Understanding and Measuring LGBTQ Pathways to Health: A Scoping Review of Strengths-Based Health Promotion Approaches in LGBTQ Health Research
Bibliographic record
Abstract
Health research traditionally has focused on the health risks and deficits of lesbian, gay, bisexual, transgender, and queer (LGBTQ) populations, obscuring the determinants that can promote health across the life course. Recognizing, appropriately measuring, and rendering visible these determinants of health is paramount to informing appropriate and engaging health policies, services, and systems for LGBTQ populations. The overarching purpose of this article is to provide an overview of the findings of a scoping review aimed at exploring strengths-based health promotion approaches to understanding and measuring LGBTQ health. Specifically, this scoping review examined peer-reviewed, published academic literature to determine (a) existing methodological frameworks for studying LGBTQ health from a strengths-based health promotion approach, and (b) suggestions for future methodological approaches for studying LGBTQ health from a strengths-based health promotion approach. The findings of this scoping review will be used to inform the development of a study aimed at assessing the health of and improving pathways to health services among LGBTQ populations in Nova Scotia, Canada.
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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 | 0.023 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".