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Record W3158077681 · doi:10.1177/00208728211004676

HIV/AIDS knowledge and attitudes among social work students: A comparative study

2021· article· en· W3158077681 on OpenAlexaffabout
Óscar Labra, Augustin Ependa, Isis Chamblás, Gabriel Gingras-Lacroix, André Antoniadis, Cristine Biston, Marthe Mukeshimana, Marie-Ève Giroux

Bibliographic record

VenueInternational Social Work · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)CurriculumSocial workPsychologyWork (physics)Sample (material)Medical educationGerontologyMedicineSociologyPedagogyFamily medicinePolitical science

Abstract

fetched live from OpenAlex

The article describes a quantitative cross-sectional study of a sample of 674 university students enrolled in social work programmes in four countries: Belgium, Canada, Chile and Switzerland. The study aimed to assess HIV/AIDS knowledge and attitudes among participants. The median HIV-KQ-18 score for the sample was 14.0, which Carey and Schroder classify as indicating borderline low levels of knowledge. Based on the results, the authors argue that social work education and training programmes should more comprehensively address HIV/AIDS within their curricula to better equip future social workers to challenge stigmatising and exclusionary practices rooted in long-standing lack of knowledge and erroneous beliefs about the disease.

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)0.002
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.068
GPT teacher head0.452
Teacher spread0.384 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

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