Notice bibliographique
Résumé
Being a product of its time, it will come as no surprise to readers that Medical Education has published a flurry of papers focused on different aspects of Diversity, Equity, and Inclusion (DEI) recently. In fact, since we dedicated a State of the Science issue to the topic 7 years ago,1 there has been a steady drip of relevant publications that has only increased in pace with no fewer than three “When I Say” articles2-4 seeking to add a degree of definitional clarity in addition to the empirical works that have been undertaken.5 Some of that empirical evidence has offered reasons for the journal to be proud of its contributions in these regards. Madden et al, for example, reported that female representation among first authors has increased from 6% in 1970 to 60% in 2019.6 We routinely publish papers from more than 30 distinct countries each year. And, while four of those countries account for more than half of our submissions, the journal has made considerable effort to build a diverse team of advisors with those same four countries accounting for fewer than a quarter of our board members.7, 8 Through their advice, we strive to contribute to the development of health professional education scholarship in all regions that are invested in becoming world leaders in this field. “Strive” is the operative word, however, as such work is never complete and we certainly do not believe the journal to “have it right.” Part of the challenge is that we have too little data. I am, therefore, pleased to report that Wiley, the journal's publisher, has proudly co-signed the Joint Commitment for Action on Inclusion and Diversity in Publishing.9 As part of that decision, they have committed to enabling self-reporting of demographic data for authors and reviewers (with details to come as they strive to ensure respectful and appropriate processes). They have also implemented the capacity for authors to include pronouns in article bylines should authors wish to do so. Through these and other means, we hope to better understand how to support more diverse sets of communities including those advocated for by Russel in this issue.10 You can also strive to help by taking the time to respond to our DEI working group's request for guidance if you have not done so already.11 That group has been led splendidly by Rola Ajjawi who has recently agreed to take on a new position of DEI Lead for the journal. In that role, Rola will continue her proactive efforts to keep Medical Education moving in the right direction while liaising with various others to take advantage of synergies where they can be found. One such synergy has already arisen as we will soon begin trialling an innovation used by Neera Jain in her teaching of critical appraisal: Adding a box to our review form that requests comment from peer reviewers regarding whether submissions engage with human difference and/or power structures in a manner that is appropriate for the focus of the article. I am also thrilled to announce this issue to be the first to include a new section in the journal dedicated to sharing ideas about educational developments in diverse corners of the globe. Consider it Extra Really Good Stuff because our indefatigable Really Good Stuff (RGS) Editor, Brownie Anderson, has scoured submissions to isolate a few that reflect intriguing innovations from under-represented areas. This first batch contains articles from Bahrain, Brazil, India, Israel, Korea, Mexico, Pakistan, and Sierra Leone that focus on issues including multicultural experiences in global classrooms,12 contraception training,13 and team-based learning.14, 15 Additional good news for authors is that those wishing to be included in this section in future issues need not submit to a separate competition as we will continue to try to identify papers that fit well from the pool of RGS papers received during the standard May 1 and November 1 deadlines. To enable any such initiatives, we must thank the incredible team of reviewers who so admirably enable the journal's contents to be curated. Each year, we isolate a few (from far too many exceptional individuals) for special commendation with our Choice Critics Awards. Recognized for going above and beyond the call of duty in 2021 are Mercedes Carreras (Yale University, USA), José Maia (Universidade Federal de Sao Paulo, Brazil), Glenn Regehr (University of British Columbia, Canada), Joshua Strange (Salford Royal NHS Foundation Trust, UK), and Dale Sheehan (University of Otago, New Zealand). Joining them as 2022 award winners are Maggio, Costello, Norton, Driessen, and Artino whose work entitled, Scoping reviews in medical education: A scoping review, received the Silver Quill Award for most downloaded article16; Matthew, Eftychiou, French, and Hare whose article, ‘Just in time’ rapid learning during COVID-19, received the Henry Walton Prize for most downloaded Really Good Stuff paper.17 In addition, we are pleased to announce that Katherine Moreau has won the Medical Education Developing Scholarship Award and that July 2022 witnessed the entry of our 10th cohort of editorial interns, which includes Helen Church (University of Nottingham, UK), Lynelle Govender (University Cape Town, South Africa), and Benjamin Kinnear (University of Cincinnati, USA). Congratulations to each individual listed, the reviewers and editors who supported them, and the local teams with whom they do their work. Kevin W. Eva Editor-in-chief
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,038 | 0,196 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,010 |
| Communication savante | 0,026 | 0,031 |
| Science ouverte | 0,004 | 0,008 |
| Intégrité de la recherche | 0,019 | 0,037 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,041 | 0,037 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».