Identification with community‐based HIV agencies as a correlate of turnover intentions and general self‐efficacy
Bibliographic record
Abstract
Abstract Research ( e.g . French, Power, & Mitchell, 2000 ; Harris, 2006 ; Harris & Alderson, 2006 , 2007 ; Roy & Cain, 2001 ) has highlighted important benefits for people living with HIV/AIDS to become connected with HIV community‐based (CB) agencies ( e.g . reduction of isolation, educational opportunities, empowerment). However, CB HIV organizations sometimes experience challenges in recruiting and retaining people living with HIV/AIDS. In a sample of 68 respondents associated with a Canadian HIV/AIDS CB agency, facets of agency identification were examined as correlates of (a) turnover intentions with the agency and (b) aspects of psychological adjustment (hope and general self‐efficacy). Results indicated one dimension of social identification, in‐group affect, as a significant correlate of turnover intentions (such that members with more positive agency‐derived feelings were more likely to say they would stay at the agency), and another emotionally‐relevant aspect of identification, in‐group ties, as a significant correlate of general self‐efficacy. Hope was unrelated to social identification. Several implications for HIV CB agencies are discussed. Copyright © 2010 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".