Bibliographic record
Abstract
Act on Employment and Vocational Rehabilitation of Persons with Disabilities 1991 109 activation programmes 148-157 active citizenship 130-131 active labour market policies (ALMPs) 146, 147, 150 active social policy 129 adverse sanctions 283n adverse selection 76 Affordable Care Act (ACA) 127-128, 136, 137 alternative economic spaces 223 alternatives to a right to work 243-247 Americans with Disabilities Act (ADA) 128 anti-discrimination legislation (ADL) 257, 260 see also employment legislation; equality legislation arts activities 231-233 assessments disability 106-107, 118n work ability 150-151 Work Capability Assessment (WCA) 37, 95, 101-102n, 189-190 work capacity 45, 47, 49 Australia conditionality 45, 46, 48 disability benefits 43-44 disability prevalence 43 Disability Support Pension (DSP) 43-44, 45, 46-47, 48-50 Index Note: Page numbers in italics refer to tables and figures, and page numbers followed by "n" refer to end of chapter notes employment rate 50 employment services 46, 47, 58-59 income poverty 44 income support reforms 45-60 volunteering 230 welfare streams 49 B bad work 207, 212, 242 Barnes, C. 248-249 barriers to finding employment 169 barriers to volunteering 230-231 barriers to work 8-9, 33-34, 36-37, 50, 70 bedroom tax 281-282 benefit inadequacy 53-55 see also poverty benefit income loss 3 benefit trap 114 benefits incapacity-related 74, 81n in-work 200, 201 see also Incapacity Benefit (IB); Jobseeker's Allowance (JSA) Berthoud, R. 164 Black, B. 245 blind people 37 business start-up grants 112 C Canada employment rate 221 social enterprises 223-228 volunteering 234n capacity to work 45, 47, 49,
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".