scholarly journals Opening the Door to Registered Reports: Census of Journals Publishing Registered Reports (2013–2020)

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Amanda Kay Montoya ◽  
William Leo Donald Krenzer ◽  
Jessica Louise Fossum

Registered reports are a new publication workflow where the decision to publish is made prior to data collection and analysis and thus cannot be dependent on the outcome of the study. An increasing number of journals have adopted this new mechanism, but previous research suggests that submission rates are still relatively low. We conducted a census of journals publishing registered reports (N = 278) using independent coders to collect information from submission guidelines, with the goal of documenting journals’ early adoption of registered reports. Our results show that the majority of journals adopting registered reports are in psychology, and it typically takes about a year to publish the first registered report after adopting. Still, many journals have not published their first registered report. There is high variability in impact of journals adopting registered reports. Many journals do not include concrete information about policies that address concerns about registered reports (e.g., exploratory analysis); however, those that do typically allow these practices with some restrictions. Additionally, other open science practices are commonly encouraged or required as part of the registered report process, especially open data and materials. Overall, many journals did not include many of the fields coded by the research team, which could be a barrier to submission for some authors. Though the majority of journals allow authors to be anonymous during the review process, a sizable portion do not, which could also be a barrier to submission. We conclude with future directions and implications for authors of registered reports, journals that have already adopted registered reports, and journals that may consider adopting registered reports in the future.

2021 ◽  
Author(s):  
Katherine S. Corker

Part of what distinguishes science from other ways of knowing is that scientists show their work. Yet when probed, it turns out that much of the process of research is hidden away: in personal files, in undocumented conversations, in point-and-click menus, and so on. In recent years, a movement towards more open science has arisen in psychology. Open science practices capture a broad swath of activities designed to take parts of the research process that were previously known only to a research team and make them more broadly accessible (e.g., open data, open analysis code, pre-registration, open research materials). Such practices increase the value of research by increasing transparency, which may in turn facilitate higher research quality. Plus, open science practices are now required at many journals. This chapter will introduce open science practices and provide plentiful resources for researchers seeking to integrate these practices into their workflow.


2020 ◽  
Vol 36 (3) ◽  
pp. 263-279
Author(s):  
Isabel Steinhardt

Openness in science and education is increasing in importance within the digital knowledge society. So far, less attention has been paid to teaching Open Science in bachelor’s degrees or in qualitative methods. Therefore, the aim of this article is to use a seminar example to explore what Open Science practices can be taught in qualitative research and how digital tools can be involved. The seminar focused on the following practices: Open data practices, the practice of using the free and open source tool “Collaborative online Interpretation, the practice of participating, cooperating, collaborating and contributing through participatory technologies and in social (based) networks. To learn Open Science practices, the students were involved in a qualitative research project about “Use of digital technologies for the study and habitus of students”. The study shows the practices of Open Data are easy to teach, whereas the use of free and open source tools and participatory technologies for collaboration, participation, cooperation and contribution is more difficult. In addition, a cultural shift would have to take place within German universities to promote Open Science practices in general.


2021 ◽  
Author(s):  
Kathryn R. Wentzel

In this article, I comment on the potential benefits and limitations of open science reforms for improving the transparency and accountability of research, and enhancing the credibility of research findings within communities of policy and practice. Specifically, I discuss the role of replication and reproducibility of research in promoting better quality studies, the identification of generalizable principles, and relevance for practitioners and policymakers. Second, I suggest that greater attention to theory might contribute to the impact of open science practices, and discuss ways in which theory has implications for sampling, measurement and research design. Ambiguities concerning the aims of preregistration and registered reports also are highlighted. In conclusion, I discuss structural roadblocks to open science reform and reflect on the relevance of these reforms for educational psychology.


2021 ◽  
Author(s):  
Tamara Kalandadze ◽  
Sara Ann Hart

The increasing adoption of open science practices in the last decade has been changing the scientific landscape across fields. However, developmental science has been relatively slow in adopting open science practices. To address this issue, we followed the format of Crüwell et al., (2019) and created summaries and an annotated list of informative and actionable resources discussing ten topics in developmental science: Open science; Reproducibility and replication; Open data, materials and code; Open access; Preregistration; Registered reports; Replication; Incentives; Collaborative developmental science.This article offers researchers and students in developmental science a starting point for understanding how open science intersects with developmental science. After getting familiarized with this article, the developmental scientist should understand the core tenets of open and reproducible developmental science, and feel motivated to start applying open science practices in their workflow.


2018 ◽  
Author(s):  
Christopher P G Allen ◽  
David Marc Anton Mehler

The movement towards open science is an unavoidable consequence of seemingly pervasive failures to replicate previous research. This transition comes with great benefits but also significant challenges that are likely to afflict those who carry out the research, usually Early Career Researchers (ECRs). Here, we describe key benefits including reputational gains, increased chances of publication and a broader increase in the reliability of research. These are balanced by challenges that we have encountered, and which involve increased costs in terms of flexibility, time and issues with the current incentive structure, all of which seem to affect ECRs acutely. Although there are major obstacles to the early adoption of open science, overall open science practices should benefit both the ECR and improve the quality and plausibility of research. We review three benefits, three challenges and provide suggestions from the perspective of ECRs for moving towards open science practices.


