doi.org/10.1371/journal.pbio.1002264

JabRef—Free Reference Manager—Stay on top of your Literature. (n.d.). JabRef. Retrieved 9 July 2021, from https://www.jabref.org/

Jacobson, D., & Mustafa, N. (2019). Social Identity Map: A Reflexivity Tool for Practicing Explicit Positionality in Critical Qualitative Research. International Journal of Qualitative Methods, 18, 160940691987007. https://doi.org/10.1177/1609406919870075

Jafar, A. J. N. (2018). What is positionality and should it be expressed in quantitative studies? Emergency Medicine Journal, emermed-2017-207158. https://doi.org/10.1136/emermed-2017-207158

James, K. L., Randall, N. P., & Haddaway, N. R. (2016). A methodology for systematic mapping in environmental sciences. Environmental Evidence, 5(1), 7. https://doi.org/10.1186/s13750-016-0059-6

Jamovi—Stats. Open. Now. (n.d.). Jamovi. Retrieved 9 July 2021, from https://www.jamovi.org/

Jannot, A.-S., Agoritsas, T., Gayet-Ageron, A., & Perneger, T. V. (2013). Citation bias favoring statistically significant studies was present in medical research. Journal of Clinical Epidemiology, 66(3), 296–301. https://doi.org/10.1016/j.jclinepi.2012.09.015

John, L. K., Loewenstein, G., & Prelec, D. (2012). Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling. Psychological Science, 23(5), 524–532. https://doi.org/10.1177/0956797611430953

Jones, A., Worrall, S., Rudin, L., Duckworth, J. J., & Christiansen, P. (2021). May I have your attention, please? Methodological and analytical flexibility in the addiction stroop. Addiction Research & Theory, 1–14. https://doi.org/10.1080/16066359.2021.1876847

Joseph, T. D., & Hirshfield, L. E. (2011). ‘Why don’t you get somebody new to do it?’ Race and cultural taxation in the academy. Ethnic and Racial Studies, 34(1), 121–141. https://doi.org/10.1080/01419870.2010.496489

Kalliamvakou, E., Gousios, G., Blincoe, K., Singer, L., German, D. M., & Damian, D. (2014). The promises and perils of mining GitHub. Proceedings of the 11th Working Conference on Mining Software Repositories - MSR 2014, 92–101. https://doi.org/10.1145/2597073.2597074

kamraro. (2014, April 1). Responsible research & innovation [Text]. Horizon 2020 - European Commission. https://ec.europa.eu/programmes/horizon2020/en/h2020-section/responsible-research-innovation

Kathawalla, U.-K., Silverstein, P., & Syed, M. (2021). Easing Into Open Science: A Guide for Graduate Students and Their Advisors. Collabra: Psychology, 7(1), 18684. https://doi.org/10.1525/collabra.18684

Kelley, T. (1927). Interpretation of educational measurements. World Book Co.

Kerr, J. R., & Wilson, M. S. (2021). Right-wing authoritarianism and social dominance orientation predict rejection of science and scientists. Group Processes & Intergroup Relations, 24(4), 550–567. https://doi.org/10.1177/1368430221992126

Kerr, N. L. (1998). HARKing: Hypothesizing After the Results are Known. Personality and Social Psychology Review, 2(3), 196–217. https://doi.org/10.1207/s15327957pspr0203_4

Kerr, N. L., Ao, X., Hogg, M. A., & Zhang, J. (2018). Addressing replicability concerns via adversarial collaboration: Discovering hidden moderators of the minimal intergroup discrimination effect. Journal of Experimental Social Psychology, 78, 66–76. https://doi.org/10.1016/j.jesp.2018.05.001

Kidwell, M. C., Lazarević, L. B., Baranski, E., Hardwicke, T. E., Piechowski, S., Falkenberg, L.-S., Kennett, C., Slowik, A., Sonnleitner, C., Hess-Holden, C., Errington, T. M., Fiedler, S., & Nosek, B. A. (2016). Badges to Acknowledge Open Practices: A Simple, Low-Cost, Effective Method for Increasing Transparency. PLOS Biology, 14(5), e1002456. https://doi.org/10.1371/journal.pbio.1002456

Kienzler, H., & Fontanesi, C. (2017). Learning through inquiry: A Global Health Hackathon. Teaching in Higher Education, 22(2), 129–142. https://doi.org/10.1080/13562517.2016.1221805

Kiernan, C. (1999). Participation in Research by People with Learning Disability: Origins and Issues. British Journal of Learning Disabilities, 27(2), 43–47. https://doi.org/10.1111/j.1468-3156.1999.tb00084.x

King, G. (1995). Replication, Replication. PS: Political Science and Politics, 28(3), 444. https://doi.org/10.2307/420301

Kitzes, J., Turek, D., & Deniz, F. (Eds.). (2018). The practice of reproducible research: Case studies and lessons from the data-intensive sciences. University of California Press.

Kiureghian, A. D., & Ditlevsen, O. (2009). Aleatory or epistemic? Does it matter? Structural Safety, 31(2), 105–112. https://doi.org/10.1016/j.strusafe.2008.06.020

Klein, O., Hardwicke, T. E., Aust, F., Breuer, J., Danielsson, H., Mohr, A. H., IJzerman, H., Nilsonne, G., Vanpaemel, W., & Frank, M. C. (2018). A Practical Guide for Transparency in Psychological Science. Collabra: Psychology, 4(1), 20. https://doi.org/10.1525/collabra.158

Klein, R. A., Ratliff, K. A., Vianello, M., Adams, R. B., Bahník, Š., Bernstein, M. J., Bocian, K., Brandt, M. J., Brooks, B., Brumbaugh, C. C., Cemalcilar, Z., Chandler, J., Cheong, W., Davis, W. E., Devos, T., Eisner, M., Frankowska, N., Furrow, D., Galliani, E. M., … Nosek, B. A. (2014). Investigating Variation in Replicability: A “Many Labs” Replication Project. Social Psychology, 45(3), 142–152. https://doi.org/10.1027/1864-9335/a000178

Klein, R. A., Vianello, M., Hasselman, F., Adams, B. G., Adams, R. B., Alper, S., Aveyard, M., Axt, J. R., Babalola, M. T., Bahník, Š., Batra, R., Berkics, M., Bernstein, M. J., Berry, D. R., Bialobrzeska, O., Binan, E. D., Bocian, K., Brandt, M. J., Busching, R., … Nosek, B. A. (2018). Many Labs 2: Investigating Variation in Replicability Across Samples and Settings. Advances in Methods and Practices in Psychological Science, 1(4), 443–490. https://doi.org/10.1177/2515245918810225

Kleinberg, B., Mozes, M., van der Toolen, Y., & Verschuere, B. (2017). NETANOS - Named entity-based Text Anonymization for Open Science [Preprint]. Open Science Framework. https://doi.org/10.31219/osf.io/w9nhb

Knoth, P., & Herrmannova, D. (n.d.). Towards Semantometrics: A New Semantic Similarity Based Measure for Assessing a Research Publication’s Contribution. D-Lib Magazine, 20(11/12), 8. https://doi.org/10.1045/november14-knoth

Koole, S. L., & Lakens, D. (2012). Rewarding Replications: A Sure and Simple Way to Improve Psychological Science. Perspectives on Psychological Science, 7(6), 608–614. https://doi.org/10.1177/1745691612462586

Kreuter, F. (Ed.). (2013). Improving Surveys with Paradata: Analytic Uses of Process Information. John Wiley & Sons, Inc. https://doi.org/10.1002/9781118596869

Kruschke, J. K. (2015). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan (2nd ed.). Academic Press.

Kuhn, T. S. (1996). The structure of scientific revolutions (3rd ed). University of Chicago Press.

