Notice bibliographique
Résumé
Who is applying and who is being admitted to Ontario Master of Physical Therapy university programs?These are the two important questions that are answered by Coghlan and colleagues' study. 1 This unprecedented review and analysis is long overdue, and Coghlan and colleagues are to be commended for taking a comprehensive, thorough, and reflective approach to comparing Canadian population data with the demographic variables of all applicants to and students of selected Ontario English-language Master of Physical Therapy programs over a 10-year period.The authors are essentially asking (1) are we doing a good job of attracting applicants and admitting students considering provincial and national lenses on population demographics and (2) how can we do better?This study generated some very interesting findings.Aside from physical therapy's being a female-dominated profession, the demographics of applicants and students are mostly representative of the diverse Canadian population, although the data also indicate that the number of Aboriginal applicants does not reflect the Canadian population.From 2004 to 2014, the number of men applying to and being admitted to physical therapy programs significantly increased, which has resulted in an increase in the number of men practising physical therapy.A trend exists wherein the proportion of male students is slightly less than that of male applicants (36% vs. 33%; 2014 data 1 ).I'm interested in learning more about this.What might be some factors that contribute to this trend?For the most part, students applying to English-speaking Master of Physical Therapy programmes come from southern Ontario, typically from large urban population centres, and the proportion of students across geographical regions and population centre size is similar to that of applicants.As Coghlan and colleagues 1 noted, applicants and students from British Columbia outnumber those from all other provinces (other than Ontario); they offer potential explanations for this finding in their Discussion section.Across the 10 years of data, the proportion of total physiotherapy students who self-declared as Aboriginal was slightly higher than the proportion of total applicants who self-declared as Aboriginal.However, the proportion of applicants who self-declared as Aboriginal was less than that in the total population (4.3% in Canada and 2.4% in Ontario).2 The authors offer several potential hypotheses for this difference and also identify it as an area for future research.For example, should universities engage with Aboriginal communities to explore the potential of increasing efforts to recruit Aboriginal students to apply to Ontario physiotherapy programs, or should they specifically reserve seats for those who self-declare as Aboriginal and meet the entrance requirements?Efforts to increase the proportion of self-declared Aboriginal physical therapy students to match their proportion of the national population would also match the recommendations of Honouring the Truth, Reconciling for the Future: Summary of the Final Report of the Truth and Reconciliation Commission of Canada 3 that strategies be developed to eliminate education and employment gaps between Aboriginal and non-Aboriginal Canadians and to increase the number and retention of Aboriginal professionals working in the health care field.
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 | 0,005 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,005 | 0,002 |
| Intégrité de la recherche | 0,049 | 0,042 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,009 |
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 ».