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Record W2147108810 · doi:10.1177/1757975909348101

High school health curriculum and health literacy: Canadian student voices

2009· article· en· W2147108810 on OpenAlexaffabout
Deborah L. Begoray, Joan Wharf-Higgins, Marjorie MacDonald

Bibliographic record

VenueGlobal Health Promotion · 2009
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCurriculumHealth promotionHealth literacyHealth educationRelevance (law)Medical educationFocus groupHealth informationMedicinePsychologyPedagogyPublic healthNursingHealth careSociologyPolitical science

Abstract

fetched live from OpenAlex

This study explores the relevance of health literacy, and its development through a health curriculum, as a necessary but insufficient component to facilitate healthy living among adolescents through comprehensive school health models. This paper presents qualitative findings from focus groups with students (N = 33) in four schools toward the end of their experience in a health class that focused on topics related to healthy living, healthy relationships, health information and decision-making. Students reported mostly negative experiences citing repetitive course content, routinely delivered by teachers and passively received by students. As well, students described their experiences of using health information sources beyond the classroom, such as the media. The findings suggest that the curriculum, and particularly its implementation, have had limited effect on health literacy: students' abilities to access, understand, communicate and evaluate health information. The paper concludes with recommendations for improving health education.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0100.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.043
GPT teacher head0.498
Teacher spread0.455 · 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

Citations76
Published2009
Admission routes2
Has abstractyes

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