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Record W7007901188

“Adding that Little Extra Something to Client Care”: Employment Experiences of Lesbian Health Care Workers

2022· dissertation· en· W7007901188 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2022
Typedissertation
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHeteronormativityLesbianSexual orientationHealth careQueerHeterosexualityHeterosexismSexual identityIdentity (music)
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines how lesbian health care workers manage and navigate their sexual identity, taking into consideration experiences of discrimination or acceptance resulting from both organizational policies and individual action, as well as the relationship between the sexual orientation of lesbian health care workers and their ability to provide care. The study draws on in-depth interviews with lesbian health care workers in the Waterloo Region and in Guelph and Wellington County. Five main themes form the core of the analysis: roles and performativity; organizational support and inclusion; disclosure and identity management; heteronormative culture; and impact of COVID-19. Research and analysis are guided by an intersectional lens (Collins 1986; McCall 2005), which recognizes how social categories are inherently intertwined and build on one another to create inequalities. The thesis also engages with queer theory to address the heteronormativity and compulsory heterosexuality present within the health care context.

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)0.006
metaresearch head score (Gemma)0.008
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 score0.028
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0280.013
Scholarly communication0.0080.004
Open science0.0020.009
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.041
GPT teacher head0.343
Teacher spread0.302 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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