Bibliographic record
Abstract
Abstract The transnational circulation of policy ideas has been increasingly advanced as a significant factor in the fabric of local diversity policies. On the one hand, the circulation of managerial concepts such as diversity management has contributed to the rise of neoliberal urban diversity models; on the other, city networks, international organisations, and transnational civic movements are pushing forward progressive urban diversity agendas. This chapter aims to analyse the role of such processes of policy modelling in shaping urban diversity governance. It is based on fieldwork conducted in Doha and Singapore since 2018 and on the analysis of these cities’ policy documents. The chapter shows how transnationally circulating references and norms contribute to shaping local diversity governance frameworks and how both cities strive to position themselves as diversity governance models. I argue that their modelling strategies rely on the spatial and organisational compartmentalisation of distinct diversity frames. The chapter identifies four compartments in Doha and Singapore that correspond to distinct understandings of diversity and differentiated modelling strategies. This allows to minimise policy tensions, alleviate external critiques, and craft local experiments that can be projected as models on the world stage.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".