OLDER ADULTS’ GENDER IDENTITY AND SEXUAL ORIENTATION: THE IMPORTANCE FOR END-OF-LIFE CARE
Bibliographic record
Abstract
As Canada’s population is aging, so too is the lesbian, gay, bisexual, and transgender (LGBT) community. Although the body of literature on LGBT aging is growing, very little of the research focused on end-of-life care originates from Canada. To begin to fill this gap, pilot research with LGBT older adults was conducted in three regions in Ontario. This presentation will feature findings from focus groups on the lived experience of twenty-three self-identified LGBT older adults. Despite commonalities pertaining to perceptions of end-of-life that apply generally to aging and older adulthood, through our analysis a key finding is that sexual orientation and gender identity have unique implications for end-of-life. Key themes include the need for autonomy and control and unique considerations around social connections and supports. A salient finding was related to the heteronormative assumptions of many health and social care providers and fears about need to ‘return to the closet’ to receive quality end-of –life care. Integrating the research literature and the lived experience of our participants, recommendations are proposed and will be presented as a ‘Call to Action.’ These recommendations encompass new directions for clinical practice, research, and law and policy, and taken together their implementation would lead to cultural competence in the area of LGBT aging across the health continuum, with the goal of improving end-of-life and quality death experiences.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".