Bibliographic record
Abstract
Poverty rates in Britain declined from 1968 to the late 1970s, but since then have risen continuously. Our report for the Joseph Rowntree Foundation1 shows how this trend has been accompanied by a rise in the geographical segregation of the poor from the rich – where the two groups live physically apart. There is some good news, though. In the most recent period, the number of households with people who are the poorest – income poor, materially deprived and subjectively poor – fell, and such very poor households also became less geographically concentrated. It has become evident that government policy can reduce that gap. The people in the most geographically segregated social group are those who were so wealthy that they could afford to exclude themselves from the schools, hospitals, cleaning, childcare, recreation and other norms for most people in society. As they grew wealthier, however, the richest did not grow greatly in number, but became corralled in fewer and fewer parts of the country. At the extreme end are the most affluent parts of, for example, the Mole Valley in Surrey, and Chesham and Amersham, in Buckinghamshire. In 1980, a majority of the population in these places were neither rich nor poor. Now only a quarter of households there are non-poor, non-wealthy, while more than a third in these areas are counted in our most exclusively wealthy category. Today, the majority of people living in the most expensive areas will have moved there over the last few decades, making such places unaffordable to almost everyone else.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.011 | 0.026 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.217 | 0.076 |
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".