Bibliographic record
Abstract
Bus Rapid Transit (BRT) is a relatively new mode with a wide range of applications that are still not well understood. Its explosive growth in developing and developed countries has increased its exposure but has led to mostly experimental implementation with mixed results. Therefore, better understanding about the reasons behind BRT implementation success and shortcomings is needed. The objective of this thesis is to evaluate the state of BRT planning under different contexts by assessing how background theory and practical implementation of BRT systems compare. The scope is limited to current a detailed evaluation of 13 case studies in the United States, Canada, Australia, Mexico, Brazil, Colombia, and Ecuador chosen to represent some of the most succesful and established systems in the world. Data was obtaiend from previous research as well as direct reporting from agencies. The evaluation is performed through qualitative and quantitative methods. Qualitative methods classify BRT systems by characteristics and assess the relationship between their implementation and performance using the criteria defined in the literature. Quantitative methods build upon the previous analysis to more precisely assess their performance from both the users' and the transit providers' perspectives. This research found that BRT as a public transit mode has a large room of improvement in terms of design and implementation, since there is a significant variability in performance under similar conditions and a considerable gap between planning best practices and implementation. Also, that planning guidelines are still in an early stage of development and difer in scope and application to a particular context. It also found that its success is not conscribed to developing countries, but that its wide range of applications need to be better adapted to the context they should serve. The findings are significant because they dispel myths about the real potential of BRT and partially identify the reasons behind successes and failures of current systems, such as understimation of implementation times and lack of knowledge about component integration. Further research should approach these issues mainly in two complementary directions. First, it should focus on expanding the case study approach to the newer systems in operation once better data is available. Second,it should further advance the development of theoretical framwork for better operational design based on urban form, as well as an evaluation framework that puts more emphasis on user experience and sustainability. Finally, the findings reinforce that BRT is a distinct mode so that systems that do not meet its criteria should not be named as such.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".