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Record W4313197669 · doi:10.1097/acm.0000000000005025

Appreciation for Peer Review and Peer Reviewers in <i>Academic Medicine</i>

2022· article· en· W4313197669 on OpenAlexaff
Megan E. L. Brown, Teresa M. Chan, Michael Gottlieb, Gustavo A. Patiño, Laura Weiss Roberts

Bibliographic record

VenueAcademic Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcMaster University
Fundersnot available
KeywordsScholarshipConversationExcellenceValue (mathematics)Peer reviewPresentation (obstetrics)Peer feedbackPublic relationsSet (abstract data type)Technical peer reviewMedical educationPsychologyMedicinePolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

The editorial team of Academic Medicine is indebted to the extraordinary contributions of our peer reviewers. Remarkably, from September 2021 until September 2022, our journal benefitted from the guidance provided by more than 1,800 reviewers from 45 countries. These reviewers provide insights of tremendous value in editorial decision making, and they assist our authors in strengthening the rigor, quality, and presentation of their scholarship. 1 The intention of peer review is to foster excellence, which it achieves by a significant investment of expertise and time. For these reasons, peer review is generative, generous, and highly deserving of our appreciation. In thinking about this topic, one of us (L.W.R.) approached a handful of colleagues who work closely with our journal and have been recognized for their consistently outstanding reviews. Together we developed a set of reasons for (incredibly busy, stretched, and often overcommitted) professionals to serve as peer reviewers. We hope that these reasons will help reinforce the importance of peer review and the value of peer reviewers—and perhaps even inspire additional colleagues to join us in this work. For me, peer review is a conversation with others in the medical education community who may be outside of my direct professional network, which offers opportunities to learn from others’ experiences and work. (Megan E.L. Brown) Peer reviewing provides a natural way to engage in continuous learning and professional development. Appraising a manuscript invites the reviewer to consider new ways to write, address research questions, visualize data, conduct analyses, and frame discussions. 2 Reviewing also creates opportunities to stay up to date with the literature; to become familiar with different contexts and ways of knowing; and to learn new techniques, approaches, and methodologies. Further, reviewers may be introduced to novel theories and frameworks that can help illuminate their own teaching and scholarship. 3,4 A second reason to serve as a peer reviewer is that this practice offers an additional opportunity to mentor, with reach beyond one’s own institution or immediate community. Careful and thorough feedback on a manuscript can help authors to improve its overall quality and to address specific flaws it may have. 5 Perhaps, more importantly, a constructive, respectful, well-informed peer review can provide guidance that may be helpful to early career scholars as they tackle future projects and articles. For the field to continue to advance, it is critical we help guide and mentor future education scholars, and peer review is a good way to do this. (Michael Gottlieb) A closely related reason for performing peer reviews is that it is part of being a good colleague within the academic community. Manuscripts that we submit as authors are improved by those reviewers who volunteer their expertise and time. Peer review offers all of us a chance to help “pay it forward” to help others as a form of “academic karma.” 6 For every article that I publish, there are usually 2 editors and 2 to 3 reviewers who have contributed sweat equity to my publication (without credit in most cases). (Teresa M. Chan) Participating as a peer reviewer is a way to influence standards of excellence and to define better and best practices in scholarship. 7 Reviewers help to ensure that the methods and interpretation of results in a manuscript are sound and that the constraints and limitations of the work are well understood. 8 As more issues in our field rely on evidence for consensus-building, resolution, and strategic decision making, scholarly approaches are becoming more complex and analyses and interpretations more consequential. For these reasons and others, service as an expert peer reviewer should be recognized in academic promotions. While this might not be the case at every institution, our hope is that more departments and more institutional promotion committees will assign value to peer review service. Serving as a peer reviewer offers a window into the most audacious and creative version of someone’s work, which often inspires me to take bigger risks in my own scholarship. (Gustavo A. Patino) The privilege of serving as a peer reviewer does come with significant ethical responsibilities. Recusing oneself from submissions where a role conflict or conflict of interest may exist is one such responsibility. Understanding the limits of one’s knowledge is a second example. The Center on Publication Ethics has published “Ethical Guidelines for Peer Reviewers,” 9 noting that peer review ultimately depends on the honesty, integrity, and trustworthiness of all in the scholarly community. This is a live issue, as reflected in the findings of a recent empirical study that evaluated nearly 1,500 reviewer comments published online in 2 scientific fields and found that 12% included at least 1 unprofessional comment about the author of the work and 41% included at least 1 inaccurate or unsubstantiated critique. 10 At Academic Medicine, we strive for better, and we endeavor to safeguard authors’ trust in several ways. When we seek peer review on a manuscript, we ensure that we have at least 2 reviewers and more than 1 editor evaluate the manuscript and its suitability for publication. In addition, we have policies and practices in place to help prevent role and interest conflicts. Our journal has created a number of reviewer resources, including reviewer guidelines, expert tips and tricks, training, and even a practice exercise, all of which are available on our website at https://journals.lww.com/academicmedicine/Pages/forreviewers.aspx. Members of the editorial team carefully evaluate reviews before they are shared with authors. Our journal also has a formal appeals process in place for our authors who have concerns about the reviews they have received. We receive appeals from time to time and they are diligently evaluated. And, finally, we continue to invite new reviewers with a wide diversity of expertise, backgrounds, and experience. We conclude with thanking all of you who are the journal’s peer reviewers. Your contributions are so important to our field. Your dedication to learning, mentoring, collegiality, advancing excellence, and ensuring professionalism—and supporting the authors and editorial team of Academic Medicine all the while—are deeply appreciated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.188
metaresearch head score (Gemma)0.617
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.812
Threshold uncertainty score0.993

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1880.617
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0050.006
Science and technology studies0.0080.022
Scholarly communication0.0500.022
Open science0.0070.009
Research integrity0.0210.040
Insufficient payload (model declined to judge)0.0100.023

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.428
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainEvaluation
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2022
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