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Courtesy stigma: a hidden health concern among front‐line service providers to sex workers

2011· article· en· W1955627360 on OpenAlexafffundabout
Rachel Phillips, Cecilia Benoit, Helga Kristín Hallgrímsdóttir, Kate Vallance

Bibliographic record

VenueSociology of Health & Illness · 2011
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsCourtesyStigma (botany)Social workSocial stigmaSocial psychologyHealth carePsychologyMedicineFamily medicinePsychiatryPolitical science

Abstract

fetched live from OpenAlex

Courtesy stigma, also referred to as 'stigma by association', involves public disapproval evoked as a consequence of associating with a stigmatised individual or group. While a small number of sociological studies have shown how courtesy stigma limits the social support and social opportunities available to family members of stigmatised individuals, there is a paucity of research examining courtesy stigma among the large network of people who provide health and social services to stigmatised groups. This article presents results from a mixed methods study of the workplace experiences of a purposive sample of workers in a non-profit organisation providing services to sex workers in Canada. The findings demonstrate that courtesy stigma plays a role in workplace health as it shapes both the workplace environment, including the range of resources made available to staff to carry out their work activities, as well as staff perceptions of others' support. At the same time, it was evident that some workers were more vulnerable to courtesy stigma than others depending on their social location. We discuss these results in light of the existing literature on courtesy stigma and conclude that it is an under-studied determinant of workplace health among care providers serving socially denigrated groups.

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)0.004
metaresearch head score (Gemma)0.015
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 score0.097
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.006
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.123
GPT teacher head0.418
Teacher spread0.294 · 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

Citations98
Published2011
Admission routes3
Has abstractyes

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