‘It’s not a me thing’: the role of transcendence and critical politics in Black LGBTQ wellness in Montreal
Bibliographic record
Abstract
This study explores well-being strategies and challenges for Black LGBTQ individuals in Montreal, Canada. Semi-structured interviews were conducted between March and May 2023 with key informants, or advocates and service providers for LGBTQ communities in the Montreal metropolitan area. Thematic analysis was used and involved transcription, memo-writing and a multi-step, inductive coding process using MAXQDA. The findings highlight three areas of well-noted challenges for Black LGBTQ individuals: systemic barriers; lack of targeted support; and challenges to accessing services. Two strategic domains emerged as innovative approaches to support well-being: transcendental practices and intersectional sociopolitical awareness raising. Transcendental practices, ranging from fine arts and dance to reiki energy healing, offered avenues for healing and community-building. Intersectional sociopolitical awareness was described as crucial in informing and contributing to existing efforts to improve well-being such as therapeutic engagement with clients and facilitating mutual aid. The identified transcendental practices and political awareness offer promising avenues for holistic well-being and comprehensive approaches to challenges such as inequitable HIV burden. Recognising the convergence of identities and social power axes can inform future interventions to foster more inclusive and empowering health strategies for Black LGBTQ communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.025 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".