Bibliographic record
Abstract
This article describes the explanatory model of human immunodeficiency virus (HIV) illness used by aboriginal women in northern Alberta. Using Kleinman's explanatory model framework, eight women who were HIV positive were interviewed to determine their perspectives on the etiology, pathophysiology, symptomology, course of illness, and methods of treatment for HIV. A comparative analysis was done between the explanatory model of HIV illness as described by participants and the conventional biomedical paradigm of HIV disease. As described by aboriginal women, several aspects of the explanatory model of HIV were congruent with the biomedical paradigm. It was also found that the findings related to etiology and treatment of HIV illness was incongruent with the conventional biomedical paradigm of HIV disease. These findings highlight the relevance of knowing models of illness for health care professionals, particularly nurses who work in communities with a high incidence of HIV/AIDS. These models make care planning of patients with HIV and AIDS more focused and directed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".