Social inequalities in later life: the socio-economic position of older people from ethnic minority groups in Britain.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are now nearly a quarter of a million individuals aged 60 years or over belonging to ethnic minority groups living in Britain. As the ethnic minority groups in Britain continue to age, information regarding their circumstances in later life will be of increasing importance for the development of appropriate services and policy. This article uses data from the General Household Survey (1991-96) to investigate the household living arrangements, lifestyle, socio-economic status, economic resources and experience of multiple deprivation in later life amongst older people from ethnic minority groups in Britain. The findings indicate that there are significant differences both between and within ethnic minority groups in access to material and social resources, which need to be taken into account by policy makers and planners.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it