Honest signaling in academic publishing

Shifting the Level of Selection in Science

Criteria for recognizing and rewarding scientists primarily focus on individual contributions. This creates a conflict between what is best for scientists' careers and what is best for science. In this article, we show how the theory of multilevel selection provides conceptual tools for modifying incentives to better align individual and collective interests. A core principle is the need to account for indirect effects by shifting the level at which selection operates from individuals to the groups in which individuals are embedded. This principle is used in several fields to improve collective outcomes, including animal husbandry, team sports, and professional organizations. Shifting the level of selection has the potential to ameliorate several problems in contemporary science, including accounting for scientists' diverse contributions to knowledge generation, reducing individual-level competition, and promoting specialization and team science. We discuss the difficulties associated with shifting the level of selection and outline directions for future development in this domain.

Bridging the information gap in organic chemical reactions

The varying quality of scientific reports is a well-recognized problem and often results from a lack of standardization and transparency in scientific publications. This situation ultimately leads to prominent complications such as reproducibility issues and the slow uptake of newly developed synthetic methods for pharmaceutical and agrochemical applications. In recent years, various impactful approaches have been advocated to bridge information gaps and to improve the quality of experimental protocols in synthetic organic publications. Here we provide a critical overview of these strategies and present the reader with a versatile set of tools to augment their standard procedures. We formulate eight principles to improve data management in scientific publications relating to data standardization, reproducibility and evaluation, and encourage scientists to go beyond current publication standards. We are aware that this is a substantial effort, but we are convinced that the resulting improved data situation will greatly benefit the progress of chemistry.

Inconsistent quality signals: evidence from the regional journals

Nowadays many countries and institutions use bibliometric assessment of journal quality in their research evaluation policies. However, bibliometric measures, such as impact factor or quartile, may provide a biased quality assessment for relatively new, regional, or non-mainstream journals, as these outlets usually do not possess a longstanding history, and may not be included into indexing databases. To reduce the information asymmetry between academic community (researchers, editors, policymakers) and journal management, we propose an alternative approach to evaluate journals quality signals using previous publication track record of authors. We explore the difference in the quality signals sent by regional journals. Traditional, journal-level, bibliometric measures are contrasted with generalised measures of authors' publishing records. We used a set of 50,477 articles and reviews in 83 regional journals in Physics and Astronomy (2014-2019) to extract and process data on 73 866 authors and their additional 329,245 publications in other Scopus-indexed journals. We found that traditional journal-level measures (such as journal quartile, CiteScore percentile, Scimago Journal Rank) tend to under-evaluate journal quality, thus contributing to an image of low-quality research venues. Author-level measures (including the share of papers in the Nature Index journals) send positive signals of journal quality and allow us to subdivide regional journals by their publishing strategies. These results suggest that research evaluation policies might consider attributing greater weight to regional journals, not only for the training purposes of doctoral students but also for gaining international visibility and impact.

Raising the value of research studies in psychological science by increasing the credibility of research reports: the transparent Psi project

The low reproducibility rate in social sciences has produced hesitation among researchers in accepting published findings at their face value. Despite the advent of initiatives to increase transparency in research reporting, the field is still lacking tools to verify the credibility of research reports. In the present paper, we describe methodologies that let researchers craft highly credible research and allow their peers to verify this credibility. We demonstrate the application of these methods in a multi-laboratory replication of Bem's Experiment 1 (Bem 2011 J. Pers. Soc. Psychol. 100, 407-425. (doi:10.1037/a0021524)) on extrasensory perception (ESP), which was co-designed by a consensus panel including both proponents and opponents of Bem's original hypothesis. In the study we applied direct data deposition in combination with born-open data and real-time research reports to extend transparency to protocol delivery and data collection. We also used piloting, checklists, laboratory logs and video-documented trial sessions to ascertain as-intended protocol delivery, and external research auditors to monitor research integrity. We found 49.89% successful guesses, while Bem reported 53.07% success rate, with the chance level being 50%. Thus, Bem's findings were not replicated in our study. In the paper, we discuss the implementation, feasibility and perceived usefulness of the credibility-enhancing methodologies used throughout the project.

The Role of Publons in the Context of Open Peer Review

Publons was a peer reviewer rewards platform that aimed to recognize the contribution that academics made during peer review to a journal. For about 10 years of its existence, Publons became the most popular service among peer reviewers. Having gained traction and popularity, Publons was purchased in 2017 by Clarivate Analytics (now Clarivate), and many academics, journals and publishers invested time and effort to participate in Publons. Using Publons, various peer review-related experiments or pilot programs were initiated by some academic publishers regarding the introduction of open peer review into their journals’ editorial processes. In this paper, we examine pertinent literature related to Publons, and reflect on its benefits and flaws during its short-lived history. In mid-August 2022, Clarivate fused Publons into the Web of Science platform. Publons, as a brand peer review service, has now ceased to exist but some of the functionality remains in Web of Science while other aspects that used to be open and free at Publons are now paid-for services. We reflect on the effect of such experiments, which initially had bold and ambitious academic objectives to fortify peer review, on academics’ trust, especially when such projects become commercialized.

Incentives for Research Effort: An Evolutionary Model of Publication Markets with Double-Blind and Open Review

Contemporary debates about scientific institutions and practice feature many proposed reforms. Most of these require increased efforts from scientists. But how do scientists' incentives for effort interact? How can scientific institutions encourage scientists to invest effort in research? We explore these questions using a game-theoretic model of publication markets. We employ a base game between authors and reviewers, before assessing some of its tendencies by means of analysis and simulations. We compare how the effort expenditures of these groups interact in our model under a variety of settings, such as double-blind and open review systems. We make a number of findings, including that open review can increase the effort of authors in a range of circumstances and that these effects can manifest in a policy-relevant period of time. However, we find that open review's impact on authors' efforts is sensitive to the strength of several other influences.

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Retinal neurogenesis is driven by concerted actions of transcription factors, some of which are expressed in a continuum and across several cell subtypes throughout development. While seemingly redundant, many factors diversify their regulatory outcome on gene expression, by coordinating variations in chromatin landscapes to drive divergent retinal specification programs. Recent studies have furthered the understanding of the epigenetic contribution to the progression of age-related macular degeneration, a leading cause of blindness in the elderly. The knowledge of the epigenomic mechanisms that control the acquisition and stabilization of retinal cell fates and are evoked upon damage, holds the potential for the treatment of retinal degeneration. Herein, this review presents the state-of-the-art approaches to investigate the retinal epigenome during development, disease, and reprogramming. A pipeline is then reviewed to functionally interrogate the epigenetic and transcriptional networks underlying cell fate specification, relying on a truly unbiased screening of open chromatin states. The related work proposes an inferential model to identify gene regulatory networks, features the first footprinting analysis and the first tentative, systematic query of candidate pioneer factors in the retina ever conducted in any model organism, leading to the identification of previously uncharacterized master regulators of retinal cell identity, such as the nuclear factor I, NFI. This pipeline is virtually applicable to the study of genetic programs and candidate pioneer factors in any developmental context. Finally, challenges and limitations intrinsic to the current next-generation sequencing techniques are discussed, as well as recent advances in super-resolution imaging, enabling spatio-temporal resolution of the genome.

Mechanistic modeling for the masses

The generalizability crisis is compounded, or even partially caused, by a lack of specificity in psychological theories. Expanding the use of mechanistic models among psychologists is therefore important, but faces numerous hurdles. A cultural evolutionary approach can help guide and evaluate interventions to improve modeling efforts in psychology, such as developing standards and implementing them at the institutional level.