Authors and publication practices

Although authors are usually considered to be the main perpetrators of research and publication misconduct, any person involved in the process has the potential to offend. Editors may breach ethical standards particularly with respect to conflicts of interest. In the same way that authors are now required to declare competing interests, notably commercial affiliations, financial interests and personal connections, so must editors. Editors can influence the chances of acceptance or rejection of a paper by reviewer selection. Reviewers should also be ready to disclose conflicts of interest. They must ensure that their reviews are evidence based and free from destructive criticism driven by self interest. It seems likely that ultimately we will progressively move towards 'open' peer review in which both the authors and the reviewers are known to each other. There is an urgent need for increased transparency of the relationship between editors and owners. The events of the last few years indicate that unless this interface is fully understood by all parties, conflicts may arise. There is also a need for a radical overhaul in the relationship between journals, journal editors and the biomedical industry. It is now increasingly accepted that all clinical trials should be registered in a centrally held database and that protocols should include the primary and secondary outcome measures and the intended approach to data analysis thereby avoiding opportunistic post hoc analyses. However, the even more radical proposal that journals should cease to publish clinical trials sponsored by industry deserves wider debate.     

Should Authors be Requested to Suggest Peer Reviewers?

As part of a continuous process to explore the factors that might weaken or corrupt traditional peer review, in this paper, we query the ethics, fairness and validity of the request, by editors, of authors to suggest peer reviewers during the submission process. One of the reasons for the current crisis in science pertains to a loss in trust as a result of a flawed peer review which is by nature biased unless it is open peer review. As we indicate, the fact that some editors and journals rely on authors’ suggestions in terms of who should peer review their paper already instills a potential way to abuse the trust of the submission and publishing system. An author-suggested peer reviewer choice might also tempt authors to seek reviewers who might be more receptive or sympathetic to the authors’ message or results, and thus favor the outcome of that paper. Authors should thus not be placed in such a potentially ethically compromising situation, especially as a mandatory condition for submission. However, the fact that they do not have an opt-out choice during the submission process—especially when using an online submission system that makes such a suggestion compulsory—may constitute a violation of authors’ rights.     

Regularized Multiple-Set Canonical Correlation Analysis

Multiple-set canonical correlation analysis (Generalized CANO or GCANO for short) is an important technique because it subsumes a number of interesting multivariate data analysis techniques as special cases. More recently, it has also been recognized as an important technique for integrating information from multiple sources. In this paper, we present a simple regularization technique for GCANO and demonstrate its usefulness. Regularization is deemed important as a way of supplementing insufficient data by prior knowledge, and/or of incorporating certain desirable properties in the estimates of parameters in the model. Implications of regularized GCANO for multiple correspondence analysis are also discussed. Examples are given to illustrate the use of the proposed technique. The work reported in this paper is supported by Grants 10630 and 290439 from the Natural Sciences and Engineering Research Council of Canada to the first and the second authors, respectively. The authors would like to thank the two editors (old and new), the associate editor, and four anonymous reviewers for their insightful comments on earlier versions of this paper. Matlab programs that carried out the computations reported in the paper are available upon request.     

When is Nothing Something? Editorial for the Null Results Special Issue of Journal of Business and Psychology

This special issue is focused on how null results can meaningfully advance science and practice. This editorial describes some of the unique aspects of creating a special issue devoted to null results, offers opinions regarding why and under what conditions null results should be valued, and offers recommendations for key stakeholders (i.e., editors, reviewers, and authors) in the publication enterprise with respect to submitting and evaluating research with null findings. This editorial also provides summaries of the papers included in this special issue with emphasis on how they serve as example for what constitutes meaningful null results.     

Editors' perspectives on the selection of reviewers and the quality of reviews

This article describes the outcomes of a survey of 93 editors in chief and associate editors of behavior-analytic journals. We sought information about variables that influence their judgment of the selection of reviewers, selection of review panels, and quality of reviews. When selecting reviewers, participants rated highly expertise on the topic, history of conducting good reviews, and history of writing constructive and respectful reviews. When selecting review panels, participants rated highly stratifying reviewers based on their expertise, avoiding conflicts of interest, and the matching based on the area of expertise between reviewers and authors. When evaluating the quality of a review, participants rated highly considerations related to research design, the science underlying the main idea, and accurate interpretations of the data. Participants did not rate copyediting as important. Overall, the extent to which reviewer selection was influenced by membership in underrepresented groups varied. These findings can inform the development of training programs for teaching peer-review repertoires.     

