Superdiversity and Sub-National Autonomous Regions: Perspectives from the South Tyrolean Case
Bibliographic record
Abstract
Introduction For many sub-national autonomous regions of Western countries, such as Catalonia, South Tyrol, Scotland, Flanders, Basque Country and Quebec, where traditional-historical groups (‘old minorities’) live, migration is a stable and increasingly important reality. Some of these regions have attracted migrants for decades, while others have only recently experienced significant migration inflow. The coexistence of old minorities and new minority groups originating from migration (‘new minorities’) in sub-national territories adds complexities to the management of diversity and migration issues. It is acknowledged that the relation between ‘old’ communities and ‘new’ minority groups can be rather complicated. Interests and needs of historical groups can be in contrast with those of the migrant population. Moreover, the presence of new minorities can have an impact, not necessarily a negative one, on the relationship between old minorities and majority groups at state level and also between old minorities and the central state, as well as with policies enacted to protect the diversity of traditional groups and the way old minorities understand and define themselves. In the past, the subject of the relationship between old communities and new minorities has been largely neglected by scholars. With few exceptions (Medda-Windischer 2009), minority and multicultural issues have been studied separately from the point of view of historical groups or migrant communities, focusing on the relationship between each of these two categories and the dominant state, and highlighting differences between the claims of old minorities, who carry on nation-building projects, and migrant communities, who are expected to integrate into the dominant society (Kymlicka, 1995). When these two perspectives have been combined, it has often been to sustain the so-called ‘threat hypothesis’, namely the belief that historical groups frequently perceive large-scale migration as a danger and harbour defensive and exclusionary attitudes towards migrants due to their ethnocentric understanding of identities or due to the fear that migrants will eventually integrate into the central state culture, further outnumbering the old minorities (Kymlicka, 2001, 278–9; Jeram and Adam, 2013, 2). In the last decade, scholars have started to look more deeply into the relationship between old and new minorities (Medda-Windischer, 2010). The ‘threat hypothesis’ has been opposed, since various ethno-national groups actually manifest inclusive approaches to migration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".