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Record W2170910445 · doi:10.1177/104973201129119253

Social Constructions of Femaleness in Writing about Cancer

2001· article· en· W2170910445 on OpenAlexaff
Barbara Hanson

Bibliographic record

VenueQualitative Health Research · 2001
Typearticle
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsYork University
Fundersnot available
KeywordsObjectificationBiomedicineQualitative researchPsychologyMEDLINEMasculinityGender studiesSocial psychologySociologyEpistemologyBioinformaticsBiologySocial sciencePhilosophy

Abstract

fetched live from OpenAlex

This article uses a qualitative content analysis of writing about cancer since 1900, with numeric summaries from Medline/PubMed searches, to propose that there is an implicit reliance in biomedicine on the idea that femaleness is pathological hence carcinogenic. Numeric summaries of rates of use of search terms for men and women and their sexual attributes are a backdrop for text sources that illustrate a greater tendency to see women in sexual terms and pathologize aspects of femaleness. This even extends into more frequent use of the term estrogen than testosterone in exclusively male cancer sites such as prostate and testicle. The analysis suggests that female focus and pathologization of femaleness come from social sex differentiation, heterosexual bias, and objectification of women as sex objects. This may be detrimental to both women and men because these social constructions may have focused cancer research on social classifications that are not physically relevant.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.240
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.807
GPT teacher head0.729
Teacher spread0.077 · 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 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

Citations8
Published2001
Admission routes1
Has abstractyes

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