Kukull, W. A., & Ganguli, M. (2012). Generalizability: The trees, the forest, and the low-hanging fruit. Neurology, 78(23), 1886–1891. https://doi.org/10.1212/WNL.0b013e318258f812

L. Haven, T., & Van Grootel, Dr. L. (2019). Preregistering qualitative research. Accountability in Research, 26(3), 229–244. https://doi.org/10.1080/08989621.2019.1580147

Laakso, M., & Björk, B.-C. (2013). Delayed open access: An overlooked high-impact category of openly available scientific literature. Journal of the American Society for Information Science and Technology, 64(7), 1323–1329. https://doi.org/10.1002/asi.22856

Laine, H. (2017). Afraid of Scooping – Case Study on Researcher Strategies against Fear of Scooping in the Context of Open Science. Data Science Journal, 16, 29. https://doi.org/10.5334/dsj-2017-029

Lakatos, I. (1978). The Methodology of Scientific Research Programs: Vol. I. Cambridge University Press.

Lakens, D. (2014). Performing high-powered studies efficiently with sequential analyses: Sequential analyses. European Journal of Social Psychology, 44(7), 701–710. https://doi.org/10.1002/ejsp.2023

Lakens, D. (2020a, May 11). The 20% Statistician: Red Team Challenge. The 20% Statistician. http://daniellakens.blogspot.com/2020/05/red-team-challenge.html

Lakens, D. (2020b). Pandemic researchers—Recruit your own best critics. Nature, 581(7807), 121–121. https://doi.org/10.1038/d41586-020-01392-8

Lakens, D. (2021a). Sample Size Justification [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/9d3yf

Lakens, D. (2021b). The Practical Alternative to the p Value Is the Correctly Used p Value. Perspectives on Psychological Science, 16(3), 639–648. https://doi.org/10.1177/1745691620958012

Lakens, D., McLatchie, N., Isager, P. M., Scheel, A. M., & Dienes, Z. (2020). Improving Inferences About Null Effects With Bayes Factors and Equivalence Tests. The Journals of Gerontology: Series B, 75(1), 45–57. https://doi.org/10.1093/geronb/gby065

Lakens, D., Scheel, A. M., & Isager, P. M. (2018). Equivalence Testing for Psychological Research: A Tutorial. Advances in Methods and Practices in Psychological Science, 1(2), 259–269. https://doi.org/10.1177/2515245918770963

Largent, E. A., & Snodgrass, R. T. (2016). Blind Peer Review by Academic Journals. In Blinding as a Solution to Bias (pp. 75–95). Elsevier. https://doi.org/10.1016/B978-0-12-802460-7.00005-X

Larivière, V., Desrochers, N., Macaluso, B., Mongeon, P., Paul-Hus, A., & Sugimoto, C. R. (2016). Contributorship and division of labor in knowledge production. Social Studies of Science, 46(3), 417–435. https://doi.org/10.1177/0306312716650046

Lazic, S. E. (2019, September 16). Genuine replication and pseudoreplication: What’s the difference? | BMJ Open Science. BMJ Open Science. https://blogs.bmj.com/openscience/2019/09/16/genuine-replication-and-pseudoreplication-whats-the-difference/

Leavens, D. A., Bard, K. A., & Hopkins, W. D. (2010). BIZARRE chimpanzees do not represent “the chimpanzee”. Behavioral and Brain Sciences, 33(2–3), 100–101. https://doi.org/10.1017/S0140525X10000166

Leavy, P. (2017). Research design: Quantitative, qualitative, mixed methods, arts-based, and community-based participatory research approaches. Guilford Press.

LeBel, E. P., McCarthy, R. J., Earp, B. D., Elson, M., & Vanpaemel, W. (2018). A Unified Framework to Quantify the Credibility of Scientific Findings. Advances in Methods and Practices in Psychological Science, 1(3), 389–402. https://doi.org/10.1177/2515245918787489

LeBel, E. P., Vanpaemel, W., Cheung, I., & Campbell, L. (2019). A Brief Guide to Evaluate Replications. Meta-Psychology, 3. https://doi.org/10.15626/MP.2018.843

Ledgerwood, A., Hudson, S. T. J., Lewis, N. A., Maddox, K. B., Pickett, C., Remedios, J. D., Cheryan, S., Diekman, A., Dutra, N. B., Goh, J. X., Goodwin, S., Munakata, Y., Navarro, D., Onyeador, I. N., Srivastava, S., & Wilkins, C. L. (2021). The Pandemic as a Portal: Reimagining Psychological Science as Truly Open and Inclusive [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/gdzue

Lee, R. M. (1993). Doing research on sensitive topics. Sage Publications.

Lewandowsky, S., & Bishop, D. (2016). Research integrity: Don’t let transparency damage science. Nature, 529(7587), 459–461. https://doi.org/10.1038/529459a

Lewandowsky, S., & Oberauer, K. (2021). Worldview-motivated rejection of science and the norms of science. Cognition, 215, 104820. https://doi.org/10.1016/j.cognition.2021.104820

Licenses & Standards | Open Source Initiative. (n.d.). Open Source Initative. Retrieved 9 July 2021, from https://opensource.org/licenses

Lin, D., Crabtree, J., Dillo, I., Downs, R. R., Edmunds, R., Giaretta, D., De Giusti, M., L’Hours, H., Hugo, W., Jenkyns, R., Khodiyar, V., Martone, M. E., Mokrane, M., Navale, V., Petters, J., Sierman, B., Sokolova, D. V., Stockhause, M., & Westbrook, J. (2020). The TRUST Principles for digital repositories. Scientific Data, 7(1), 144. https://doi.org/10.1038/s41597-020-0486-7

Lind, F., Gruber, M., & Boomgaarden, H. G. (2017). Content Analysis by the Crowd: Assessing the Usability of Crowdsourcing for Coding Latent Constructs. Communication Methods and Measures, 11(3), 191–209. https://doi.org/10.1080/19312458.2017.1317338

Lindsay, D. S. (2015). Replication in Psychological Science. Psychological Science, 26(12), 1827–1832. https://doi.org/10.1177/0956797615616374

Lindsay, D. S. (2020). Seven steps toward transparency and replicability in psychological science. Canadian Psychology/Psychologie Canadienne, 61(4), 310–317. https://doi.org/10.1037/cap0000222

Lintott, C. J., Schawinski, K., Slosar, A., Land, K., Bamford, S., Thomas, D., Raddick, M. J., Nichol, R. C., Szalay, A., Andreescu, D., Murray, P., & Vandenberg, J. (2008). Galaxy Zoo: Morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey ^★. Monthly Notices of the Royal Astronomical Society, 389(3), 1179–1189. https://doi.org/10.1111/j.1365-2966.2008.13689.x

Liu, H., & Priest, S. (2009). Understanding public support for stem cell research: Media communication, interpersonal communication and trust in key actors. Public Understanding of Science, 18(6), 704–718. https://doi.org/10.1177/0963662508097625

Liu, Y., Gordon, M., Wang, J., Bishop, M., Chen, Y., Pfeiffer, T., Twardy, C., & Viganola, D. (2020). Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication. ArXiv:2005.04543 [Cs]. http://arxiv.org/abs/2005.04543

Longino, H. E. (1990). Science as social knowledge: Values and objectivity in scientific inquiry. Princeton University Press.

Longino, H. E. (1992). Taking Gender Seriously in Philosophy of Science. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 1992(2), 333–340. https://doi.org/10.1086/psaprocbienmeetp.1992.2.192847

Lu, J., Qiu, Y., & Deng, A. (2019). A note on Type S/M errors in hypothesis testing. British Journal of Mathematical and Statistical Psychology, 72(1), 1–17. https://doi.org/10.1111/bmsp.12132

Lüdtke, O., Ulitzsch, E., & Robitzsch, A. (2020). A Comparison of Penalized Maximum Likelihood Estimation and Markov Chain Monte Carlo Techniques for Estimating Confirmatory Factor Analysis Models with Small Sample Sizes [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/u3qag

Lutz, M. (2019). Programming Python (Fourth edition). O’Reilly.

