Unpaid Britain: challenges of enforcement and wage recovery
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
As a comparative contribution to a volume dealing with employment rights enforcement (or Employment Standards - ES) in Ontario, this chapter summarises to position in Britain, with particular reference to unpaid wages. \n \nSection one offers an overview of ES in Britain. Setting the context for the enforcement gap, section two surveys recent developments in the British labour market, revealing deepening insecurity among workers. Section three then explores issues surrounding ES enforcement, highlighting key actors and methods involved in the realisation of these rights and entitlements; it emphasises drivers of the enforcement gap including impediments workers face in initiating a complaint, the low recovery of wages due to workers, and a persistent emphasis on soft-law compliance-oriented enforcement strategies. By way of conclusion, the chapter offers suggestions for improved enforcement in Britain.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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