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Record W1992960309 · doi:10.3402/ijch.v63i0.17917

Youth sexual health in Nunavut: a needs based survey of knowledge, attitudes and behaviour

2004· article· en· W1992960309 on OpenAlexaffabout
Madeleine Cole

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2004
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsOttawa Baffin Nunavut Health Services
Fundersnot available
KeywordsReproductive healthConfidentialityPsychological interventionHuman sexualityPsychologyMedical educationPublic healthCitizen journalismHealth promotionHealth educationMedicineEnvironmental healthNursingPolitical scienceGender studiesSociologyPopulation

Abstract

fetched live from OpenAlex

OBJECTIVES: This study attempts to address the need for culturally specific data on beliefs and behaviours in order to design and implement appropriate public health interventions. The goal of the health promotion booklet that followed the study is to give youth a tool that will promote healthy choices and give non-judgmental information about sexuality. STUDY DESIGN AND METHODS: Knowledge gaps and beliefs about birth control, healthy sexuality and sexual health education were assessed through a written survey of young adults in three schools on Baffin Island. The sexual health survey was four pages long and written in simple language. The survey was voluntary, consensual and confidential, and it was administered by teachers. RESULTS: Some of the findings from the Iqaluit high school student survey (n=71) are reported with references to results from a smaller Iqaluit college student group (n=31). CONCLUSIONS: In Nunavut, teen pregnancy and sexually transmitted infection rates exceed national averages and continue to have devastating health and social consequences--particularly for Inuit girls and women. Using the data and a participatory approach, a culturally appropriate, bilingual booklet about sexual health is being developed for Nunavut youth.

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)0.005
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.078
GPT teacher head0.427
Teacher spread0.349 · 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 designObservational
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

Citations15
Published2004
Admission routes2
Has abstractyes

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