Planning for accessibility: the divide between research and policy in the promotion of equitable mobility
Bibliographic record
Abstract
Mobility-related social inequalities are receiving increasing attention from planning research and practice. Nevertheless, research seems to have a limited impact on urban policies addressing mobility. Using Santiago de Chile as a case study, the paper discusses the existing gaps between research on mobility-related equity concerns and existing policies and plans addressing urban mobility operating at national, metropolitan and municipal scales. An equity-based comparison is performed for different spatial planning instruments, exploring guiding concepts and deriving proposals through content analysis. The findings show that there is a comprehensive and multidisciplinary body of literature in Santiago on mobility and equity, approaching several dimensions of mobility, accessibility and social exclusion in relation to different population groups. However, the series of discourses, norms and actions (policies and programmes) operating at different planning scales lack coherence and address only some of the dimensions identified in the literature. Current plans and policies in Santiago have a limited scope and are difficult to modify, questioning their effectiveness for understanding and tackling mobility-related equity concerns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".