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Record W2747216970 · doi:10.2196/publichealth.7812

Vulnerable Youth as Prosumers in HIV Prevention: Studies Using Participatory Action Research

2017· article· en· W2747216970 on OpenAlexvenueno aff
Cath Conn, Shoba Nayar, Dinar Saurmauli Lubis, Carol Maibvisira, Kristel Modderman

Bibliographic record

VenueJMIR Public Health and Surveillance · 2017
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
FundersDepartment of Foreign Affairs and Trade, Australian Government
KeywordsHuman immunodeficiency virus (HIV)Participatory action researchAction (physics)Environmental healthCitizen journalismPsychologyMedicineInternet privacyComputer scienceEconomic growthVirologyEconomicsWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Stigma, voicelessness, and legislative and rights barriers, coupled with top-down decision making, are the common experiences of vulnerable youth populations that limit their opportunities to participate in vital health promotion efforts such as HIV prevention. OBJECTIVE: To consider new opportunities arising from a digital society for youth to creatively shape HIV prevention. METHODS: Drawing on research with vulnerable youth in Busoga, Uganda; Bulawayo, Zimbabwe; Bangkok, Thailand; and Bali, Indonesia, we explore current youth participation, in theory and practice, while considering new opportunities arising from a digital society for youth to creatively shape HIV prevention. RESULTS: Collaborative commons and prosumer models are defined as people employing new technology to codesign toward a common goal. Within the context of a diminishing role of the traditional institution and the rise of digitized networks, such models offer exciting new directions for youth as electronic health promotion prosumers to participate in difficult challenges such as HIV prevention in the 21st century. CONCLUSIONS: It is time for institutions to embrace such opportunities, especially in areas where access to technology is widening, while continuing to champion youth and advocate for supportive social environments.

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)0.048
metaresearch head score (Gemma)0.038
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 score0.048
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0090.010
Scholarly communication0.0070.007
Open science0.0020.011
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.587
GPT teacher head0.522
Teacher spread0.065 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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