The Transnationalization of Labor Mobility: Development Trends and Selected Challenges Involved in Its Regulation
Bibliographic record
Abstract
Internationalization of value chains and of for-profit as well as non-profit organizations, and as a result of cheaper and safer mass migration, transnational labor mobility is of increasing importance. The article presents the development of the different types of cross-border labor mobility (from long-term labor migration over expatriats/inpatriats up to business traveling); it analyses crucial aspects of labor conditions and how the collective regulation of working, employment and participation conditions in general is affected: could local or national forms of labor regulation cope with these new conditions? What are the main challenges when it comes to collective bargaining and the monitoring of labor conditions? The article is based on a three year international and comparative research in Germany and Mexico. First, different ideal types of transnational labor mobility are distinguished that have emerged as a result of increasing cross-border labor mobility. Then potential sources of labor related social inequality and challenges in the regulation of the working, employment and participation conditions for transnational workers are discussed. Finally, some conclusions are drawn for further research.
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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 | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".