Migrants in the city: Rethinking the governance of integration in an age of ‘super-diversity’
Bibliographic record
Abstract
‘Super-diversity’, which has resulted from mass immigration, has led to major shifts in the ethnic demographic composition of English cities, and has also created many challenges for local authorities. In this respect, segregation, which characterises some urban areas, is a dominant issue. Following the publication of Ted Cantle’s report on race riots, which highlighted the fact that communities were operating on the basis of ‘parallel lives’, local authorities have had to take the lead in the integration issue by implementing adequate measures to promote community cohesion. Cities are considered to be better able to respond to the issues that are of immediate concern to them. By defining cities as key stakeholders in managing integration, a shift towards the local governance of integration in England has been observed. This shift has been cemented in the plethora of reports published by successive governments, but the government’s retreat can be questioned in many ways: Firstly, the government’s cuts to the funding allocated to local authorities has had a severe impact on those welcoming the highest number of migrants, as well as on Black, Asian and minority ethnic (BAME) groups, by limiting their actions; secondly, as a further result of this cut, the numerous local stakeholders involved in the integration of migrants have created a complex and often confusing ‘multilevel local’ governance of integration. Moreover, the ineffectiveness of community relations programmes in tackling segregation should compel the government to play an active role in this national issue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".