Lynch, Jr., J. G. (1982). On the External Validity of Experiments in Consumer Research. Journal of Consumer Research, 9(3), 225. https://doi.org/10.1086/208919

Macfarlane, B., & Cheng, M. (2008). Communism, Universalism and Disinterestedness: Re-examining Contemporary Support among Academics for Merton’s Scientific Norms. Journal of Academic Ethics, 6(1), 67–78. https://doi.org/10.1007/s10805-008-9055-y

Makowski, D., Ben-Shachar, M. S., Chen, S. H. A., & Lüdecke, D. (2019). Indices of Effect Existence and Significance in the Bayesian Framework. Frontiers in Psychology, 10, 2767. https://doi.org/10.3389/fpsyg.2019.02767

Martinez-Acosta, V. G., & Favero, C. B. (2018). A Discussion of Diversity and Inclusivity at the Institutional Level: The Need for a Strategic Plan. Journal of Undergraduate Neuroscience Education: JUNE: A Publication of FUN, Faculty for Undergraduate Neuroscience, 16(3), A252–A260.

Marwick, B., Boettiger, C., & Mullen, L. (2018). Packaging Data Analytical Work Reproducibly Using R (and Friends). The American Statistician, 72(1), 80–88. https://doi.org/10.1080/00031305.2017.1375986

Masur, P. K. (2020). Understanding the Effects of Analytical Choices on Finding the Privacy Paradox: A Specification Curve Analysis of Large-Scale Survey Data [Preprint]. Open Science Framework. https://osf.io/m72gb/

McElreath, R. (2020). Statistical rethinking: A Bayesian course with examples in R and Stan (2nd ed.). Taylor and Francis, CRC Press.

McNutt, M. K., Bradford, M., Drazen, J. M., Hanson, B., Howard, B., Jamieson, K. H., Kiermer, V., Marcus, E., Pope, B. K., Schekman, R., Swaminathan, S., Stang, P. J., & Verma, I. M. (2018). Transparency in authors’ contributions and responsibilities to promote integrity in scientific publication. Proceedings of the National Academy of Sciences, 115(11), 2557–2560. https://doi.org/10.1073/pnas.1715374115

Medical Research Centre. (2019). Identifiability, anonymisation and pseudonymisation. Medical Research Centre. https://mrc.ukri.org/documents/pdf/gdpr-guidance-note-5-identifiability-anonymisation-and-pseudonymisation/

Medin, D. L. (2012, February 1). Rigor Without Rigor Mortis: The APS Board Discusses Research Integrity [Blog]. Association for Psychological Science. https://www.psychologicalscience.org/observer/scientific-rigor

Melissa S. Anderson, Emily A. Ronning, Raymond De Vries, & Brian C. Martinson. (2010). Extending the Mertonian Norms: Scientists’ Subscription to Norms of Research. The Journal of Higher Education, 81(3), 366–393. https://doi.org/10.1353/jhe.0.0095

Mellers, B., Hertwig, R., & Kahneman, D. (2001). Do Frequency Representations Eliminate Conjunction Effects? An Exercise in Adversarial Collaboration. Psychological Science, 12(4), 269–275. https://doi.org/10.1111/1467-9280.00350

Menke, C. (2015). A Note on Science and Democracy? Robert K. Mertons Ethos of Science. In R. Klausnitzer, C. Spoerhase, & D. Werle (Eds.), Ethos und Pathos der Geisteswissenschaften. DE GRUYTER. https://doi.org/10.1515/9783110375008-013

Mertens, G., & Krypotos, A.-M. (2019). Preregistration of Analyses of Preexisting Data. Psychologica Belgica, 59(1), 338–352. https://doi.org/10.5334/pb.493

Merton, R. K. (1938). Science and the Social Order. Philosophy of Science, 5(3), 321–337. https://doi.org/10.1086/286513

Merton, R. K. (1968). The Matthew Effect in Science: The reward and communication systems of science are considered. Science, 159(3810), 56–63. https://doi.org/10.1126/science.159.3810.56

Meslin, E. M. (2008). Achieving global justice in health through global research ethics: Supplementing Macklin’s ‘top-down’ approach with one from the ‘ground up’. In R. M. Green, A. Donovan, & S. A. Jauss (Eds.), Global bioethics: Issues of conscience for the twenty-first century (pp. 163–177). Clarendon Press ; Oxford University Press.

Michener, W. K. (2015). Ten Simple Rules for Creating a Good Data Management Plan. PLOS Computational Biology, 11(10), e1004525. https://doi.org/10.1371/journal.pcbi.1004525

Mischel, W. (2009, January 1). Becoming a Cumulative Science. Association for Psychological Science. https://www.psychologicalscience.org/observer/becoming-a-cumulative-science

Moher, D., Bouter, L., Kleinert, S., Glasziou, P., Sham, M. H., Barbour, V., Coriat, A.-M., Foeger, N., & Dirnagl, U. (2020). The Hong Kong Principles for assessing researchers: Fostering research integrity. PLOS Biology, 18(7), e3000737. https://doi.org/10.1371/journal.pbio.3000737

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097

Moher, D., Naudet, F., Cristea, I. A., Miedema, F., Ioannidis, J. P. A., & Goodman, S. N. (2018). Assessing scientists for hiring, promotion, and tenure. PLOS Biology, 16(3), e2004089. https://doi.org/10.1371/journal.pbio.2004089

Monroe, K. R. (2018). The Rush to Transparency: DA-RT and the Potential Dangers for Qualitative Research. Perspectives on Politics, 16(1), 141–148. https://doi.org/10.1017/S153759271700336X

Morabia, A., Have, T. T., & Landis, J. R. (1997). Interaction Fallacy. Journal of Clinical Epidemiology, 50(7), 809–812. https://doi.org/10.1016/S0895-4356(97)00053-X

Moran, H., Karlin, L., Lauchlan, E., Rappaport, S. J., Bleasdale, B., Wild, L., & Dorr, J. (2020). Understanding Research Culture: What researchers think about the culture they work in. Wellcome Open Research, 5, 201. https://doi.org/10.12688/wellcomeopenres.15832.1

Moretti, M. (2020, August 12). Beyond Open-washing: Are Narratives the Future of Open Data Portals? | by matteo moretti | Nightingale | Medium. Nightingale. https://medium.com/nightingale/beyond-open-washing-are-stories-and-narratives-the-future-of-open-data-portals-93228d8882f3

Morey, R. D., Chambers, C. D., Etchells, P. J., Harris, C. R., Hoekstra, R., Lakens, D., Lewandowsky, S., Morey, C. C., Newman, D. P., Schönbrodt, F. D., Vanpaemel, W., Wagenmakers, E.-J., & Zwaan, R. A. (2016). The Peer Reviewers’ Openness Initiative: Incentivizing open research practices through peer review. Royal Society Open Science, 3(1), 150547. https://doi.org/10.1098/rsos.150547

Morgan, C. (1998). The DOI (Digital Object Identifier). Serials: The Journal for the Serials Community, 11(1), 47–51. https://doi.org/10.1629/1147

Moshontz, H., Campbell, L., Ebersole, C. R., IJzerman, H., Urry, H. L., Forscher, P. S., Grahe, J. E., McCarthy, R. J., Musser, E. D., Antfolk, J., Castille, C. M., Evans, T. R., Fiedler, S., Flake, J. K., Forero, D. A., Janssen, S. M. J., Keene, J. R., Protzko, J., Aczel, B., … Chartier, C. R. (2018). The Psychological Science Accelerator: Advancing Psychology Through a Distributed Collaborative Network. Advances in Methods and Practices in Psychological Science, 1(4), 501–515. https://doi.org/10.1177/2515245918797607

Moshontz, H., Ebersole, C. R., Weston, S. J., & Klein, R. A. (2021). A guide for many authors: Writing manuscripts in large collaborations. Social and Personality Psychology Compass, 15(4). https://doi.org/10.1111/spc3.12590

Mourby, M., Mackey, E., Elliot, M., Gowans, H., Wallace, S. E., Bell, J., Smith, H., Aidinlis, S., & Kaye, J. (2018). Are ‘pseudonymised’ data always personal data? Implications of the GDPR for administrative data research in the UK. Computer Law & Security Review, 34(2), 222–233. https://doi.org/10.1016/j.clsr.2018.01.002

Muller, J. Z. (2018). The tyranny of metrics. Princeton University Press.

