‘That would have been beneficial’: LGBTQ education for home-care service providers
Bibliographic record
Abstract
This paper reports qualitative findings from a pilot study that explored the lesbian, gay, bisexual, transgender and queer (LGBTQ) education needs of home-care service providers working in one large, urban Canadian city. The pilot study builds upon research that has documented barriers to health services for diversely situated LGBTQ people, which function to limit access to good-quality healthcare. LGBTQ activists, organisations and allies have underscored the need for health provider education related to the unique health and service experiences of sexual and gender minority communities. However, the home-care sector is generally overlooked in this important body of research literature. We used purposeful convenience sampling to conduct four focus groups and two individual interviews with a total of 15 professionally diverse home-care service providers. Data collection was carried out from January 2011 to July 2012 and data were analysed using grounded theory methods towards the identification of the overarching theme, 'provider education' and it had two sub-themes: (i) experiences of LGBTQ education; and (ii) recommendations for LGBTQ education. The study findings raise important questions about limited and uneven access to adequate LGBTQ education for home-care service providers, suggest important policy implications for the education and health sectors, and point to the need for anti-oppression principles in the development of education initiatives.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".