The strictly Orthodox Jewish population in the United Kingdom: Assessment of the census undercount using an alternative estimation system
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
Strictly Orthodox Jews, otherwise known as Haredi, constitute about one-quarter of the total Jewish population of the UK. This population is growing very quickly. A religion question, first introduced into the census of England and Wales in 2001, is generally used to estimate the Haredi Jewish population. This paper claims that Haredi Jews have been severely and consistently undercounted in the census, leading to detrimental consequences for a proper understanding of the numerical dynamics of the UK's Jewish population as a whole and also compromised service provision. This paper develops an alternative estimation system that uses different types of administrative sources to quantify and correct for the census undercount of Haredi Jews. The paper proceeds to show that the undercount is not an exclusively 'Haredi problem': other ethnic and religious groups are also likely to be affected by it.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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