Feature: In‐work Benefit Reform in a Cross‐National Perspective ‐ Introduction
Bibliographic record
Abstract
In the past two decades, a number of industrialised countries – including the US, the UK, Canada and New Zealand – have witnessed an increasing reliance on in‐work support through tax credits and work‐conditioned transfers as a means of providing cash assistance to low‐income families with children. These Governments have used tax credits in an attempt to alleviate poverty without creating adverse incentives for participation in the labour market. In‐work benefits achieve this goal by targeting low‐income families with an income supplement that is contingent on work. Eligibility is based on family income and typically requires the presence of children, reflecting that there are higher out‐of‐work welfare benefits for families with children, that such families have higher costs of working (childcare) and, perhaps, that such families have higher labour supply elasticities than those without children. Family‐income‐based eligibility rules and the interaction with other aspects of the tax and benefit system make the analysis of the impact on work incentives and the impact on other outcomes more complex than what they might appear at first.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 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".