Ambiguous goals, uneven implementation – how immigration offices shape internal immigration control in Germany
Bibliographic record
Abstract
Abstract This paper investigates regional variation in migration policy implementation, focusing specifically on the underexplored role of policy ambiguity. It chooses a salient case study of internal migration control implementation: the application of labour market access policies for migrants with precarious legal status in German municipal immigration offices. Studying the implementation approaches of eleven offices within one Land by means of semi-structured interviews with senior officials, the research design allows for drawing inter-agency and inter-policy comparisons. The data provides empirical evidence for the claim that the more conflictive and hence ambiguous a policy, the more importance can be placed on local determinants of implementation. Different logics (economic welfare and regulatory control logic) legitimizing more restrictive or expansive implementation are identified and linked to the broader migration policy context. Moreover, the difficult task of officials to determine applicants’ identity clarification efforts – a condition for receiving a work permit – serves as basis for conceptually distinguishing between collective and individual discretion of street-level bureaucrats.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".