Forgotten lives: Trans older adults living with dementia at the intersection of cisgenderism, ableism/cogniticism and ageism
Bibliographic record
Abstract
There is little research at the international level to help us understand the experiences and needs of trans people living with dementia, despite population aging and the growing numbers of trans people including the first cohort of trans older adults. There is a need to understand the widespread barriers, discrimination and mistreatment faced by trans people in the health and social service system, and the fears trans people express about aging and dementia. Anecdotal evidence from the scarce literature on the topic of LGBTQ populations and dementia suggest that cognitive changes can impact on gender identity. For example, trans older adults with dementia may forget they transitioned and reidentify with their sex/gender assigned at birth or may experience ‘gender confusion.’ This raises crucial questions, for example regarding practices related to pronouns, care to the body (shaving, hair, clothes, etc.), social gendered interactions, health care (continuing or not hormonal therapy) and so on. This article fills a gap in current literature by offering a first typology of responses offered by academics who analyzed the topic of dementia and gender identity, to trans older adults with dementia who may be experiencing ‘gender confusion,’ namely: (1) a gender neutralization approach; (2) a transaffirmative stable approach; and (3) a trans-affirmative fluid approach. After providing critical reflections regarding each approach, we articulate the foundations of a fourth paradigm, rooted in an interdisciplinary dialogue regarding the interlocking systems of oppression faced by trans older adults with dementia, namely ageism, ableism/sanism, and cisgenderism.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.018 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.005 | 0.010 |
| 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".