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Record W2010865032 · doi:10.1080/17441692.2015.1021365

Workplace interventions to reduce HIV and TB stigma among health care workers – Where do we go from here?

2015· article· en· W2010865032 on OpenAlex
Jacob S. Siegel, Annalee Yassi, Asta Rau, Jane A. Buxton, Edwin Wouters, Michelle Engelbrecht, Kerry Uebel, Letshego E. Nophale

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGlobal Public Health · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsStigma (botany)Psychological interventionWorkforceMedicineHealth careTuberculosisContext (archaeology)Human immunodeficiency virus (HIV)Social stigmaNursingEnvironmental healthFamily medicinePsychiatryPolitical science

Abstract

fetched live from OpenAlex

Fear of stigma and discrimination among health care workers (HCWs) in South African hospitals is thought to be a major factor in the high rates of HIV and tuberculosis infection experienced in the health care workforce. The aim of the current study is to inform the development of a stigma reduction intervention in the context of a large multicomponent trial. We analysed relevant results of four feasibility studies conducted in the lead up to the trial. Our findings suggest that a stigma reduction campaign must address community and structural level drivers of stigma, in addition to individual level concerns, through a participatory and iterative approach. Importantly, stigma reduction must not only be embedded in the institutional management of HCWs but also be attentive to the localised needs of HCWs themselves.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.690
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.404
Teacher spread0.330 · 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