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Record W2793266639 · doi:10.1177/0008417417728524

What about the men? Gender parity in occupational therapy

2018· article· en· W2793266639 on OpenAlexvenueno aff
Brenda L. Beagan, Erin Fredericks

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2018
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMasculinityParity (physics)Equity (law)Gender equityPrestigePay EquityPsychologyLevel playing fieldDemographic economicsLabour economicsGender studiesPolitical scienceSociologyEconomicsFinance

Abstract

fetched live from OpenAlex

BACKGROUND: Gender parity is frequently raised as an equity issue in occupational therapy, with strategies proposed to recruit more men. PURPOSE: This article explores whether this is a legitimate equity concern. KEY ISSUES: Most employment is gender segregated; when gender balances change, the field either re-genders feminine or creates gender-segregated internal divisions. Men avoid feminized jobs because they pay less and hold less social status. They are a "step down" for men. In such jobs, men are disproportionately pushed into management positions, with better pay, more prestige, and less hands-on care. Equity issues concern structural barriers to success in particular employment fields. Though they may feel discomfort in a feminized field, men do not face structural barriers in occupational therapy. IMPLICATIONS: Broader challenges to traditional gender norms are needed, but there is no evidence that gender parity is an equity concern or that recruitment targeting masculinity would make a difference.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.013
Scholarly communication0.0060.008
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.484
GPT teacher head0.549
Teacher spread0.065 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations23
Published2018
Admission routes1
Has abstractyes

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