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Record W2021851172 · doi:10.1177/109019810002700407

Using Communicative Action in the Primary Prevention of Cancer

2000· review· en· W2021851172 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 Education & Behavior · 2000
Typereview
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsOkanagan University CollegeInterior Health
Fundersnot available
KeywordsPrimary preventionHealth promotionCancer preventionAction (physics)Health educationPublic healthPromotion (chess)Communicative actionPsychologyDisease preventionMedicineDiseaseCancerPolitical scienceNursingEnvironmental healthSociology

Abstract

fetched live from OpenAlex

The primary prevention of disease, including cancer, has been a major part of health promotion and health education for decades. However, the long-term results of these strategies have been mixed, and primary prevention as an instrument of cancer control continues to fail to live up to either public or professional expectations. The authors identify and critique two possible factors contributing to this failure and then offer a model for the development and implementation of primary prevention strategies that addresses these factors. The model used is based on Habermas's theory of communicative action and recognizes the importance of a critical dialogue in health education and health promotion. The primary prevention programs currently being conducted by the Cancer Centre for the Southern Interior are presented as an example of the model in action.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.006
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.946
GPT teacher head0.822
Teacher spread0.124 · 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