Bibliographic record
Abstract
Introduction: bringing context into focus to understand the power of participation As discussed elsewhere in this book, transport planners seeking to build more sustainable urban transport systems generally view Bus Rapid Transit (BRT) as an option that offers substantial advantages, in terms of flexibility, implementation, public–private arrangements, capacity and other elements. Moreover, when treated as the articulator of a whole transport system and major contributor to resilience overall, BRT can also enhance health, environmental quality, social integration and equality, among other benefits. Often these benefits are not realised, despite planners’ and politicians’ efforts to position BRT as an alternative to better known approaches, such as metros/subways, trains and light rail. In these conditions, traditional participation methods, which primarily involve vertical delivery of information to passive recipients, do not help and can hurt. Often, citizens see these as largely hollow rituals that do not genuinely consider the needs and desires of diverse, often marginalised groups (Bickerstaff et al 2002). With a few exceptions, BRT has provoked indifference, hostility and rejection among the general public and political leaders. This is highly problematic, given that for BRT to accomplish the larger/sustainability goal of transforming street/public space it requires active support from the public, particularly vocal and respected organisations, committed public health officials, transit riders, cyclists and pedestrians, given the prevailing bias favouring car use in many cities. This chapter examines issues of public buy-in, focusing on experiences in Santiago, Chile. Unlike traditional views, which examine participation largely from a process-centred perspective, this chapter starts by examining issues of democratisation in established, post-World War II democracies (Canada, the US, most of Europe), and in newly democratising countries, particularly in Latin America, as these affect the relevant policy making environment. Terminology is complex, with ‘citizen engagement’ being the most common in the English-language literature, based primarily on experiences in North America and Europe, while participación ciudadana (citizen participation) is widely used in Latin America. Although analogous, the terms enclose a world of difference. The first refers to permanent procedures for citizen involvement, practised in the context of established democracies, with diverse civil society actors and elected ‘public servants’ at the local and regional levels. Their relationships tend to be relatively horizontal, although there are many exceptions.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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; both teacher heads agree on what is shown here.
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".