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Record W2050963996 · doi:10.5539/ass.v9n2p129

Rural Secondary School Teachers’ Capacity to Respond to Hiv and Aids: The Case of Shurugwi District in Zimbabwe

2013· article· en· W2050963996 on OpenAlexvenueno aff
Ezron Mangwaya, Emily Ndlovu

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Psychological interventionHuman immunodeficiency virus (HIV)PsychologyQualitative researchWelfarePedagogyPandemicPublic relationsMedical educationSociologyMedicinePolitical scienceCoronavirus disease 2019 (COVID-19)NursingSocial scienceFamily medicine

Abstract

fetched live from OpenAlex

Young people often turn to their teachers for information on sexuality and HIV and Aids. Consequently teachers need to be not only knowledgeable about these issues but also able to integrate them into their teaching. As part of an umbrella study to investigate and promote HIV and Aids education and support in schools, this article reports on a qualitative study conducted among a purposively selected sample of teachers in Shurugwi schools to ascertain their response to the challenges resulting from the pandemic. The findings suggest that the participating teachers held complex and contradictory views about HIV and Aids education; that they were constrained by the prevailing social and cultural background; and that their responses were inhibited by the lack of adequate social welfare support systems. These factors combined to make it difficult for them to interpret and implement policy that calls for a coherent and collaborative response. This study will hopefully inform professional development interventions to ensure that future HIV and AIDS teaching and learning is relevant and effective, given the social and educational context.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.005
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.053
GPT teacher head0.399
Teacher spread0.346 · 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 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

Citations8
Published2013
Admission routes1
Has abstractyes

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