Counselling about <scp>HIV</scp> serological status disclosure: nursing practice or law enforcement? a Foucauldian reflection
Bibliographic record
Abstract
Recently, focus groups and qualitative interviews with nurses who provide frontline care for persons living with HIV highlighted the contentiousness surrounding the seemingly innocuous activity of counselling clients about HIV-status disclosure, hereafter disclosure counselling. These empirical studies highlighted that while some nurses felt they should instruct clients to disclose their HIV-positive status if HIV transmission were possible, other nurses were equally adamant that such counselling was outside the nursing scope of practice. A review of these opposing perceptions about disclosure counselling, including an examination of the empirical evidence which supports each point, revealed that the dichotomous arguments needed to be nuanced. The empirical evidence about serostatus disclosure neither supported nor refuted either of these assertions; rather, it substantiated parts of each. To create this understanding, both empirical and theoretical works are used. First, the results of empirical studies about serostatus disclosure, or lack thereof and HIV transmission is presented; as part of this, Marks and Crepaz's HIV disclosure and exposure framework is examined. Second, the work of Michel Foucault on disciplinary and pastoral power is drawn from. The outcome is a nuanced understanding about the interrelationships between disclosure counselling and nursing practice and a final interpretation about what this understanding means for public health practice.
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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 | 0.047 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.067 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.010 | 0.017 |
| 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".