Accessibility as a framework for sustainable transportation planning in the tijuana-rosarito-tecate metropolitan region
Bibliographic record
Abstract
One of the basic goals of urban sustainability is to manage urban fl ows effi ciently.Urban transportation is considered one of the aspects that largely generate environmental, social and economic impacts in cities and urban regions.With the increase of automobile dependence, the new perspective about urban transportation has to favor accessibility over mobility.Accessibility is considered one of the main goals of sustainable transportation and it is used as a good concept to develop an integrated land use-transportation planning process.According to this, this paper examines the relationship between urban form and transportation in the Tijuana-Rosarito-Tecate metropolitan region, located in the cross border space between Mexico and the Unites States of America, as a framework to implement a more integrated planning process.The research is conducted at three scales: urban, metropolitan and cross border space.The fi rst stage of this study is developed at the urban scale (Tijuana), analyzing data at the city and district level.Linear correlation analysis was implemented to identify the relation of land use factors and automobile trips.The results in this fi rst stage indicate at the city level that population density and distance from center have negative correlations with automobile trips; significance correlation between urban form factors evidence a segregated land use pattern in Tijuana.At the district level, negative correlations appear in other factors (job density, land use mixture and transit routes density) with no relevant signifi cance; nevertheless, core districts appear as the ones which urban conditions favor other transportation modes.Preliminary conclusions indicate that urban conditions of core districts could be implemented in the rest of the city through new zoning and transportation strategies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".