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Record W1563136555 · doi:10.18357/ijcyfs.61201513494

IMPROVING SEXUAL HEALTH RESOURCES FOR YOUTH: THE USE OF SEX-POSITIVE PUBLIC HEALTH WEBSITES

2015· article· en· W1563136555 on OpenAlexfundvenueno aff
Clemon George, Robert G. Weaver, Alyssa Higginson, Lindsay Chartier

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchOntario HIV Treatment Network
KeywordsConfidentialityThe InternetReproductive healthAnonymityInternet privacyPsychologyQualitative researchHealth informationTrustworthinessPublic relationsSocial psychologyMedicineEnvironmental healthHealth carePolitical scienceComputer securitySociologyPopulationComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Technologies that bring more information to our fingertips can often mislead and misinform youth about the risks of practising unsafe sex. On the other hand, valid and trustworthy information can promote health and reduce harmful practices by shaping and encouraging safe sex practices. Our qualitative study conducted with 32 youth explored their desire to access sexual health information and services, their perceptions of current sexual health services, and their sources of information. The results of the study indicate that youth are concerned about the accessibility, anonymity, confidentiality, and comfort of sexual health services; and that they identified the Internet as a key source of information, and as the preferred medium for sexual health information. Yet they expressed concern about the quality of information retrieved on the Internet. This indicates that trustworthy sources of youth-friendly health materials on the Internet need to be provided to support youth in making low-risk sexual decisions.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.192
GPT teacher head0.363
Teacher spread0.170 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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