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Enregistrement W4387392554 · doi:10.1002/bdr2.2255

Recommendation to change the peer review process

2023· article· en· W4387392554 sur OpenAlex

Pourquoi ce travail est dans la base

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Notice bibliographique

RevueBirth Defects Research · 2023
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueMeta-analysis and systematic reviews
Établissements canadiensSt. Stephen's University
Organismes subventionnairesnon disponible
Mots-clésProcess (computing)Computer scienceInformation retrievalContent (measure theory)Peer reviewWorld Wide WebInternet privacyPolitical scienceMathematicsLawProgramming language

Résumé

récupéré en direct d'OpenAlex

As long-time subscribers, readers, authors, and peer-reviewers for Birth Defects Research (BDR, formerly Teratology), we believe the peer review process has been deteriorating. This is seen throughout the scientific literature and is not merely in BDR. With the proliferation of new journals internationally, the amount of inferior science published in the literature is increasing, so the peer review process must be strengthened. To this end, we propose the following two recommendations for discussion and encourage a rapid change to a new Peer Review format. We realize any changes to the peer review process must pass through several levels within the editorial office, as well as the Society for Birth Defects Research and Prevention, before being approved by the publisher, Wiley Publishing. We also recognize publishers (e.g., Wiley and Elsevier) are well aware of the subject and have collected much useful information available on their websites (Wiley Author Services, n.d.-a; Elsevier, n.d.). BDR uses a single anonymized model, as shown on the Wiley website (Wiley Author Services, n.d.-b). Readers are encouraged to search the fairly extensive literature, perhaps starting with our references listed in Supplemental Information. Wiley has collected much of this information and summarized various options, with pros and cons for each (Wiley Author Services, n.d.-c). At first, we believed a system allowing more ways to review and comment on a manuscript would lead to a better product; however, implementing such procedures likely would be cumbersome and/or expensive. Other models can be implemented almost immediately, which would greatly improve the transparency and legitimacy of BDR's peer review process. Several options are available to change the BDR's peer review system. One would be to adopt the “Transparent Peer Review” (TPR) model (Wiley Author Services, n.d.-c) in which the review is published (or posted) along with the article (authors have the option to decline TPR, and reviewers can choose whether or not to be identified). Wiley has launched a TPR program with over 60 participating journals (Wiley Author Services, n.d.-d). A link to a TPR example is located in Wiley Author Services (n.d.-d), as well as links to all other journals within the program. Additionally, as presented in the associated figure, one can read the benefits that accrue to authors, research in general, and the publisher. A study of this available model of published reviews found increased helpful reviewer comments and positive recommendations (Bravo et al., 2019; Communications Physics, 2022; Cosgrove & Cheifet, 2018). Another option is to incentivize the review process in a way that motivates reviewers to put forth a strong effort. For instance, reviewers could be offered a tangible reward for peer review (Brainard, 2021; Cheah & Piasecki, 2022). Indirect rewards (e.g., being a good academic citizen, participating in peer review as a usual part of work) are well established. If an honorarium were offered, it could be accepted, declined, donated, used to access articles, or used to help with various article processing charges. We acknowledge that there are arguments against monetary incentives. Still, a tangible reward, such as an honorarium or points that could be accrued and used to purchase Wiley books at a discount, may (1) enlarge the pool of reviewers, (2) engender motivation to review, and (3) increase the speed of reviews. It is likely that together with the publication of reviewers’ reports, there would be accountability and improved quality of published manuscripts. While the two previous suggestions would help to improve the logistical process, in the end, successful peer review comes down to individual reviewers. We do not presume to give specific instructions or recommendations on conducting a peer review, and perhaps our societies should organize reoccurring classes or workshops on the subject. In addition, the Wiley website has valuable materials for the novice peer reviewer (Wiley Author Services, n.d.-e), and Elsevier Researcher Academy offers an online certification course (Elsevier Researcher Academy, n.d.). By accepting an invitation, the reviewers promise to give the assignment their experience, wisdom, unbiased skepticism, work ethic, and willingness to give back to the scientific method. An astute reviewer will assess his/her capability to review the manuscript and/or recognize the potential for perceived bias. Upon assuming the task, a good reviewer will assess whether the experimental design is appropriate for the question at hand, methods are acceptable, data presentation is proper, and figures and photographs are clear. Peer reviewers must then decide if those methods and results lead to conclusions drawn by the authors, and if the authors have made adequate comparisons to previous/similar studies, as well as, perhaps, suggestions for future research. Ultimately, these subjective aspects must be self-taught during continuous training in the scientific method. With this said, we believe that reviewers should be proud to affix their names to their reviews, as we shall do in the future. We are not alone in recognizing the amount of poor science being published and have heard complaints from others about the current status of the peer review system. But in the final analysis, it is up to you, the readership, to take action if you want to fix the problem. This means continued, dedicated participation in the review process, and thinking about ways to improve it. We invite comments and discussion, especially to our suggestions as listed above. The authors report no conflict of interest. Data S1. Supporting information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,436
score de la tête « metaresearch » (Gemma)0,227
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMétarecherche, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,702
Score d'incertitude au seuil0,970

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,4360,227
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,013
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0030,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0310,133

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,954
Tête enseignante GPT0,689
Écart entre enseignants0,265 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle