Citizen Participation for Sustainable Transport: Role of Self-organizing Civil Society Organizations to Innovate in Complex City and Transport Planning Systems
Bibliographic record
Abstract
20th century, citizen “revolts” against urban highway projects have influenced thinking about public transport (Toronto, Vancouver, New York), governance (Portland), and cycling (The Netherlands) to this day. Less is known, however, about how these emerge in developing countries, and what they can tell us about citizens’ role in innovation to achieve more sustainable transport systems. Using a complexity-based methodology, this case study examines a social movement that emerged in opposition to the country’s first major highway concession, in Santiago, Chile (1997), challenging and changing urban planning paradigms. In 2000, the anti-highway campaign founded a citizen institution, Living City (Ciudad Viva). Twelve years later, it has become a prize-winning, citizen-led planning institution. Although participation’s role in improving transport systems has become increasingly recognized in recent years, it still tends to be rather ritualistic. This experience offers insight into how strategic approaches to participation can reinforce the role of self-organizing civil society organizations in introducing innovation into existing systems. Findings suggest that traditional large formats should be supplemented by small groups, with more attention paid to the quality of communication and how new consensuses are transmitted (or not) through networks of relationships. This experience suggests that rethinking the city and transport as complex systems, and providing room for leadership from citizen, as well as “technical” and “governmental” planners, opens the way to more effective strategies for innovating in transport, to address the social, environmental and other challenges humanity faces today.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".