Challenging the myth of ‘Minority White Cities’
Bibliographic record
Abstract
Whites will soon become a minority in Birmingham and other major British cities, posing a critical challenge to social stability, Britain’s race relations watchdog has warned. The Sunday Times newspaper Introduction Concerns about the consequences of immigration and residential segregation converge in a spectre of ‘Minority White Cities’, where White residents make up less than half of the population. There is a fascination with the year in which particular cities will lose their White majority both from those whose work encourages ethnic diversity and those who fear lack of integration. Thus, publicity from a global forum on Cities in Transition was headlined by the wholly unsubstantiated claim that ‘Birmingham is set to join Toronto and Los Angeles as a “majority-minority city” by 2011’ in order to raise questions for planning: ‘What will it mean for public services and race relations when more than half the population is non-White?’ Similarly, the Commission for Racial Equality’s factual profiles based on the 2001 Census and prepared in 2006 claim that ‘Leicester is widely predicted, within the next five years, to become the first city in Europe with a majority non-white population. Nowhere else in Britain has proportionally fewer White British residents’. Here ‘widely predicted’ needs to be interpreted as ‘predicted wide of the mark’ as no such predictions have been made. The coolly stated ‘fact’ of Leicester’s extremely low proportion of White British residents is also false. In 2007 a contributor to Wikipedia, a widely used free online encyclopaedia edited by its readers, used six such apparently authoritative reports to claim that ‘The indigenous population is due to be a minority in Leicester, London and in Birmingham by the time of the 2011 Census’. Two claims about Minority White Cities are addressed in this chapter. First, that the phenomenon of a Minority White City has some democratic meaning or significance for city management. Second, that population change will be such that several British cities will have fewer than half their residents of White ethnicities by 2011. The chapter examines the predictions and puts the evidence beside them, which demonstrates severe exaggeration. First, we argue that the notion of cities becoming plural in the near future (where no one racial or ethnic group has a majority) is simply a convenient hook on which to hang discussion of the challenges and opportunities of future multicultural cities.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.038 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.013 | 0.030 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".