Socio-demographic diversity and unexplained variation in death rates among the most deprived parliamentary constituencies in Britain
Bibliographic record
Abstract
BACKGROUND: There is considerable unexplained variation in death rates between deprived areas of Britain. This analysis assesses the degree of variation in socio-demographic factors among deprivation deciles and how variables associated with deaths differ among the most deprived areas. METHODS: Death rates 1996-2001, Carstairs' 2001 deprivation score and indicators, population density, black and minority ethnic group (BME) and population change 1971-2001 were calculated for 641 parliamentary constituencies in Britain. Constituencies were grouped into Carstairs' deciles. We assessed standard errors of all variables by decile and the relationship between death rates and socio-demographic variables with Pearson's correlations and linear regression by decile and for all constituencies combined. RESULTS: Standard errors in death rates and most socio-demographic variables were greatest for the most deprived decile. Death rates among all constituencies were positively correlated with Carstairs' score and indicators, density and BME, but for the most deprived decile, there was no association with Carstairs and a negative correlation with overcrowding, density and BME. For the most deprived decile multivariate models containing population density, BME and change had substantially higher R(2). CONCLUSIONS: Understanding variations in death rates between deprived areas requires greater consideration of their socio-demographic diversity including their population density, ethnicity and migration.
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How this classification was reachedexpand
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".