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Record W1984014710 · doi:10.1300/j013v38n04_05

Feminism and Women's Health Professions in Ontario

2003· article· en· W1984014710 on OpenAlexaffabout
Tracey L. Adams, Ivy Lynn Bourgeault

Bibliographic record

VenueWomen & Health · 2003
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsMcMaster UniversityWestern University
Fundersnot available
KeywordsFeminismIdeologyGender studiesSociologyBattleOpposition (politics)InequalityFraming (construction)Health carePolitical sciencePoliticsLawEngineering

Abstract

fetched live from OpenAlex

Historically, prevailing gender ideologies were an important element in both the exclusionary strategies employed by male occupational groups and the countervailing responses by female groups. The way in which evolving gender ideologies, and feminism in particular, influence the continuing struggle for greater status and recognition by female professions, however, remains to be fully explored. In this paper, we examine the impact and the role of feminism and feminist ideologies within three female professional projects: nursing, dental hygiene and midwifery in Ontario. We argue that feminism provides an ideology of opposition that enables leaders in these professions to battle against professional inequalities by laying bare the gender inequalities that underlie them. Framing their struggles in feminist terms, female professions also seek recognition for the uniquely female contribution they make to the health care division of labour. At the same time, there exists a tension between ideals of feminism and ideals of professionalism, that has the potential to undermine female professional projects.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.604

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0160.006
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.078
GPT teacher head0.438
Teacher spread0.360 · 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 designQualitative
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
Published2003
Admission routes2
Has abstractyes

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