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Record W2033479895 · doi:10.1080/13691058.2010.508844

Inclusion and exclusion in mid-life lesbians' experiences of the Pap test

2010· article· en· W2033479895 on OpenAlexafffundabout
Lynn McIntyre, Andrea Szewchuk, Jenny Munro

Bibliographic record

VenueCulture Health & Sexuality · 2010
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsInclusion (mineral)PsychologyTest (biology)Social exclusionInclusion and exclusion criteriaSociologyGender studiesSocial psychologyMedicinePolitical scienceAlternative medicine

Abstract

fetched live from OpenAlex

Lesbians are said to feel excluded by sexual health messages that presume heterosexuality, a finding linked to lower levels of Papanicolaou (Pap) testing. This paper discusses a small, focused qualitative study based in Calgary, Canada that illuminated mid-life lesbians' experiences and perceptions of Pap testing and health. Participants indicated that they felt compelled and invited to access Pap testing by an inclusive discourse - that of 'mid-life', a period associated with an increased need for body surveillance. They also reflected upon aging as an experience of liberation, increased confidence and a time when they could 'catch up' on health and sexuality issues denied them in their younger days. On the other hand, there was significant uncertainty about Pap testing, human papillomavirus (HPV), cervical cancer and what kind of sexual healthcare is necessary for lesbians, which was reinforced by physician messages suggesting a reduced need for Pap testing when lesbian sexual identity was disclosed. In approaching mid-life lesbian healthcare, we suggest that greater analytical attention should be paid to the ways in which lesbian women are included, as much as excluded, in dominant sexual health scripts particularly by health providers who need to attend to women's diverse experiences and needs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.411
Teacher spread0.372 · 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.

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

Citations29
Published2010
Admission routes3
Has abstractyes

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