Coordinated wage setting and social partnership under EMU. A framework for analysis and results from Belgium, Germany and the Netherlands
Bibliographic record
Abstract
Recent scholarship has found wage-setting practices to be a key ingredient in the eurozone crisis, but has yet to examine the specifics of individual wage-bargaining systems and how they behave under EMU. This article addresses this oversight, dissecting wage-bargaining systems by the mechanisms that deliver horizontal and vertical coordination, as well as the indicators to which they are calibrated. It then presents the results of a comparative study of the wage-bargaining systems in Belgium, Germany and the Netherlands. Comparisons of the Dutch and Belgian systems find that calibration is an important component of wage-bargaining systems, while greater subtlety is needed with regard to the role of the state. While Belgium has clearly struggled because of its practice of indexing wages, the German and Dutch cases instead suggest that developments unconnected to monetary union may be limiting their ability to manage its pressures. The article concludes that in order to continue to function, these three systems require revisions.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".