In Response: Women Leadership in Liver Transplantation
Notice bibliographique
Résumé
We thank Choubey et al1 for the letter regarding our article on women leadership in liver transplantation (LT).2 We are glad to hear that other institutions also have conducted analysis on this important topic alongside the International Liver Transplantation Society Equality, Diversity, and Inclusion Committee, aiming to gain further understanding on the gender gap within the field of transplantation. We agree that identifying the current gender composition of transplant programs is only the first step on recognizing the current paradigm. The causes of the gender leadership gap in LT are complex and mutifactorial, complicated by various cultural norms in different countries, institutions, and medical specialties. In addition to providing women physicians the access to leadership positions, advocacy for women in LT requires the elimination of the gender gap in professional promotion and compensation.3 Providing women physicians the access to leadership positions is not simply having men put women in leadership positions as “tokens” to meet the diversity quota. To assist with creating gender neutrality in leadership roles, medical institutions should remove present barriers as different perceived higher standard of performance from women physicians and preference for men due to gender similarity in promotion decisions. Removing gender specificity on the labels of leadership roles, such as changing the title from “Chairman” to a gender neutral “Chair” or “Chairperson,” can be a basic start. For academic promotion, data have shown disparities in the experiences of men and women. Women often must produce far more than men to achieve promotion.4 A clear promotional criteria should be established and consistently utilized to rate academic performance equally for both genders. Women physicians should also seek clarity on which scholar activities have higher impacts in the promotional process, focusing their time and effort on those tasks with higher promotional values. Recent studies continue to find compensation differences between men and women physicians, even after adjusting for multiple factors including, but not limited to, age, experience, work hours, years in practice, productivity, and academic rank.5 The gender pay gap remained and widened over the course of a woman physician’s career.3,5 Equitable physician compensation based on comparable work with transparency and routine assessment of the equity on pay may mitigate the gender pay gap.5 Although the field of medicine continues its efforts on improving equality and equity, women physicians should also actively seek educational programs in negotiation, training in career and leadership development, mentorships and sponsorships, and opportunities in networking. Gender equality and equity can only be achieved if women physicians continue to advocate for themselves and be the change. We hope our article brings awareness to the gender leadership gap and further strengthens the movement of gender equity and equality in the field of LT.
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 | 0,006 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,004 | 0,007 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,037 | 0,043 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,006 |
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 ».