The Logics and Logistics of Urban Progress: Contradictions and Conceptual Challenges of the Global North-South Divide
Bibliographic record
Abstract
This article explores contradictions and pitfalls inherent to the binary concept of the North-South divide. Using Savannah, Georgia and Montreal, Quebec as illustrations, we argue that characteristics of what is commonly defined as typically “Global South” can equally be observed in cities that would generally be referred to as “Global North.” The clear-cut distinctions between global cities of the North and megacities of the South are dissipating as cities use strategies of scalar identification to retell their own pasts. However, simply to point to emerging similarities between global cities and megacities is to ignore the underlying material logics of urban development. Rather than completely doing away with socially constructed North-South dichotomies, then, we argue that they serve historically and geographically specific social functions. We contend that narratives of progress and lagged development play an important role in processes of neoliberal state restructuring in that they help to maintain social cohesion and legitimacy for political action despite the material unevenness and crisis tendencies of neoliberalization processes. The logistic infrastructures that support post-industrial urban development patterns serve as a case in point for these irreducible material logics that underpin the hopes for a better urban future.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.078 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".