2020 ◽  
Author(s):  
Denis Cousineau

Born-Open Data experiments are encouraged for better open science practices. To be adopted, Born-Open data practices must be easy to implement. Herein, I introduce a package for E-Prime such that the data files are automatically saved on a GitHub repository. The BornOpenData package for E-Prime works seamlessly and performs the upload as soon as the experiment is finished so that there is no additional steps to perform beyond placing a package call within E-Prime. Because E-Prime files are not standard tab-separated files, I also provide an R function that retrieves the data directly from GitHub into a data frame ready to be analyzed. At this time, there are no standards as to what should constitute an adequate open-access data repository so I propose a few suggestions that any future Born-Open data system could follow for easier use by the research community.


2022 ◽  
Author(s):  
Bermond Scoggins ◽  
Matthew Peter Robertson

The scientific method is predicated on transparency -- yet the pace at which transparent research practices are being adopted by the scientific community is slow. The replication crisis in psychology showed that published findings employing statistical inference are threatened by undetected errors, data manipulation, and data falsification. To mitigate these problems and bolster research credibility, open data and preregistration have increasingly been adopted in the natural and social sciences. While many political science and international relations journals have committed to implementing these reforms, the extent of open science practices is unknown. We bring large-scale text analysis and machine learning classifiers to bear on the question. Using population-level data -- 93,931 articles across the top 160 political science and IR journals between 2010 and 2021 -- we find that approximately 21% of all statistical inference papers have open data, and 5% of all experiments are preregistered. Despite this shortfall, the example of leading journals in the field shows that change is feasible and can be effected quickly.


2018 ◽  
Author(s):  
Gerit Pfuhl ◽  
Jon Grahe

Watch the VIDEO.Recent years have seen a revolution in publishing, and large support for open access publishing. There has been a slower acceptance and transition to other open science principles such as open data, open materials, and preregistration. To accelerate the transition and make open science the new standard, the collaborative replications and education project (CREP; http://osf.io/wfc6u/)) was launched in 2013, hosted on the Open Science Framework (osf.io). OSF is like a preprint, collecting partial data with each individual contributors project. CREP introduces open science at the start of academic research, facilitating student research training in open science and solidifying behavioral science results. The CREP team attempts to achieve this by inviting contributors to replicate one of several replication studies selected for scientific impact and suitability for undergraduates to complete during one academic term. Contributors follow clear protocols with students interacting with a CREP team that reviews the materials and video of the procedure to ensure quality data collection while students are learning science practices and methods. By combining multiple replications from undergraduates across the globe, the findings can be pooled to conduct meta-analysis and so contribute to generalizable and replicable research findings. CREP is careful to not interpret any single result. CREP has recently joined forces with the psychological science accelerator (PsySciAcc), a globally distributed network of psychological laboratories accelerating the accumulation of reliable and generalizable results in the behavioral sciences. The Department of Psychology at UiT is part of the network and has two ongoing CREP studies, maintaining open science practices early on. In this talk, we will present our experiences of conducting transparent replicable research, and experience with preprints from a supervisor and researcher perspective.


2021 ◽  
Author(s):  
Robert Heirene ◽  
Debi LaPlante ◽  
Eric R. Louderback ◽  
Brittany Keen ◽  
Marjan Bakker ◽  
...  

Study preregistration is one of several “open science” practices (e.g., open data, preprints) that researchers use to improve the transparency and rigour of their research. As more researchers adopt preregistration as a regular research practice, examining the nature and content of preregistrations can help identify strengths and weaknesses of current practices. The value of preregistration, in part, relates to the specificity of the study plan and the extent to which investigators adhere to this plan. We identified 53 preregistrations from the gambling studies field meeting our predefined eligibility criteria and scored their level of specificity using a 23-item protocol developed to measure the extent to which a clear and exhaustive preregistration plan restricts various researcher degrees of freedom (RDoF; i.e., the many methodological choices available to researchers when collecting and analysing data, and when reporting their findings). We also scored studies on a 32-item protocol that measured adherence to the preregistered plan in the study manuscript. We found that gambling preregistrations had low specificity levels on most RDoF. However, a comparison with a sample of cross-disciplinary preregistrations (N = 52; Bakker et al., 2020) indicated that gambling preregistrations scored higher on 12 (of 29) items. Thirteen (65%) of the 20 associated published articles or preprints deviated from the protocol without declaring as much (the mean number of undeclared deviations per article was 2.25, SD = 2.34). Overall, while we found improvements in specificity and adherence over time (2017-2020), our findings suggest the purported benefits of preregistration—including increasing transparency and reducing RDoF—are not fully achieved by current practices. Using our findings, we provide 10 practical recommendations that can be used to support and refine preregistration practices.


2021 ◽  
Vol 35 (3) ◽  
pp. 193-214
Author(s):  
Edward Miguel

A decade ago, the term “research transparency” was not on economists' radar screen, but in a few short years a scholarly movement has emerged to bring new open science practices, tools and norms into the mainstream of our discipline. The goal of this article is to lay out the evidence on the adoption of these approaches – in three specific areas: open data, pre-registration and pre-analysis plans, and journal policies – and, more tentatively, begin to assess their impacts on the quality and credibility of economics research. The evidence to date indicates that economics (and related quantitative social science fields) are in a period of rapid transition toward new transparency-enhancing norms. While solid data on the benefits of these practices in economics is still limited, in part due to their relatively recent adoption, there is growing reason to believe that critics' worst fears regarding onerous adoption costs have not been realized. Finally, the article presents a set of frontier questions and potential innovations.


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