Cross-border collective actions in Europe: a legal challenge : a study of the legal aspects of transnational collective actions from a labour law and private international law perspective
Bibliographic record
Abstract
This volume offers a lawyer’s perspective of cross-border collective action in Europe. The Phenomenon of cross-border collective action is well-known in the transport sector where there is a long standing tradition of organising collective action and boycotts to improve the employment conditions of seafarers. However due to the expanding “Europeanisation” of the economy, industrial disputes with a cross-border impact do and will continue to arise in other sectors of the economy as well. As a result, they will or may become a more common feature in multinational enterprises when they operate in a European and global context. The recent cases of Laval (C-341/05) and Viking (C-438/05) are perfect illustrations of the complex interaction between economic freedoms and the fundamental social right to take collective action. This kind of industrial dispute tends to raise fundamental questions about the position of industrial action within the framework of the EU/EC. This volume takes a three-pronged approach to the issue. The book starts with several contributions addressing general issues related to the right to take collective action in a transnational context. The second part consists of national reports on labour law aspects of cross-border collective action. The third part includes national reports on private international law issues resulting from the transnational nature of a collective action. Both parts are rounded off with a comparative analysis. The following Member States have been included in this study: Belgium, Finland, France, Germany, Italy, the Netherlands, Spain, Sweden and the United Kingdom. At present, the right to take collective action with a cross border impact constitutes a major legal challenge. Firstly the question arises whether divergence between domestic labour law and domestic private international law impedes the effective use of cross-border collective action. Another quintessential issue that arises is whether Community law itself can become an obstacle to the effective use of collective action (Cf. the Viking and Laval cases) or to what extent Community law can constitute a means to resolve the obstacles to cross-border collective action. Is there a need for a ‘kind’ of a European law on collective action?
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.023 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.013 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".