THE REQUIRMENTS FOR THE DEGREE OF
Bibliographic record
Abstract
For those living in resource rich countries such as Canada a positive HIV diagnosis no longer means an imminent death. In response to this change, numerous treatment and therapeutic institutions have arisen to assist individuals with managing their illness. Illness narratives then, the stories people tell and retell about their illness experience, are constructed by and within this multiplicity of medical frameworks that can interact in ways that are both complimentary and contradictory. Drawing on ethnographic data obtained through two months of participant observation and seven in-depth interviews at an HIV/AIDS treatment facility in Vancouver, British Columbia I discuss how illness narratives reveal the presence of and an orientation towards the powerful discourses of medicine. Some of the frameworks evident in the narratives I examine include biomedical understandings of health and disease, support group dialogues on self-empowerment, tenets of complementary and alternative medicines, clinical models of low-threshold access to health care, notions of health services as a human right, and addiction treatment concepts. In order to afford a place for the institutional discourses of medicine in my analysis, the subjective experience of illness is
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".