Cities in Asia by and for the People
Bibliographic record
Abstract
Cities by and for the people' indicates the active role of urban citizens in constructing spaces in the cities.The collection of narratives in this book brings together research from ten cities in Asia to contribute to re-theorizing the city from the perspective of ordinary people who face moments of crisis, contestation, and cooperation to create alternative spaces from those produced under prevailing urban processes.The chapters in this book accent the intertwining of 'human flourishing' with the exercise of human agency through daily practices in the production of urban space, placing people in the centre as agents of city-making with discontents about their current conditions and desires for a better life.The cases brought together in this volume each tell us what people strive for when they mobilize with others to produce urban spaces.One of the important theoretical lessons is that the appropriation of space for de-commodified, alternative visions of urban life is not permanent.Sharing space is an opportunity to build collective actions and initiate discussions on the collaborative management of the place.In practice, these processes may be far from ideal and may be subjected to local forms of power imbalances.Although they are spaces of continuous struggles and are embedded with specific limitations that include local hierarchies and contradictions, these convivial spaces are places that actively demonstrate the possible alternative ways to produce urban spaces.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.006 |
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".