Munn, Z., Peters, M. D. J., Stern, C., Tufanaru, C., McArthur, A., & Aromataris, E. (2018). Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology, 18(1), 143. https://doi.org/10.1186/s12874-018-0611-x

Muthukrishna, M., Bell, A. V., Henrich, J., Curtin, C. M., Gedranovich, A., McInerney, J., & Thue, B. (2020). Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance. Psychological Science, 31(6), 678–701. https://doi.org/10.1177/0956797620916782

Naudet, F., Ioannidis, J. P. A., Miedema, F., Cristea, I. A., Goodman, Steven N., J., & Moher, D. (2018, June 4). Six principles for assessing scientists for hiring, promotion, and tenure. Impact of Social Sciences Blog. http://eprints.lse.ac.uk/90753/

Navarro, D. (2020). Paths in strange spaces: A comment on preregistration [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/wxn58

Nelson, L. D., Simmons, J. P., & Simonsohn, U. (2012). Let’s Publish Fewer Papers. Psychological Inquiry, 23(3), 291–293. https://doi.org/10.1080/1047840X.2012.705245

Neuroskeptic. (2012). The Nine Circles of Scientific Hell. Perspectives on Psychological Science, 7(6), 643–644. https://doi.org/10.1177/1745691612459519

Nichols, T. E., Das, S., Eickhoff, S. B., Evans, A. C., Glatard, T., Hanke, M., Kriegeskorte, N., Milham, M. P., Poldrack, R. A., Poline, J.-B., Proal, E., Thirion, B., Van Essen, D. C., White, T., & Yeo, B. T. T. (2017). Best practices in data analysis and sharing in neuroimaging using MRI. Nature Neuroscience, 20(3), 299–303. https://doi.org/10.1038/nn.4500

Nickerson, R. S. (1998). Confirmation Bias: A Ubiquitous Phenomenon in Many Guises. Review of General Psychology, 2(2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175

Nieuwenhuis, S., Forstmann, B. U., & Wagenmakers, E.-J. (2011). Erroneous analyses of interactions in neuroscience: A problem of significance. Nature Neuroscience, 14(9), 1105–1107. https://doi.org/10.1038/nn.2886

Nimon, K. F. (2012). Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review. Frontiers in Psychology, 3. https://doi.org/10.3389/fpsyg.2012.00322

Nisbet, M. C., Scheufele, D. A., Shanahan, J., Moy, P., Brossard, D., & Lewenstein, B. V. (2002). Knowledge, Reservations, or Promise?: A Media Effects Model for Public Perceptions of Science and Technology. Communication Research, 29(5), 584–608. https://doi.org/10.1177/009365002236196

Nittrouer, C. L., Hebl, M. R., Ashburn-Nardo, L., Trump-Steele, R. C. E., Lane, D. M., & Valian, V. (2018). Gender disparities in colloquium speakers at top universities. Proceedings of the National Academy of Sciences, 115(1), 104–108. https://doi.org/10.1073/pnas.1708414115

Nosek, B. A. (2019, June 11). Strategy for Culture Change. Center for Open Science. https://www.cos.io/blog/strategy-for-culture-change

Nosek, B. A., & Bar-Anan, Y. (2012). Scientific Utopia: I. Opening Scientific Communication. Psychological Inquiry, 23(3), 217–243. https://doi.org/10.1080/1047840X.2012.692215

Nosek, B. A., Ebersole, C. R., DeHaven, A. C., & Mellor, D. T. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences, 115(11), 2600–2606. https://doi.org/10.1073/pnas.1708274114

Nosek, B. A., & Errington, T. M. (2020). What is replication? PLOS Biology, 18(3), e3000691. https://doi.org/10.1371/journal.pbio.3000691

Nosek, B. A., & Lakens, D. (2014). Registered Reports: A Method to Increase the Credibility of Published Results. Social Psychology, 45(3), 137–141. https://doi.org/10.1027/1864-9335/a000192

Nosek, B. A., Spies, J. R., & Motyl, M. (2012). Scientific Utopia: II. Restructuring Incentives and Practices to Promote Truth Over Publishability. Perspectives on Psychological Science, 7(6), 615–631. https://doi.org/10.1177/1745691612459058

Noy, N. F., & Guinness, D. L. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report  KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880. https://protege.stanford.edu/publications/ontology_development/ontology101.pdf

Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2016). The prevalence of statistical reporting errors in psychology (1985–2013). Behavior Research Methods, 48(4), 1205–1226. https://doi.org/10.3758/s13428-015-0664-2

Nüst, D., Boettiger, C., & Marwick, B. (2018). How to Read a Research Compendium. ArXiv:1806.09525 [Cs]. http://arxiv.org/abs/1806.09525

Obels, P., Lakens, D., Coles, N. A., Gottfried, J., & Green, S. A. (2020). Analysis of Open Data and Computational Reproducibility in Registered Reports in Psychology. Advances in Methods and Practices in Psychological Science, 3(2), 229–237. https://doi.org/10.1177/2515245920918872

Oberauer, K., & Lewandowsky, S. (2019). Addressing the theory crisis in psychology. Psychonomic Bulletin & Review, 26(5), 1596–1618. https://doi.org/10.3758/s13423-019-01645-2

OER Commons. (n.d.). OER Commons. Retrieved 9 July 2021, from https://www.oercommons.org/

Open Aire. (n.d.). Amnesia Anonymization Tool—Data anonymization made easy. High Accuracy Data Anonymisation. Retrieved 9 July 2021, from https://amnesia.openaire.eu/

Open Educational Resources (OER). (2017, July 20). UNESCO. https://en.unesco.org/themes/building-knowledge-societies/oer

Open Scholarship Knowledge Base | OER Commons. (n.d.). OER Commons. Retrieved 9 July 2021, from https://www.oercommons.org/hubs/OSKB

Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716–aac4716. https://doi.org/10.1126/science.aac4716

Open Source in Open Science | FOSTER. (n.d.). Foster. Retrieved 9 July 2021, from https://www.fosteropenscience.eu/foster-taxonomy/open-source-open-science

Orben, A. (2019). A journal club to fix science. Nature, 573(7775), 465–465. https://doi.org/10.1038/d41586-019-02842-8

ORCID. (n.d.). ORCID. Retrieved 9 July 2021, from https://orcid.org/

OSF. (n.d.). Open Science Framework. Retrieved 9 July 2021, from https://osf.io/

OSF | StudySwap: A platform for interlab replication, collaboration, and research resource exchange. (n.d.). Retrieved 10 July 2021, from https://osf.io/meetings/StudySwap/

Ottmann, G., Laragy, C., Allen, J., & Feldman, P. (2011). Coproduction in Practice: Participatory Action Research to Develop a Model of Community Aged Care. Systemic Practice and Action Research, 24(5), 413–427. https://doi.org/10.1007/s11213-011-9192-x

Our Approach | Co-Production Collective. (n.d.). Co-Production Collective. Retrieved 9 July 2021, from https://www.coproductioncollective.co.uk/what-is-co-production/our-approach

Padilla, A. M. (1994). Research news and Comment: Ethnic Minority Scholars; Research, and Mentoring: Current and Future Issues. Educational Researcher, 23(4), 24–27. https://doi.org/10.3102/0013189X023004024

Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … McKenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ, n160. https://doi.org/10.1136/bmj.n160

Patience, G. S., Galli, F., Patience, P. A., & Boffito, D. C. (2019). Intellectual contributions meriting authorship: Survey results from the top cited authors across all science categories. PLOS ONE, 14(1), e0198117. https://doi.org/10.1371/journal.pone.0198117

Pautasso, M. (2013). Ten Simple Rules for Writing a Literature Review. PLoS Computational Biology, 9(7), e1003149. https://doi.org/10.1371/journal.pcbi.1003149

Pavlov, Y. G., Adamian, N., Appelhoff, S., Arvaneh, M., Benwell, C., Beste, C., Bland, A., Bradford, D. E., Bublatzky, F., Busch, N., Clayson, P. E., Cruse, D., Czeszumski, A., Dreber, A., Dumas, G., Ehinger, B. V., Ganis, G., He, X., Hinojosa, J. A., … Mushtaq, F. (2020). #EEGManyLabs: Investigating the Replicability of Influential EEG Experiments [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/528nr

