Notice bibliographique
Résumé
Dear Sir, I thank Dr. Damant for her letter and will attempt to address some of the points that have been raised. First, I would like emphasize that the President's Message does not represent the views of the CVMA on gender issues in veterinary medicine. I developed the President's Message after reviewing the body of veterinary literature on this topic. I agree that incomes of men and women in the veterinary profession are less than optimal, and women are faring less well than men in this regard. A 2000 CVMA National Survey of Graduates (1997, 1998, 1999 Canadian veterinary graduates) revealed that the average annual salary of female graduates working an average of 1980 h/y was $45 000 (22.22/h) and that of male graduates at 2055 h/y was $50 000 ($24.46/h). The trend in compensation differences by gender persisted by practice type and by seniority ( 2 y out), excepting for associates 2 y postgraduation. Similarly, the Brakke Management and Behavior Study (1) conducted in the United States in 1998 revealed that women with the same ownership status, years of experience, and hours worked earned dramatically less than their male counterparts. I disagree that feminization is occurring to a lesser degree in the veterinary profession than in human medicine and dentistry. Women comprise 50% to 60% of medical students in the United States and Canada today and 50% of students in most Canadian dental schools (2,3). In contrast, many veterinary colleges (including some in Canada) report that close to 80% of their student population is female. I agree that men, on average, may have lower academic grades than women. However, in my experience and in that of other associate deans across North America, men compete well when they choose to apply for admission to veterinary colleges. The proportions of men and women in the applicant and admitted pools are almost identical, but men are not applying to veterinary colleges in the same proportions. I did not state that men are not caring or nurturing, neither did I categorically state that the caring and nurturing aspects of the profession have been enhanced by the increased participation of women in the profession. My statement reads “...may have been enhanced.” The CVMA has been devoting considerable resources and energy towards improving the economic well being of the veterinary profession in Canada through its National Benchmarking Program, as part of its priority, The Successful Practice of Veterinary Medicine.
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 distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».