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Record W4387086935 · doi:10.1080/09540121.2023.2253505

An evaluation of an employment assistance program focused on people living with HIV in Toronto, Canada

2023· article· en· W4387086935 on OpenAlexafffundabout
Melissa Perri, Ayu Pinky Hapsari, Amy Craig-Neil, Julia Ho, Jessica Cattaneo, Mark Gaspar, Charlotte Hunter, Sergio Rueda, Ann N. Burchell, Andrew D. Pinto

Bibliographic record

VenueAIDS Care · 2023
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsCentre for Addiction and Mental HealthSt. Michael's HospitalAIDS Committee of TorontoUniversity of TorontoCentre for Global Health ResearchPublic Health Ontario
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsOutreachPopulationUnemploymentEthnic groupQualitative propertyProgram evaluationBusinessFamily medicineMedicineGerontologyPsychologyEconomic growthEnvironmental healthPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Unemployment is more common among people living with HIV (PLWH) compared to the general population. PLWH who are employed have better physical and mental health outcomes compared to unemployed PLWH. The main objective of this mixed-methods study was to conduct a program evaluation of Employment Action (EACT), a community-based program that assists PLWH in Toronto, Ontario, Canada to maintain meaningful employment. We extracted quantitative data from two HIV services databases used by EACT, and collected qualitative data from 12 individuals who had been placed into paid employment through EACT. From 131 clients included in the analysis, 38.1% (n = 50) maintained their job for at least 6 weeks within the first year of enrollment in the EACT program. Gender, ethnicity, age, and first language did not predict employment maintenance. Our interviews highlighted the barriers and facilitators to effective service delivery. Key recommendations include implementing skills training, embedding PLWH as EACT staff, and following up with clients once they gain employment. Investment in social programs such as EACT are essential for strengthening their data collection capacity, active outreach to service users, and sufficient planning for the evaluation phase prior to program implementation.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.668
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.367
Teacher spread0.340 · 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 teacher head, 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

Citations0
Published2023
Admission routes3
Has abstractyes

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