Labour Market Policy in the United States, Canada and Sweden: Addressing the Issue of Convergence
Bibliographic record
Abstract
Abstract ‘Convergence theorists’ suggest that domestic and/or global challenges and pressures are rendering welfare states broadly similar across national boundaries. ‘Resilience theorists’, in contrast, argue that a range of socio‐political factors have allowed states to respond differentially to these pressures and maintain their distinct national social policy approaches. However, both research streams have addressed the ‘welfare state’ writ large in a multitude of nations and typically relied upon narrow, quantitative budgetary indicators. This study examines qualitative changes to key income security and social service programmes in one central social policy domain – labour market policy – in three nations, the United States, Canada and Sweden. It suggests that there is evidence of some degree of ‘convergence’ in the broadest sense of the term across these three nations. However, while both the USA and Canada have readily embraced genuinely neo‐liberal restructuring, and become increasingly similar over the past two decades in this policy area, Sweden has managed to retain its distinctive social policy approach so far, despite notable changes, developments and trends. It also suggests that the character and direction of change may vary across and within policy domains in a single nation. The conclusion provides a discussion of universality, equality and solidarity, concepts that are commonly employed in accounts of welfare state change.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".