Marketization of Planning : The Cases of Quayside-Toronto and Fikirtepe-Istanbul
Bibliographic record
Abstract
Neoliberalism is undoubtedly one of the most fundamental concepts when explaining urban development and spatial processes. Urban politics is one of the most fundamental fields in which neoliberal restructuring is effective. Neoliberal urbanization aims to make urban areas attractive for capital and increase the role of market forces in urban development. One of the most practical ways to achieve this is to integrate neoliberal market-oriented approaches into urban planning and transform existing planning systems into marketized planning systems. To realize this integration, formulating large-scale urban development projects with market logic in partnerships between the public and private sectors is beneficial. This research paper examines two cases from Toronto and Istanbul to see how neoliberal market-oriented approaches are adapted into urban planning and what are the implications of this adaptation. In doing so, this paper investigates how actors, especially from the private sector, contributed to the marketization process of planning. Furthermore, this paper looks into how market-thinking and market-oriented methods were blended with regulatory planning frameworks.
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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 | 0.003 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".