Bibliographic record
Abstract
Abstract Individuals in and leaving care within the UK experience numerous dilemmas that include a lack of supportive housing and potential homelessness, lower educational attainment and occupational status, and greater likelihood of moving into poverty. These adverse situations—all of which are interrelated—shape their present and future health status. Models of these processes usually focus on individual behaviours/characteristics, the consolidation of positive identities through the development of supportive networks, and specific social policies germane to this group. Although informative, these models neglect many key contextual factors that shape these outcomes. In this paper, we present a model of care‐leaving that incorporates developments in the political economy of health literature to show how differing welfare state arrangements shape health by mediating the distribution of economic and social resources over the life course for populations in general and for those in and leaving care specifically. The key recommendation suggested by this model is to focus upon developing public policies to address the vulnerable situations care leavers experience associated with skewed income distributions, lack of housing affordability, weak employment standards, and lack of access to higher education typical of liberal welfare states such as the UK.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".