Bibliographic record
Abstract
What is often absent in accounts of LGBTQ2 migration experiences are the roles of policies and legislations in the regulation of sexual and gender minoritized populations ’ movements across borders. Spe-cifically, many health policies can simultaneously impact on access to and uptake of health services and thereby influence health outcomes among older LGBTQ2 populations. In this paper we offer an analysis of the ways in which current policies and legislation within select European Union (EU) states can impact on freedom of mobility; re-cognition of same-sex partners and gender-identity in receipt of social benefits; social and labour market integration; language and cultural competency; anti-discrimination policies in health and care; healthy aging initiatives; and the mainstreaming of health policies versus tar-geted health intervention policies could potentially impact the flow of migration of older LGBTQ2 individuals between select Member States and outside of them. In the following synthesis, we argue the need to approach health policies from ‘strengths-based ’ approaches within a life course framework in exploring the development and im-plementation of policies surrounding the healthy aging of older LGB-TQ2 people; and to articulate how policies surrounding these issues could influence the migration of older LGBTQ2 individuals and their families. We argue that there is a need to develop both mainstream and targeted-intervention policies, and direct future research towards the assessment of the specific health needs and initiatives for aging LGBTQ2 populations both in Canada and in EU Member States with comparable health systems.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.910 | 0.815 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".