15 2020 CaRMS Residency Match Confirms Popularity of Pediatrics
Notice bibliographique
Résumé
Abstract Primary Subject area Medical Education Background Longitudinal data about the interest in, and competitiveness of, pediatric postgraduate training in Canada has not been reported. Objectives 1. To describe the results of the 2020 CaRMS pediatric residency match with respect to application rates, first-choice discipline choices, and succesful match rates by gender. 2. To examine the trend of these indices over the past decade. Design/Methods Data from the 2020 Canadian Residency Matching Service (CaRMS) pediatric residency match was evaluated and compared over the past decade. Residency match data from other programs was also used for some comparison reporting. Results Of a total pool of 2998 Canadian medical graduate (CMG) applicants in 2020, 305 (10.2%) applied to pediatrics, and 17 of these latter applicants (5.6%) applied solely to pediatrics. In the first iteration CaRMS match, pediatrics was the first-choice discipline for 177 CMG applicants (6.0% of all first choices). Pediatrics has been consistent as a first-choice discipline over the years: 5.9% (2017), 5.5% (2015), and 6.1% (2013). Of the 155 first-year positions offered in pediatrics this year, all were filled. Of those CMGs who matched to pediatrics in 2020, the specialty was the first-choice discipline for 128 applicants (92.8%) and the second-choice discipline for 9 applicants (6.5%). There were clear gender differences noted. Pediatrics accounted for 8.3% of female and 3.2% of male first-choice disciplines. Of the 135 females whose first-choice discipline was pediatrics, 101 matched to that first choice (74.8%). Of the 41 males whose first-choice discipline was pediatrics, 26 matched to that first choice (63.4%). Since 1995 (at CaRMS’ inception), the rates of first-choice discipline choice by gender have been quite stable (Table 1), with females consistently higher than males, while the first-choice discipline matching rate by gender have varied (Figure 1). Forty CMG applicants whose first-choice discipline was pediatrics matched to an alternate discipline choice and nine went unmatched, suggesting that pediatrics continues to be a competitive discipline. The pediatric rate of first-choice discipline matching to another alternate choice of 22.6% (40/177) is comparable to Anesthesia (22.1%; 34/154), Ophthalmology (26.7%; 20/75), and Otolaryngology (20.9%; 9/43). Conclusion Pediatrics continues to be a top specialty choice for graduates of Canadian medical schools, according to data from the 2020 CaRMS match. There are gender differences noted in the choice of pediatrics as a first-choice discipline, and in the successful match rate to pediatrics programs. The rate of successful first-choice discipline matching by gender have varied over time, with the past two years showing significantly greater matching success for females. These trends in the CaRMS pediatric data have implications on discipline recruitment and the pediatric workforce in Canada, and merit further exploration.
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 | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
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 ».