Women and HIV Care in New Brunswick and Nova Scotia, Canada
Bibliographic record
Abstract
This study explores the barriers to care women face living with HIV in New Brunswick and Nova Scotia, and also the health and support systems they navigate to improve their wellbeing. Women living with HIV are invisible within the epidemic and often to community sector employees, especially in the Maritime Provinces where men account for the largest number of diagnoses in Canada; this is a central theme in the data. The thesis is rooted in applied medical anthropology and uses qualitative and quantitative methods to capture the changing health priorities of women living with HIV as they navigate the health care systems after diagnosis. This information was used to create maps that show the availability of services in relation to women’s needs, including affordable housing, food security, accessible transportation, and reducing HIV stigma. I examine the efficiency of HIV women’s referral network in both provinces, and the way forward for organizations to meet their long-term health needs, such as widening of outreach activities and improving gendered care. The main findings of this study reveal that the barriers to care women face are not easily overcome by AIDS service organizations. Current support initiatives are no longer relevant to their lives because they are tailored mainly to men, but women increasingly value the referral activities of organizations. Among the most important contributions of this thesis is the envisioning of a women-centered care model that meets their health needs and acknowledges their diverse reality of their experiences.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".