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Record W4283824862 · doi:10.3138/ptc-2020-0142

Gender Issues in Physiotherapy in Quebec, Canada

2022· article· en· W4283824862 on OpenAlexaffvenueabout
Debbie Ehrmann Feldman, Cassandra Bellavance, David Frédérick, Tomás Gagnon, Charlotte Lalonde, Anne Hudon

Bibliographic record

VenuePhysiotherapy Canada · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsWorkforceMedicineNursingDocumentationMedical educationFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Purpose: This study examines gender differences in the physiotherapy (PT) profession in the province of Quebec regarding: (1) areas of practice; (2) roles associated with the advancement of the profession; (3) formal disciplinary complaints; and (4) interests and competency perceptions of PT students. Methods: We collected data from the Canadian Institute of Health Information, the Quebec Professional Order of Physiotherapy, Quebec university public Internet sites, and PT associations. We also surveyed PT students at the Université de Montréal. Results: The PT workforce in Quebec was 76.6% women. The presidents of the four main PT associations were men. In the five university programmes, the percentage of male and female physiotherapists in tenure track positions was 46% and 54%, respectively. There were more sanctioned complaints of sexual misconduct and not maintaining continuing education for male physiotherapists, while more women were sanctioned for problems with documentation and billing. Among students, men were more interested in becoming administrators, but neither men nor women had a strong interest in research. Conclusions: Male physiotherapists make up 23.4% of the PT workforce in Quebec but are more involved in leadership positions in the profession than women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.290
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2022
Admission routes3
Has abstractyes

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