Do policy legacies matter? Past and present guest worker recruitment in Germany
Bibliographic record
Abstract
Immigration policy is shaped by the legacies of the past. Historical legacies create national immigration ideologies that delineate the range of viable policy responses well into the future. Is it the case, then, that policy choices must conform to an immigration ideology even long after its emergence? What is the scope for meaningful policy choice within a legacy's substantive bounds? This article examines the relationship between Germany's legacy of postwar guest worker recruitment and subsequent policy choices in the 1990s. The failure of the postwar system to prevent settlement left behind a no-immigration ideology that precluded the future pursuit of economic immigration. I argue that the ability of government officials to resume recruitment in the 1990s critically hinged on their ability to devise a recruitment system that could credibly commit to settlement prevention. Policy-makers pursued policies that—in contrast to the past—were premised on worker rotation, annual quotas, the denial of family unification and the absence of labour market integration. This article shows that policy legacies not only have constraining but also enabling effects. By providing opportunities for policy learning, legacies can create opportunities for policy innovation even within the constraints of paradigmatic path dependence.
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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".