Bibliographic record
Abstract
While joblessness is by no means a phenomenon specific to this century, the concept of 'unemployment' is. This book follows the invention and transformation of unemployment, understood as a historically specific site of regulation. Taking key aspects of the history of unemployment in Britain as its focus, it argues that the ways in which authorities have defined and sought to manage the jobless have been remarkably varied. In tracing some of the different constructions of unemployment over the last 100 years - as a problem of 'character', as a social 'risk', or today, as a problem of 'skills' - the study highlights the discursive dimension of social and economic policy problems. The book examines such institutionalized practices as the labour bureau, unemployment insurance, and the 'New Deal' as 'technologies' of power. The result is a challenge to our thinking about welfare states.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".