Social Progress in Britain
Bibliographic record
Abstract
Social Progress in Britain examines how much progress has made in the years since Sir William Beveridge described the ‘five giants on the road to reconstruction’—the giants of Want, Disease, Ignorance, Squalor, and Idleness. The book has chapters examining the progress which Britain has made in improving material prosperity and tackling poverty; in extending length of life and tackling disease; in raising participation in education and improving educational standards; in tackling the scourge of unemployment, especially youth unemployment; and in providing better-quality housing and tackling overcrowding. In addition to Beveridge’s five giants, the book also explores inequalities of opportunity (focussing on inequalities between social classes, men and women, and ethnic groups), and the changing nature of social divisions and social cohesion in Britain. Throughout, the chapters put British progress into perspective by drawing comparisons with progress made in other large developed democracies such as Canada, France, Germany, Italy, Japan, Sweden, and the USA. As well as looking at the average level of prosperity, life expectancy, education, and housing, the book examines the extent of inequality around the average and pays particular attention to whether the most disadvantaged sections of society have shared in progress or have fallen behind. It concludes with an assessment of the effect of policy interventions such as Margaret Thatcher’s free market reforms of the 1980s on different aspects of social progress.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".