Introduction: Theorizing the civic turn in European integration policies
Bibliographic record
Abstract
Many authors have written about the ‘civic turn’ in European immigrant integration politics and policies that began in the late 1990s, but few have focused on the conceptual or normative dimensions of this turn. The purpose of this special issue is to help correct this situation. In this substantive introductory article, we begin with a discussion of the ‘convergence or national models’ debate that dominated early work on the subject. The next section presents the argument that civic integration is best understood as an ideological turn. It expands ‘good citizenship’ into personal conduct and values, shifts the responsibility for integration from the state to individuals and institutionalizes incentivizing and disciplining integration processes, which are often really just a means of migration control. This is accompanied, we argue, by a civic nationalist conception of membership that appeals to shared political values but defines those values through the culture of the state’s national majority. We then move on to the mechanisms and effects of civic integration, followed by a discussion of its normative analysis, before finally summarizing the articles included in this special issue and how they address the concerns that we have raised.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".