What Reviewers Should Expect from Authors Regarding Common Method Bias in Organizational Research

We believe that journal reviewers (as well as editors and dissertation or thesis committee members) have to some extent perpetuated misconceptions about common method bias in self-report measures, including (a) that relationships between self-reported variables are necessarily and routinely upwardly biased, (b) other-reports (or other methods) are superior to self-reports, and (c) rating sources (e.g., self, other) constitute measurement methods. We argue against these misconceptions and make recommendations for what reviewers (and others) should reasonably expect from authors regarding common method bias. We believe it is reasonable to expect (a) an argument for why self-reports are appropriate, (b) construct validity evidence, (c) lack of overlap in items for different constructs, and (d) evidence that authors took proactive design steps to mitigate threats of method effects. We specifically do not recommend post hoc statistical control strategies; while some statistical strategies are promising, all have significant drawbacks and some have shown poor empirical results.     

Ensuring the Quality,Fairness, and Integrity of Journal Peer Review: A Possible Role of Editors

A growing body of literature has identified potential problems that can compromise the quality, fairness, and integrity of journal peer review, including inadequate review, inconsistent reviewer reports, reviewer biases, and ethical transgressions by reviewers. We examine the evidence concerning these problems and discuss proposed reforms, including double-blind and open review. Regardless of the outcome of additional research or attempts at reforming the system, it is clear that editors are the linchpin of peer review, since they make decisions that have a significant impact on the process and its outcome. We consider some of the steps editors should take to promote quality, fairness and integrity in different stages of the peer review process and make some recommendations for editorial conduct and decision-making.     

Beyond inference by eye: Statistical and graphing practices in JEAB, 1992‐2017

Debates about the utility of p values and correct ways to analyze data have inspired new guidelines on statistical inference by the American Psychological Association (APA) and changes in the way results are reported in other scientific journals, but their impact on the Journal of the Experimental Analysis of Behavior (JEAB) has not previously been evaluated. A content analysis of empirical articles published in JEAB between 1992 and 2017 investigated whether statistical and graphing practices changed during that time period. The likelihood that a JEAB article reported a null hypothesis significance test, included a confidence interval, or depicted at least one figure with error bars has increased over time. Features of graphs in JEAB, including the proportion depicting single‐subject data, have not changed systematically during the same period. Statistics and graphing trends in JEAB largely paralleled those in mainstream psychology journals, but there was no evidence that changes to APA style had any direct impact on JEAB. In the future, the onus will continue to be on authors, reviewers and editors to ensure that statistical and graphing practices in JEAB continue to evolve without interfering with characteristics that set the journal apart from other scientific journals.     

Using a dialectical scientific brief in peer review

This paper presents a framework that editors, peer reviewers, and authors can use to identify and resolve efficiently disputes that arise during peer review in scientific journals. The framework is called a scientific dialectical brief. In this framework, differences among authors and reviewers are formatted into specific assertions and the support each party provides for its position. A literature review suggests that scientists use five main types of support; empirical data, reasoning, speculation, feelings, and status. It is suggested that the scientific dialectical brief format can streamline the review process by facilitating rapid differentiation between stronger and weaker support, so that valuable time can be focused on the better-substantiated claims. The paper concludes with some suggestions for implementation. The author researches, lectures and publishes in the area of physical and social aspects of environmental quality. He is also a practicing architect. This paper is based on a presentation at a workshop, “Advances in Peer Review Research”, American Association for the Advancement of Science Meeting, Baltimore, MD, February 9, 1996.     

Detecting and (Not) Dealing with Plagiarism in an Engineering Paper: Beyond CrossCheck—A Case Study

In papers in areas such as engineering and the physical sciences, figures, tables and formulae are the basic elements to communicate the authors’ core ideas, workings and results. As a computational text-matching tool, CrossCheck cannot work on these non-textual elements to detect plagiarism. Consequently, when comparing engineering or physical sciences papers, CrossCheck may return a low similarity index even when plagiarism has in fact taken place. A case of demonstrated plagiarism involving engineering papers with a low similarity index is discussed, and editor’s experiences and suggestions are given on how to tackle this problem. The case shows a lack of understanding of plagiarism by some authors or editors, and illustrates the difficulty of getting some editors and publishers to take appropriate action. Consequently, authors, journal editors, and reviewers, as well as research institutions all are duty-bound not only to recognize the differences between ethical and unethical behavior in order to protect a healthy research environment, and also to maintain consistent ethical publishing standards.     

Recommendations for Describing Statistical Studies and Results in General Readership Science and Engineering Journals

This paper recommends how authors of statistical studies can communicate to general audiences fully, clearly, and comfortably. The studies may use statistical methods to explore issues in science, engineering, and society or they may address issues in statistics specifically. In either case, readers without explicit statistical training should have no problem understanding the issues, the methods, or the results at a non-technical level. The arguments for those results should be clear, logical, and persuasive. This paper also provides advice for editors of general journals on selecting high quality statistical articles without the need for exceptional work or expense. Finally, readers are also advised to watch out for some common errors or misuses of statistics that can be detected without a technical statistical background.