“I feel like I am surviving the health care system”: understanding LGBTQ health in Nova Scotia, Canada
Bibliographic record
Abstract
BACKGROUND: Currently, there is a dearth of baseline data on the health of lesbian, gay, bisexual, transgender, and queer (LGBTQ) populations in the province of Nova Scotia, Canada. Historically, LGBTQ health research has tended to focus on individual-level health risks associated with poor health outcomes among these populations, which has served to obscure the ways in which they maintain their own health and wellness across the life course. As such, there is an urgent need to shift the focus of LGBTQ health research towards strengths-based perspectives that explore the complex and resilient ways in which LGBTQ populations promote their health. METHODS: This paper discusses the findings of our recent scoping review as well as the qualitative data to emerge from community consultations aimed at developing strengths-based approaches to understanding and advancing LGBTQ pathways to health across Nova Scotia. RESULTS: Our scoping review findings demonstrated the lack of strengths-based research on LGBTQ health in Nova Scotia. Specifically, the studies examined in our scoping review identified a number of health-promoting factors and a wide variety of measurement tools, some of which may prove useful for future strengths-based health research with LGBTQ populations. In addition, our community consultations revealed that many participants had negative experiences with health care systems and services in Nova Scotia. However, participants also shared a number of factors that contribute to LGBTQ health and suggestions for how LGBTQ pathways to health in Nova Scotia can be improved. CONCLUSIONS: There is an urgent need to conduct research on the health needs, lived experiences, and outcomes of LGBTQ populations in Nova Scotia to address gaps in our knowledge of their unique health needs. In moving forward, it is important that future health research take an intersectional, strengths-based perspective in an effort to highlight the factors that promote LGBTQ health and wellness across the life course, while taking into account the social determinants of health.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".