Tying Up the Loose Ends: The Determinants of Active Labour Market Policy in the Western Countries 1985-2013
Bibliographic record
Abstract
Knowledge on the determinants of Active Labour Market Policy (ALMP) spending accumulated during the 2000s. Despite these advances, the current research lacks a systematic approach to the relevant determinants. This article fills the research gaps by analysing simultaneously the 14 most frequently used determinants for the first time. In addition to these variables, this study introduces a new factor, namely the impact of economic crises. Through the analysis of the longest data period yet investigated of 20 Western countries and a comparison of methodological alternatives, this study both challenges and reinforces previous findings, as well as produces new ones. For example, it is the first investigation to reveal the positive effect of government indebtedness and economic crises on ALMP expenditure. However, the rivalry between the “usual suspects” continues, as the negative effects of budget deficits, foreign trade, and population ageing, and the positive effects of trade union density and GDP growth, were rediscovered in this analysis.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".