Brigitte Le Normand. <i>Citizens without Borders: Yugoslavia and Its Migrant Workers in Western Europe</i>.
Bibliographic record
Abstract
Building on a wide range of historical sources, Brigitte Le Normand’s Citizens without Borders: Yugoslavia and Its Migrant Workers in Western Europe presents a fascinating account of a complex social phenomenon that peaked in the early 1970s and linked the former socialist federation with several countries short of manpower. Yugoslavia was among those Eastern European countries that relied on migrant workers and even forced their own populations to seek work in the West. The case of “guest workers” (Gastarbeiter) in German-speaking countries provided an instructive model. Le Normand structures her book in two main sections. In the first one, she reconstructs attempts to administer and govern Yugoslav labor migrations in human geography, statistics, and the political economy, and analyzes the representations of migrant workers in Yugoslav cinematography. Whereas her choice to present migration as a state-centered phenomenon might be at first questionable, Le Normand strengthens this claim by pointing at the state policies of socialist Yugoslavia. The federation was one of the rare examples of a state-controlled economy deciding to export the work force and thus cope with domestic unemployment. The author follows the state-centered approach in the second part of the book as well, where she documents different attempts of various state-controlled mechanisms to keep in contact with the workers abroad. This was a crucial point for Yugoslav authorities in order not to lose influence among workers in favor of anti-Communist exile organizations, most often structured according to different nationalist projects. Le Normand contextualizes policies, such as radio programs, newspapers, associations, and cultural production destined for workers abroad, including activities for migrant children such as schooling in native languages and youth clubs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".