MétaCan
Menu
Back to cohort
Record W2115890121 · doi:10.1177/1524839908328990

Health Promotion and Illness Demotion at Prostate Cancer Support Groups

2009· article· en· W2115890121 on OpenAlexafffundabout
John L. Oliffe, Julieta S. Gerbrandt, Joan L. Bottorff, T. Gregory Hislop

Bibliographic record

VenueHealth Promotion Practice · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsBC Cancer AgencyUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsDemotionHealth promotionMasculinitySociology of health and illnessPerspective (graphical)Embodied cognitionPromotion (chess)Prostate cancerMedicinePsychologyHealth careGerontologyNursingCancerPublic healthPolitical science

Abstract

fetched live from OpenAlex

Although health promotion programs can positively influence health practices, men typically react to symptoms, rather than maintain their health, and are more likely to deny than discuss illness-related issues. Prostate cancer support groups (PCSGs) provide an intriguing exception to these practices, in that men routinely discuss ordinarily private illness experiences and engage with self-health. This article draws on individual interview data from 52 men, and participant observations conducted at the meetings of 15 groups in British Columbia, Canada to provide insights to how groups simultaneously facilitate health promotion and illness demotion. The study findings reveal how an environment conducive to men's talk was established to normalize prostate cancer and promote the individual and collective health of group members. From a gendered perspective, men both disrupted and embodied dominant ideals of masculinity in how they engaged with their health at PCSGs.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.004
Scholarly communication0.0020.001
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.061
GPT teacher head0.417
Teacher spread0.356 · 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

Citations36
Published2009
Admission routes3
Has abstractyes

Explore more

Same venueHealth Promotion PracticeSame topicGender Roles and Identity StudiesFrench-language works237,207