PCI Registered Reports. (n.d.). PCI. Retrieved 9 July 2021, from https://rr.peercommunityin.org/about/about

Peer Community In – A free recommendation process of scientific preprints based on peer-reviews. (n.d.). Retrieved 9 July 2021, from https://peercommunityin.org/

Peer, E., Brandimarte, L., Samat, S., & Acquisti, A. (2017). Beyond the Turk: Alternative platforms for crowdsourcing behavioral research. Journal of Experimental Social Psychology, 70, 153–163. https://doi.org/10.1016/j.jesp.2017.01.006

Peng, R. D. (2011). Reproducible Research in Computational Science. Science, 334(6060), 1226–1227. https://doi.org/10.1126/science.1213847

Percie du Sert, N., Hurst, V., Ahluwalia, A., Alam, S., Avey, M. T., Baker, M., Browne, W. J., Clark, A., Cuthill, I. C., Dirnagl, U., Emerson, M., Garner, P., Holgate, S. T., Howells, D. W., Karp, N. A., Lazic, S. E., Lidster, K., MacCallum, C. J., Macleod, M., … Würbel, H. (2020). The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLOS Biology, 18(7), e3000410. https://doi.org/10.1371/journal.pbio.3000410

Pernet, C. (2016). Null hypothesis significance testing: A short tutorial. F1000Research, 4, 621. https://doi.org/10.12688/f1000research.6963.3

Pernet, C., Garrido, M. I., Gramfort, A., Maurits, N., Michel, C. M., Pang, E., Salmelin, R., Schoffelen, J. M., Valdes-Sosa, P. A., & Puce, A. (2020). Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research. Nature Neuroscience, 23(12), 1473–1483. https://doi.org/10.1038/s41593-020-00709-0

Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., & Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6(1), 103. https://doi.org/10.1038/s41597-019-0104-8

Peterson, D., & Panofsky, A. (2020). Metascience as a scientific social movement [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/4dsqa

Petre, M., & Wilson, G. (2014). Code Review For and By Scientists. ArXiv:1407.5648 [Cs]. http://arxiv.org/abs/1407.5648

‘Plan S’ and ‘cOAlition S’ – Accelerating the transition to full and immediate Open Access to scientific publications. (n.d.). Retrieved 9 July 2021, from https://www.coalition-s.org/

Poldrack, R. A., Barch, D. M., Mitchell, J. P., Wager, T. D., Wagner, A. D., Devlin, J. T., Cumba, C., Koyejo, O., & Milham, M. P. (2013). Toward open sharing of task-based fMRI data: The OpenfMRI project. Frontiers in Neuroinformatics, 7. https://doi.org/10.3389/fninf.2013.00012

Poldrack, R. A., & Gorgolewski, K. J. (2014). Making big data open: Data sharing in neuroimaging. Nature Neuroscience, 17(11), 1510–1517. https://doi.org/10.1038/nn.3818

Pollet, I. L., & Bond, A. L. (2021). Evaluation and recommendations for greater accessibility of colour figures in ornithology. Ibis, 163(1), 292–295. https://doi.org/10.1111/ibi.12887

Popper, K. (2010). The logic of scientific discovery (Special Indian Edition). Routledge.

Posselt, J. R. (2020). Equity in science: Representation, culture, and the dynamics of change in graduate education. Stanford University Press.

Pownall, M., Talbot, C. V., Henschel, A., Lautarescu, A., Lloyd, K., Hartmann, H., Darda, K. M., Tang, K. T. Y., Carmichael-Murphy, P., & Siegel, J. A. (2020). Navigating Open Science as Early Career Feminist Researchers [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/f9m47

Preregistration pledge. (n.d.). Google Docs. Retrieved 9 July 2021, from https://docs.google.com/forms/d/e/1FAIpQLSf8RflGizFJZamE874o8aDOhyU7UsNByR4dLmzhOtEOiu8KRQ/viewform?embedded=true&usp=embed_facebook

Press, W. (2007). Numerical recipes: The art of scientific computing, (3rd ed.). Cambridge University Press.

Psychological Science Accelerator. (n.d.). Psychological Science Accelerator. Retrieved 9 July 2021, from https://psysciacc.org/

Publication bias. (2019, May 2). Catalog of Bias. https://catalogofbias.org/biases/publication-bias/

PubPeer—Search publications and join the conversation. (n.d.). Pubpeer. Retrieved 9 July 2021, from https://www.pubpeer.com/

R: The R Project for Statistical Computing. (n.d.). R Project. Retrieved 10 July 2021, from https://www.r-project.org/

Rabagliati, H., Moors, P., & Heyman, T. (2020). Can Item Effects Explain Away the Evidence for Unconscious Sound Symbolism? An Adversarial Commentary on Heyman, Maerten, Vankrunkelsven, Voorspoels, and Moors (2019). Psychological Science, 31(9), 1200–1204. https://doi.org/10.1177/0956797620949461

Rakow, T., Thompson, V., Ball, L., & Markovits, H. (2015). Rationale and guidelines for empirical adversarial collaboration: A Thinking & Reasoning initiative. Thinking & Reasoning, 21(2), 167–175. https://doi.org/10.1080/13546783.2015.975405

Recommended Data Repositories | Scientific Data. (n.d.). Retrieved 10 July 2021, from https://www.nature.com/sdata/policies/repositories

Replication Markets – Reliable research replicates…you can bet on it. (n.d.). Retrieved 10 July 2021, from https://www.replicationmarkets.com/

ReproducibiliTea. (n.d.). ReproducibiliTea. Retrieved 10 July 2021, from https://reproducibilitea.org/

Retraction Watch. (n.d.). Retraction Watch. Retrieved 9 July 2021, from https://retractionwatch.com/

RIOT Science Club—Riot Science Club. (n.d.). Reproducible, Interpretable, Open, & Transparent Science. Retrieved 10 July 2021, from http://riotscience.co.uk/

Rogers, A., Castree, N., & Kitchin, R. (2013). Reflexivity. In A Dictionary of Human Geography. Oxford University Press. https://www.oxfordreference.com/view/10.1093/acref/9780199599868.001.0001/acref-9780199599868-e-1530

Rolls, L., & Relf, M. (2006). Bracketing interviews: Addressing methodological challenges in qualitative interviewing in bereavement and palliative care. Mortality, 11(3), 286–305. https://doi.org/10.1080/13576270600774893

Rose, D. (2000). Universal Design for Learning. Journal of Special Education Technology, 15(3), 45–49. https://doi.org/10.1177/016264340001500307

Rose, D. (2018). Participatory research: Real or imagined. Social Psychiatry and Psychiatric Epidemiology, 53(8), 765–771. https://doi.org/10.1007/s00127-018-1549-3

Rose, D. H., & Meyer, A. (2002). Teaching every student in the Digital Age: Universal design for learning. Association for Supervision and Curriculum Development.

