Place inclusion for older LGBT+ people and older people with Learning Disabilities: UK organisational perspectives
Bibliographic record
Abstract
Abstract Older LGBT+ individuals and those with Learning Disabilities (LD) have lived through eras of systemic stigma, exclusion, and social devaluation. The 46-month IncludeAge project (www.IncludeAge), funded by the UK Economic and Social Research Council, aims to examine the experiences of inclusion and exclusion among these groups and identify strategies to create more inclusive communities. By exploring both lived experiences and organizational perspectives, the project seeks to develop co-created solutions that enhance inclusion in place, space, policy, and practice. Eighty semi-structured interviews were conducted with advocacy and support groups for older LGBT+ and LD communities, age-related organizations, and third spaces such as churches, shops, hospitality, and welfare services. A thematic analysis of barriers and facilitators of inclusion across organizations in Scotland, England, and Wales was undertaken. Four key themes emerged as barriers to inclusion: (1) historical distrust and past negative experiences, (2) organizational limitations and financial constraints, (3) passive inclusion and limited visibility, and (4) digital (in)accessibility. Five themes were identified as facilitators: (1) communication and social networks, (2) external oversight mechanisms, (3) inclusive symbols and language, (4) stakeholder involvement, and (5) intergenerational initiatives. Findings highlight systemic, socio-structural, and psychological challenges in fostering inclusive environments. Despite these barriers, facilitators indicate that meaningful change is achievable. Strengthening organizational strategies and fostering sustainable institutional change are critical to building more equitable communities. Addressing these issues requires targeted policy interventions, cross-sector collaboration, and long-term investment in inclusive practices to ensure older LGBT+ people and those with LD are fully recognized and supported in society.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.002 |
| 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".