Reflections on researching new cities underway in the Global South
Bibliographic record
Abstract
Over the past decade, new master-planned cities have been increasingly adopted worldwide as a strategy for economic growth. This paper reflects on new cities built from scratch as a field of study, and the particular methodological considerations associated with conducting research in and on new cities, structured around four key themes. First, we discuss the inherently global and transnational character of new cities as a specific challenge that shapes our approach to studying them. Second, we examine challenges of accessing people and information in rapidly developing private and high-profile ventures. Third, we address power dynamics and positionality in new city projects that are globally concentrated in “closed,” non-democratic contexts. Fourth, we draw attention to the unique logistical constraints and challenges of doing field research in new cities under construction and outline the disparate experiences of site visits, where varying degrees of control and surveillance impact research activities.
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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 | 0.030 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.024 | 0.050 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 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".