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Record W2097772990 · doi:10.1177/1049732315570125

Youth Perspectives on Sexual Health Workshops

2015· article· en· W2097772990 on OpenAlexafffund
Heather Ashdown, Chelsea Jalloh, John Wylie

Bibliographic record

VenueQualitative Health Research · 2015
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchUniversity of Manitoba
KeywordsPositive Youth DevelopmentPsychologyFocus groupPsychological interventionPerspective (graphical)EmpowermentIntervention (counseling)PsychosocialYouth empowermentReproductive healthCriticismMedical educationApplied psychologyPedagogyDevelopmental psychologySociologyMedicinePolitical sciencePsychotherapist

Abstract

fetched live from OpenAlex

Newcomer and street-involved youth provided their perspective on the design and content of a sexual education workshop. Following the workshop, focus group discussions were held with 80 youth from four youth-serving agencies. Youth expressed increased levels of confidence and empowerment, consistent with recent criticism that a focus on specific behaviors as intervention outcome measures may miss important psychosocial changes in participants. Some youth views on cultural adaptation of workshops were not consistent with current views expressed by some adult educators, highlighting the need to ensure a youth perspective is captured during intervention development. Finally, the dichotomous views that youth expressed regarding workshop activities emphasizes a research gap related to how best to adapt interventions to different cognitive capacities, literacy levels, and learning styles. Information of this kind is relevant in terms of knowledge translation from youth to program planners and educators.

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)0.006
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.861
GPT teacher head0.704
Teacher spread0.157 · 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

Citations15
Published2015
Admission routes2
Has abstractyes

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