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Record W2473639284 · doi:10.18357/ijih111201616011

Sexy Health Carnival on the Powwow Trail: HIV Prevention by and for Indigenous Youth

2016· article· en· W2473639284 on OpenAlexaffvenueabout
Renée Monchalin, Alexa Lesperance, Sarah Flicker, Carmen H. Logie, Native Youth Sexual Health Network

Bibliographic record

VenueInternational Journal of Indigenous Health · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsNative Youth Sexual Health NetworkYork UniversityUniversity of Toronto
Fundersnot available
KeywordsIndigenousOutreachCondomReproductive healthContext (archaeology)Intervention (counseling)Human immunodeficiency virus (HIV)PsychologyGender studiesMedicineSociologyPolitical scienceGeographyFamily medicineEnvironmental healthPopulationPsychiatry

Abstract

fetched live from OpenAlex

Background: This article introduces a peer-led pilot intervention called the “Sexy Health Carnival” (SHC) that takes a strengths-based approach to promoting Indigenous youth sexual health in a culturally safe context. Methods: In 2014, Indigenous youth leaders brought the SHC to 4 Ontario, Canada, powwows, where they administered an offline iPad survey to 154 Indigenous youth (aged 16 to 25) who engaged with the SHC. The survey gathered descriptive data on HIV prevention behaviours and intentions, and the acceptability of the SHC approach in powwow settings. Results: Over one third (40%) of youth thought that “a lot” of sex happens at powwows; 14% reported that they were either “definitely” or “probably” going to “hook up” or be sexual with someone at the powwow, and another 14% were not sure. Among those contemplating sexual activity, 79% said they would use a condom that they received at the SHC. The majority (80%) of youth rated the SHC as “awesome.” Conclusion: This pilot provides preliminary evidence that the SHC is feasible and welcomed by youth in powwow settings. This project illustrates that Indigenous youth are capable of developing successful sexual health outreach and HIV prevention resources for each other.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.356
Teacher spread0.326 · 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.

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

Citations26
Published2016
Admission routes3
Has abstractyes

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