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Record W2115039943 · doi:10.1177/1524839906289166

The Novella Approach to Inform Women Living on Low Income About Early Breast Cancer Detection

2006· article· en· W2115039943 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Promotion Practice · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsAlberta Health ServicesSouth Health Campus
Fundersnot available
KeywordsBreast cancerDisadvantagedNovellaMedicineHealth careHealth promotionCommunity healthGerontologyCancerPublic healthNursingEconomic growth

Abstract

fetched live from OpenAlex

Economically disadvantaged women have a greater likelihood of later-stage breast cancer diagnosis when compared to women with higher levels of income. Later-stage diagnosis decreases the chances of survival. The purpose of this article is to describe a project whereby breast cancer survivors, living on lower incomes, created novellas (stories) using artistic media to reach their peers with a message about the importance of early breast cancer detection. The recruitment and engagement of breast cancer survivors in a 2-year community development project that used participatory, women-driven approaches are discussed, and the reciprocal learning between health care providers, community partners, and women living on low income is shared. Recommendations for health promotion practice are presented.

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.

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)0.019
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
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 head0.307
GPT teacher head0.597
Teacher spread0.290 · 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