Ross-Hellauer, T. (2017). What is open peer review? A systematic review. F1000Research, 6, 588. https://doi.org/10.12688/f1000research.11369.2

Rossner, M., Van Epps, H., & Hill, E. (2007). Show me the data. Journal of Cell Biology, 179(6), 1091–1092. https://doi.org/10.1083/jcb.200711140

Rothstein, H. R., Sutton, A. J., & Borenstein, M. (2006). Publication Bias in Meta-Analysis. In H. R. Rothstein, A. J. Sutton, & M. Borenstein (Eds.), Publication Bias in Meta-Analysis (pp. 1–7). John Wiley & Sons, Ltd. https://doi.org/10.1002/0470870168.ch1

Rowhani-Farid, A., Aldcroft, A., & Barnett, A. G. (2020). Did awarding badges increase data sharing in BMJ Open ? A randomized controlled trial. Royal Society Open Science, 7(3), 191818. https://doi.org/10.1098/rsos.191818

Rubin, M. (2021). Explaining the association between subjective social status and mental health among university students using an impact ratings approach. SN Social Sciences, 1(1), 20. https://doi.org/10.1007/s43545-020-00031-3

Rubin, M., Evans, O., & McGuffog, R. (2019). Social Class Differences in Social Integration at University: Implications for Academic Outcomes and Mental Health. In J. Jetten & K. Peters (Eds.), The Social Psychology of Inequality (pp. 87–102). Springer International Publishing. https://doi.org/10.1007/978-3-030-28856-3_6

Sagarin, B. J., Ambler, J. K., & Lee, E. M. (2014). An Ethical Approach to Peeking at Data. Perspectives on Psychological Science, 9(3), 293–304. https://doi.org/10.1177/1745691614528214

Salem, D. N., & Boumil, M. M. (2013). Conflict of Interest in Open-Access Publishing. New England Journal of Medicine, 369(5), 491–491. https://doi.org/10.1056/NEJMc1307577

Sato, T. (1996). Type I and Type II Error in Multiple Comparisons. The Journal of Psychology, 130(3), 293–302. https://doi.org/10.1080/00223980.1996.9915010

Schafersman, S. (1997, January). An Introduction to Science: Scientific Thinking and Scientific Method. An Introduction to Science. https://www.geo.sunysb.edu/esp/files/scientific-method.html

Schmidt, Robert. H. (1987). A Worksheet for Authorship of Scientific Articles on JSTOR. Bulletin of the Ecological Society of America, 68(1), 8–10. https://www.jstor.org/stable/20166549

Schneider, J., Merk, S., & Rosman, T. (2020). (Re)Building Trust? Investigating the effects of open science badges on perceived trustworthiness in journal articles. https://doi.org/10.17605/OSF.IO/VGBRS

Schönbrodt, F. (2019). Training students for the Open Science future. Nature Human Behaviour, 3(10), 1031–1031. https://doi.org/10.1038/s41562-019-0726-z

Schönbrodt, F. D., Wagenmakers, E.-J., Zehetleitner, M., & Perugini, M. (2017). Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences. Psychological Methods, 22(2), 322–339. https://doi.org/10.1037/met0000061

Schulz, K. F., & Grimes, D. A. (2005). Multiplicity in randomised trials I: Endpoints and treatments. The Lancet, 365(9470), 1591–1595. https://doi.org/10.1016/S0140-6736(05)66461-6

Schwarz, N., & Strack, F. (n.d.). Does merely going through the same moves make for a “direct” replication? Concepts, contexts, and operationalizations. Social Psychology, 45(4), 305–306.

Science. (n.d.). Open Science Badges. Centre for Open Science. https://www.cos.io/initiatives/badges

Scopatz, A., & Huff, K. D. (2015). Effective computation in physics (First Edition). O’Reilly Media.

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2001). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin.

Sharma, M., Sarin, A., Gupta, P., Sachdeva, S., & Desai, A. (2014). Journal Impact Factor: Its Use, Significance and Limitations. World Journal of Nuclear Medicine, 13(2), 146. https://doi.org/10.4103/1450-1147.139151

Shepard, B. (2015). Community practice as social activism: From direct action to direct services. SAGE Publications, Inc.

Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-Analyses, and Meta-Syntheses. Annual Review of Psychology, 70(1), 747–770. https://doi.org/10.1146/annurev-psych-010418-102803

Sijtsma, K. (2016). Playing with Data—Or How to Discourage Questionable Research Practices and Stimulate Researchers to Do Things Right. Psychometrika, 81(1), 1–15. https://doi.org/10.1007/s11336-015-9446-0

Silberzahn, R., Simonsohn, U., & Uhlmann, E. L. (2014). Matched-Names Analysis Reveals No Evidence of Name-Meaning Effects: A Collaborative Commentary on Silberzahn and Uhlmann (2013). Psychological Science, 25(7), 1504–1505. https://doi.org/10.1177/0956797614533802

Silberzahn, R., Uhlmann, E. L., Martin, D. P., Anselmi, P., Aust, F., Awtrey, E., Bahník, Š., Bai, F., Bannard, C., Bonnier, E., Carlsson, R., Cheung, F., Christensen, G., Clay, R., Craig, M. A., Dalla Rosa, A., Dam, L., Evans, M. H., Flores Cervantes, I., … Nosek, B. A. (2018). Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results. Advances in Methods and Practices in Psychological Science, 1(3), 337–356. https://doi.org/10.1177/2515245917747646

Simmons, J., Nelson, L., & Simonsohn, U. (2021). Pre‐registration: Why and How. Journal of Consumer Psychology, 31(1), 151–162. https://doi.org/10.1002/jcpy.1208

Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Psychological Science, 22(11), 1359–1366. https://doi.org/10.1177/0956797611417632

Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017). Constraints on Generality (COG): A Proposed Addition to All Empirical Papers. Perspectives on Psychological Science, 12(6), 1123–1128. https://doi.org/10.1177/1745691617708630

Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014a). P-curve: A key to the file-drawer. Journal of Experimental Psychology: General, 143(2), 534–547. https://doi.org/10.1037/a0033242

Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014b). p -Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results. Perspectives on Psychological Science, 9(6), 666–681. https://doi.org/10.1177/1745691614553988

Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2019). P-curve won’t do your laundry, but it will distinguish replicable from non-replicable findings in observational research: Comment on Bruns & Ioannidis (2016). PLOS ONE, 14(3), e0213454. https://doi.org/10.1371/journal.pone.0213454

Simonsohn, U., Simmons, J. P., & Nelson, L. D. (2015). Specification Curve: Descriptive and Inferential Statistics on All Reasonable Specifications. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2694998

Simonsohn, U., Simmons, J. P., & Nelson, L. D. (2020). Specification curve analysis. Nature Human Behaviour, 4(11), 1208–1214. https://doi.org/10.1038/s41562-020-0912-z

Smaldino, P. E., & McElreath, R. (2016). The natural selection of bad science. Royal Society Open Science, 3(9), 160384. https://doi.org/10.1098/rsos.160384

Smith, A. C., Merz, L., Borden, J. B., Gulick, C., Kshirsagar, A. R., & Bruna, E. M. (2020). Assessing the effect of article processing charges on the geographic diversity of authors using Elsevier’s ‘Mirror Journal’ system [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/s7cx4

Smith, A. J., Clutton, R. E., Lilley, E., Hansen, K. E. A., & Brattelid, T. (2018). PREPARE: Guidelines for planning animal research and testing. Laboratory Animals, 52(2), 135–141. https://doi.org/10.1177/0023677217724823

Smith, G. T. (2005). On Construct Validity: Issues of Method and Measurement. Psychological Assessment, 17(4), 396–408. https://doi.org/10.1037/1040-3590.17.4.396

Sorsa, M. A., Kiikkala, I., & Åstedt-Kurki, P. (2015). Bracketing as a skill in conducting unstructured qualitative interviews. Nurse Researcher, 22(4), 8–12. https://doi.org/10.7748/nr.22.4.8.e1317

SORTEE. (n.d.). SORTEE. SORTEE. Retrieved 10 July 2021, from https://www.sortee.org/

Spence, J. R., & Stanley, D. J. (2018). Concise, Simple, and Not Wrong: In Search of a Short-Hand Interpretation of Statistical Significance. Frontiers in Psychology, 9, 2185. https://doi.org/10.3389/fpsyg.2018.02185

Spencer, E. A., & Heneghan, C. (2018, April 2). Confirmation bias. Catalog of Bias. https://catalogofbias.org/biases/confirmation-bias/

Steckler, A., & McLeroy, K. R. (2008). The Importance of External Validity. American Journal of Public Health, 98(1), 9–10. https://doi.org/10.2105/AJPH.2007.126847

Steegen, S., Tuerlinckx, F., Gelman, A., & Vanpaemel, W. (2016). Increasing Transparency Through a Multiverse Analysis. Perspectives on Psychological Science, 11(5), 702–712. https://doi.org/10.1177/1745691616658637

