Dis/Entangling Disability, Mental Health, and the Cultural Politics of Care
Bibliographic record
Abstract
This paper explores how understandings of care can be prefigured through engagements with concepts of ableism and sanism as productive and radical companions for (re)thinking care. Working with family carers and people with learning disabilities as part of a co-produced project based in England: Tired of spinning plates: an exploration of the mental health experiences of adults and/or older carers of adults with learning disabilities (National Institute for Health and Care Research (NIHR) 135080, October 2022-November 2024), we notice the absence of the concepts of ableism and sanism in theorisations of the cultural politics of care. We begin by describing family carers’ complex entanglements with categories of ‘carer’, ‘learning disability’, and ‘mental health’. We draw on theorisations of ableism and sanism to inform our analysis of caring relationships, attending to the dis/temporalities and dis/locations of care and the centrality of dis/political love. We conclude by reflecting on what academics, policy makers and practitioners might learn about caring practices from family carers and people with learning disabilities, crucially acknowledging and embracing the power of dis/political love in caring relationships.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.103 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.002 | 0.005 |
| 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".