Problematizing transitions in relation to correctional centres for people living with HIV: Unpacking the taken for granted.
Bibliographic record
Abstract
Transitions into and out of correctional facilities for people living with HIV are a pivotal point in the HIV treatment cascade where adherence metrics are significantly affected. In this paper I use Alvesson and Sandberg’s problematization method of literature analysis to critique and understand the taken-for-granted assumptions underpinning how knowledge is generated within the intersecting fields of HIV, transitions, and corrections. Utilizing problematization, two assumptions underpinning knowledge generation are identified: the linearity of the HIV care continuum model and the tendency to create and perpetuate spatially segregating metaphors of transitions inside versus outside correctional facilities for people living with HIV. These assumptions are discussed in the context of how they shape dominant ways of thinking and practicing in the field. An alternative way to understand transitions for people living with HIV is proposed along with recommendations to guide the HIV care practices of nurses and other healthcare providers.
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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 | 0.027 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.024 | 0.077 |
| Scholarly communication | 0.018 | 0.028 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".