Bibliographic record
Abstract
Introduction Labour migration is as old as the hills. Workers move from areas of high unemployment to those regions where jobs are more plentiful. While economists highlight the economic benefits of labour migration, labour lawyers are more concerned with the rights and entitlements of those individuals – and their families – who have moved. Since its inception, the European Union has provided a structured framework in which transnational migration can occur, principally through the provisions of the European Community Treaty establishing the right of free movement of persons. These provisions enshrine so-called “fundamental freedoms” which grant individuals both the right to move and the right to claim certain welfare benefits in the host state on the same terms as nationals. This is a highly sensitive area. The aim of this paper is to question the basis on which mobility rights have been granted before examining whether the situation in the EU is unique and whether it has wider lessons for international migration. Free movement of workers Although the original EEC Treaty talked of free movement of persons, reference to the free movement of persons was misleading: The original Treaty gave no general right of free movement for all persons. To enjoy such a right, the individual had to hold the nationality of one of the member states (with nationality being a matter for national – not Community – law) and be economically active either as a worker under Article 39(1), or as a self-employed person under Article 43.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".