Bibliographic record
Abstract
The current investigation seeks to examine the attitudes and beliefs of health care providers in Canada about people living with HIV. The line of research consists of three studies. Study 1 was a qualitative study conducted with a critical lens. The critical lens was used in a series of four focus groups when qualitatively soliciting opinions about the range of attitudes, behaviours and cognitions health care providers may have towards people living with HIV. Study 2 used the information gathered from Study 1 to develop a scale to assess HIV stigma in health care providers. Items were created from examples and themes found in the qualitative study, and were tested via exploratory factor analysis, confirmatory factor analysis, test-retest reliability analysis, and assessed for convergent and divergent validity. Study 3 examined the newly developed scale’s relationship to proposed overlapping stigmas and attitudes, and tested the adapted intersectional model of HIV-related stigma with health care trainees using the newly developed HIV stigma scale as an outcome measure. The line of research found that HIV stigma continues to be a significant problem in the health care system. The scale developed in Study 2 demonstrates that HIV stigma can be conceptualized and assessed as a tripartite model of discrimination, stereotyping and prejudice, and that this conceptualization of HIV stigma supports an intersectional model of overlapping stigmas with homophobia, racism, stigma against injection drug use and stigma against sex work.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 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".