Bibliographic record
Abstract
Chapter 9 focuses on protest impact. It begins by illustrating the role of partisan dealignment, with a discussion of Buenos Aires and Santiago. Cases in these cities followed different paths to mobilization, yet in both sites protest had high impact because organizers found allies at the national level. The chapter then illustrates the pivotal role of the councillor in single-member districts with two divergent cases in Toronto, in Mimico and Parkdale. These cases also illustrate the co-optation of the creative class by real-estate developers – an important lesson because signs indicate that co-optation will become more common. The chapter then examines impact under right-wing partisan alignment, an adverse setting for protesters. In Seoul, the same set of protest strategies led to success in a leftist district (in the Duriban case), yet they failed in a conservative ward (in the Myeong-dong case). The final part of the chapter continues in Seoul, illustrating the change in protest following a shift from development regime to a progressive regime: In Mullae, cultural producers resisted displacement by infiltrating institutions and obtaining support through insider lobbying.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".