Steup, M., & Neta, R. (2020). Epistemology. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Fall 2020). Metaphysics Research Lab, Stanford University. https://plato.stanford.edu/archives/fall2020/entries/epistemology/

Stewart, N., Chandler, J., & Paolacci, G. (2017). Crowdsourcing Samples in Cognitive Science. Trends in Cognitive Sciences, 21(10), 736–748. https://doi.org/10.1016/j.tics.2017.06.007

Stodden, V. C. (2011). Trust Your Science? Open Your Data and Code. https://doi.org/10.7916/D8CJ8Q0P

Strathern, M. (1997). ‘Improving ratings’: Audit in the British University system. European Review, 5(3), 305–321. https://doi.org/10.1002/(SICI)1234-981X(199707)5:3<305::AID-EURO184>3.0.CO;2-4

Suber, P. (2004, February 4). It’s the authors, stupid! SPARC Open Access Newsletter. https://dash.harvard.edu/bitstream/handle/1/4391161/suber_authors.htm?sequence=1&isAllowed=y

SwissRN. (n.d.). Retrieved 10 July 2021, from http://www.swissrn.org/

Syed, M. (2019). The Open Science Movement is For All of Us [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/cteyb

Syed, M., & Kathawalla, U.-K. (2020). Cultural Psychology, Diversity, and Representation in Open Science [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/t7hp2

Szollosi, A., & Donkin, C. (2021). Arrested Theory Development: The Misguided Distinction Between Exploratory and Confirmatory Research. Perspectives on Psychological Science, 174569162096679. https://doi.org/10.1177/1745691620966796

Team, psyTeachR. (n.d.). P | Glossary. Retrieved 9 July 2021, from https://psyteachr.github.io/glossary

Tennant, J., Beamer, J. E., Bosman, J., Brembs, B., Chung, N. C., Clement, G., Crick, T., Dugan, J., Dunning, A., Eccles, D., Enkhbayar, A., Graziotin, D., Harding, R., Havemann, J., Katz, D. S., Khanal, K., Kjaer, J. N., Koder, T., Macklin, P., … Turner, A. (2019). Foundations for Open Scholarship Strategy Development [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/b4v8p

Tennant, J., Bielczyk, N. Z., Greshake Tzovaras, B., Masuzzo, P., & Steiner, T. (2019). Introducing Massively Open Online Papers (MOOPs) [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/et8ak

Tenny, S., & Abdelgawad, I. (2021). Statistical Significance. In StatPearls [Internet]. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK459346/

The Committee on Publication Ethics. (n.d.). Transparency & best practice – DOAJ. DOAJ. https://doaj.org/apply/transparency/

the CONSORT Group, Schulz, K. F., Altman, D. G., & Moher, D. (2010). CONSORT 2010 Statement: Updated guidelines for reporting parallel group randomised trials. Trials, 11(1), 32. https://doi.org/10.1186/1745-6215-11-32

The European Code of Conduct for Research Integrity | ALLEA. (n.d.). Retrieved 10 July 2021, from https://allea.org/code-of-conduct/

The Open Definition—Open Definition—Defining Open in Open Data, Open Content and Open Knowledge. (n.d.). Open Knowledge Foundation. Retrieved 9 July 2021, from https://opendefinition.org/

The Open Source Definition | Open Source Initiative. (n.d.). Open Source Initative. Retrieved 9 July 2021, from https://opensource.org/osd

The Slow Science Academy. (2010). The Slow Science Manifesto. SLOW-SCIENCE.Org — Bear with Us, While We Think. http://slow-science.org/

Thombs, B. D., Levis, A. W., Razykov, I., Syamchandra, A., Leentjens, A. F. G., Levenson, J. L., & Lumley, M. A. (2015). Potentially coercive self-citation by peer reviewers: A cross-sectional study. Journal of Psychosomatic Research, 78(1), 1–6. https://doi.org/10.1016/j.jpsychores.2014.09.015

Tierney, W., Hardy, J., Ebersole, C. R., Viganola, D., Clemente, E. G., Gordon, M., Hoogeveen, S., Haaf, J., Dreber, A., Johannesson, M., Pfeiffer, T., Huang, J. L., Vaughn, L. A., DeMarree, K., Igou, E. R., Chapman, H., Gantman, A., Vanaman, M., Wylie, J., … Uhlmann, E. L. (2021). A creative destruction approach to replication: Implicit work and sex morality across cultures. Journal of Experimental Social Psychology, 93, 104060. https://doi.org/10.1016/j.jesp.2020.104060

Tierney, W., Hardy, J. H., Ebersole, C. R., Leavitt, K., Viganola, D., Clemente, E. G., Gordon, M., Dreber, A., Johannesson, M., Pfeiffer, T., & Uhlmann, E. L. (2020). Creative destruction in science. Organizational Behavior and Human Decision Processes, 161, 291–309. https://doi.org/10.1016/j.obhdp.2020.07.002

Tiokhin, L., Yan, M., & Morgan, T. J. H. (2021). Competition for priority harms the reliability of science, but reforms can help. Nature Human Behaviour. https://doi.org/10.1038/s41562-020-01040-1

Topor, M., Pickering, J. S., Barbosa Mendes, A., Bishop, D. V. M., Büttner, F. C., Elsherif, M. M., Evans, T. R., Henderson, E. L., Kalandadze, T., Nitschke, F. T., Staaks, J., Van den Akker, O., Yeung, S. K., Zaneva, M., Lam, A., Madan, C. R., Moreau, D., O’Mahony, A., Parker, A. J., … Westwood, S. J. (2020). An integrative framework for planning and conducting Non-Intervention, Reproducible, and Open Systematic Reviews (NIRO-SR) [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/8gu5z

Transparency: The Emerging Third Dimension of Open Science and Open Data. (2016). LIBER QUARTERLY, 25(4), 153–171. https://doi.org/10.18352/lq.10113

Tscharntke, T., Hochberg, M. E., Rand, T. A., Resh, V. H., & Krauss, J. (2007). Author Sequence and Credit for Contributions in Multiauthored Publications. PLoS Biology, 5(1), e18. https://doi.org/10.1371/journal.pbio.0050018

Tufte, E. R. (2001). The visual display of quantitative information (2nd ed). Graphics Press.

Tukey, J. W. (1977). Exploratory data analysis. Addison-Wesley Pub. Co.

Tvina, A., Spellecy, R., & Palatnik, A. (2019). Bias in the Peer Review Process: Can We Do Better? Obstetrics & Gynecology, 133(6), 1081–1083. https://doi.org/10.1097/AOG.0000000000003260

Uhlmann, E. L., Ebersole, C. R., Chartier, C. R., Errington, T. M., Kidwell, M. C., Lai, C. K., McCarthy, R. J., Riegelman, A., Silberzahn, R., & Nosek, B. A. (2019). Scientific Utopia III: Crowdsourcing Science. Perspectives on Psychological Science, 14(5), 711–733. https://doi.org/10.1177/1745691619850561

UK Reproducibility Network. (n.d.). UK Reproducibility Network. Retrieved 10 July 2021, from https://www.ukrn.org/

University of Illinois at Urbana-Champaign, Burnette, M., Williams, S., University of Illinois at Urbana-Champaign, Imker, H., & University of Illinois at Urbana-Champaign. (2016). From Plan to Action: Successful Data Management Plan Implementation in a Multidisciplinary Project. Journal of EScience Librarianship, 5(1), e1101. https://doi.org/10.7191/jeslib.2016.1101

van de Schoot, R., Depaoli, S., King, R., Kramer, B., Märtens, K., Tadesse, M. G., Vannucci, M., Gelman, A., Veen, D., Willemsen, J., & Yau, C. (2021). Bayesian statistics and modelling. Nature Reviews Methods Primers, 1(1), 1. https://doi.org/10.1038/s43586-020-00001-2

Vazire, S. (2018). Implications of the Credibility Revolution for Productivity, Creativity, and Progress. Perspectives on Psychological Science, 13(4), 411–417. https://doi.org/10.1177/1745691617751884

