Exploring Food and Nutrition Programming for People Living With HIV/AIDS: Interviews With Service Providers in Nova Scotia, Canada
Bibliographic record
Abstract
There is a lack of nutritional programming and resources available for people living with HIV/AIDS (PLWHA) in Nova Scotia, Canada. This is problematic for several reasons, including that adequate food and nutrition knowledge is integrated to effective medical therapy and wellness for PLWHA. The aim of this research was to explore and describe the beliefs, values, and experiences of HIV-service providers involved programming for PLWHA in Nova Scotia. Using a post-structuralist lens, semi-structured interviews were conducted with nine service providers. Thematic analysis of interview transcripts identified four main themes: (1) recognizing the social determinants of health, (2) acknowledging and disrupting layered stigma, (3) understanding the commensality, and (4) navigating and utilizing networks of care. These findings suggest that those developing, delivering, and evaluating food and nutrition-related programming must engage in community-inclusive approaches that recognize the varied social determinants of health that shape the lived of PLWHA, leverage existing networks and resources, and actively disrupt layered stigma. Also, in agreement with existing evidence, participants stressed the value of communicating and supporting the practice of eating together (commensality) and cultivating networks of care.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".