Dealing with<i>Viking</i>and Laval: From Theory to Practice
Bibliographic record
Abstract
Abstract This chapter examines the recent controversial decisions of the ECJ in Viking and Laval , focusing on how they are likely to be applied in practice. Firstly, it considers the rules regarding the applicable forum and the procedures for going to court in the UK, then it looks at when it can be said that an employer’s economic rights under EU law have been engaged and when there has been a ‘restriction’ on those rights. It goes on to address the core issue of the circumstances in which a ‘restriction’ on the relevant EU economic right pursues a ‘legitimate aim’ and then considers the key battleground in future cases falling under Viking and Laval , namely whether the industrial action is ‘proportionate’. Finally, it addresses an important, but unresolved, issue: the extent to which industrial action in breach of Articles 43 or 49 EC could give rise to liability in damages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".