Vazire, S., Schiavone, S. R., & Bottesini, J. G. (2020). Credibility Beyond Replicability: Improving the Four Validities in Psychological Science [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/bu4d3

Villum, C. (2014, March 10). “Open-washing” – The difference between opening your data and simply making them available – Open Knowledge Foundation blog. Open Knowledge Foundation. https://blog.okfn.org/2014/03/10/open-washing-the-difference-between-opening-your-data-and-simply-making-them-available/

Vlaeminck, S., & Podkrajac, F. (2017). Journals in Economic Sciences: Paying Lip Service to Reproducible Research? IASSIST Quarterly, 41(1–4), 16. https://doi.org/10.29173/iq6

Voracek, M., Kossmeier, M., & Tran, U. S. (2019). Which Data to Meta-Analyze, and How?: A Specification-Curve and Multiverse-Analysis Approach to Meta-Analysis. Zeitschrift Für Psychologie, 227(1), 64–82. https://doi.org/10.1027/2151-2604/a000357

Vuorre, M., & Curley, J. P. (2018). Curating Research Assets: A Tutorial on the Git Version Control System. Advances in Methods and Practices in Psychological Science, 1(2), 219–236. https://doi.org/10.1177/2515245918754826

Wacker, J. G. (1998). A definition of theory: Research guidelines for different theory-building research methods in operations management. Journal of Operations Management, 16(4), 361–385. https://doi.org/10.1016/S0272-6963(98)00019-9

Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35–57. https://doi.org/10.3758/s13423-017-1343-3

Wagenmakers, E.-J., Wetzels, R., Borsboom, D., van der Maas, H. L. J., & Kievit, R. A. (2012). An Agenda for Purely Confirmatory Research. Perspectives on Psychological Science, 7(6), 632–638. https://doi.org/10.1177/1745691612463078

Wagge, J. R., Baciu, C., Banas, K., Nadler, J. T., Schwarz, S., Weisberg, Y., IJzerman, H., Legate, N., & Grahe, J. (2019). A Demonstration of the Collaborative Replication and Education Project: Replication Attempts of the Red-Romance Effect. Collabra: Psychology, 5(1), 5. https://doi.org/10.1525/collabra.177

Walker, P., & Miksa, T. (2019, November 26). RDA-DMP-Common/RDA-DMP-Common-Standard. GitHub. https://github.com/RDA-DMP-Common/RDA-DMP-Common-Standard

Wason, P. C. (1960). On the Failure to Eliminate Hypotheses in a Conceptual Task. Quarterly Journal of Experimental Psychology, 12(3), 129–140. https://doi.org/10.1080/17470216008416717

Wasserstein, R. L., & Lazar, N. A. (2016). The ASA Statement on p -Values: Context, Process, and Purpose. The American Statistician, 70(2), 129–133. https://doi.org/10.1080/00031305.2016.1154108

Webster, M. M., & Rutz, C. (2020). How STRANGE are your study animals? Nature, 582(7812), 337–340. https://doi.org/10.1038/d41586-020-01751-5

Welcome to Sherpa Romeo—V2.sherpa. (n.d.). Sherpa Romeo. Retrieved 10 July 2021, from https://v2.sherpa.ac.uk/romeo/

Wendl, M. C. (2007). H-index: However ranked, citations need context. Nature, 449(7161), 403–403. https://doi.org/10.1038/449403b

What is a Codebook? (n.d.). ICPSR. Retrieved 9 July 2021, from https://www.icpsr.umich.edu/icpsrweb/content/shared/ICPSR/faqs/what-is-a-codebook.html

What is a reporting guideline? | The EQUATOR Network. (n.d.). Retrieved 10 July 2021, from https://www.equator-network.org/about-us/what-is-a-reporting-guideline/

What is Crowdsourcing? (2021, April 29). Crowdsourcing Week. https://crowdsourcingweek.com/what-is-crowdsourcing/

What is data sharing? | Support Centre for Data Sharing. (n.d.). Support Centre for Data Sharing. Retrieved 11 July 2021, from https://eudatasharing.eu/what-data-sharing

What is impact? - Economic and Social Research Council. (n.d.). Economic and Social Research Council. Retrieved 8 July 2021, from https://esrc.ukri.org/research/impact-toolkit/what-is-impact/

What is Open Data? (n.d.). Open Data Handbook. Retrieved 9 July 2021, from https://opendatahandbook.org/guide/en/what-is-open-data/

What is open education? (n.d.). Opensource.Com. Retrieved 9 July 2021, from https://opensource.com/resources/what-open-education

Whitaker, K., & Guest, O. (2020). #bropenscience is broken science. The Psychologist, 33, 34–37.

Wicherts, J. M., Veldkamp, C. L. S., Augusteijn, H. E. M., Bakker, M., van Aert, R. C. M., & van Assen, M. A. L. M. (2016). Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking. Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.01832

Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), 160018. https://doi.org/10.1038/sdata.2016.18

Wilson, B., & Fenner, M. (2012, May 9). Open Researcher &amp; Contributor ID (ORCID): Solving the Name Ambiguity Problem. https://er.educause.edu/articles/2012/5/open-researcher--contributor-id-orcid-solving-the-name-ambiguity-problem

Wilson, R. C., & Collins, A. G. (2019). Ten simple rules for the computational modeling of behavioral data. ELife, 8, e49547. https://doi.org/10.7554/eLife.49547

Wingen, T., Berkessel, J. B., & Englich, B. (2020). No Replication, No Trust? How Low Replicability Influences Trust in Psychology. Social Psychological and Personality Science, 11(4), 454–463. https://doi.org/10.1177/1948550619877412

Woelfle, M., Olliaro, P., & Todd, M. H. (2011). Open science is a research accelerator. Nature Chemistry, 3(10), 745–748. https://doi.org/10.1038/nchem.1149

Working Group 1 of the Joint Committee for Guides in Metrology JCGM. (2008). Evaluation of measurement data—Guide to the expression of uncertainty in measurement (pp. 1–120). JCGM. https://www.bipm.org/documents/20126/2071204/JCGM_100_2008_E.pdf/cb0ef43f-baa5-11cf-3f85-4dcd86f77bd6

World Wide Web Consortium. (n.d.). Home | Web Accessibility Initiative (WAI) | W3C. Web Accessibility Initiative. Retrieved 9 July 2021, from https://www.w3.org/WAI/

Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The Increasing Dominance of Teams in Production of Knowledge. Science, 316(5827), 1036–1039. https://doi.org/10.1126/science.1136099

Xia, J., Harmon, J. L., Connolly, K. G., Donnelly, R. M., Anderson, M. R., & Howard, H. A. (2015). Who publishes in “predatory” journals? Journal of the Association for Information Science and Technology, 66(7), 1406–1417. https://doi.org/10.1002/asi.23265

Yamada, Y. (2018). How to Crack Pre-registration: Toward Transparent and Open Science. Frontiers in Psychology, 9, 1831. https://doi.org/10.3389/fpsyg.2018.01831

Yarkoni, T. (2020). The generalizability crisis. Behavioral and Brain Sciences, 1–37. https://doi.org/10.1017/S0140525X20001685

Yeung, S. K., Feldman, G., Fillon, A., Protzko, J., Elsherif, M. M., Xiao, Q., & Pickering, J. (n.d.). Experimental Studies Meta-Analysis  Registered Report template: Main manuscript [Preprint]. Hong Kong University. https://docs.google.com/document/d/1z3QBDYr86S9FxGjptZP94jJnZeeN4aQaBQP3VVT89Ec/edit#

Zenodo—Research. Shared. (n.d.). Zenodo. Retrieved 9 July 2021, from https://www.zenodo.org/

Zurn, P., Bassett, D. S., & Rust, N. C. (2020). The Citation Diversity Statement: A Practice of Transparency, A Way of Life. Trends in Cognitive Sciences, 24(9), 669–672. https://doi.org/10.1016/j.tics.2020.06.009

Zwaan, R. A., Etz, A., Lucas, R. E., & Donnellan, M. B. (2018). Making replication mainstream. Behavioral and Brain Sciences, 41, e120. https://doi.org/10.1017/S0140525X17001972