Not quite a block party: COVID-19 street reallocation programs in Seattle, WA and Vancouver, BC
Bibliographic record
Abstract
The COVID-19 pandemic has exposed mobility inequities within cities. In response, cities are rapidly implementing street reallocation initiatives. These interventions provide space for walking and cycling, however, other mobility needs (e.g., essential workers, deliveries) may be impeded by these reallocation decisions. Informed by mobility justice frameworks, we examined socio-spatial differences in access to street reallocations in Seattle, Washington and Vancouver, British Columbia. In both cities, more interventions occurred in areas where people of color, particularly Black and Indigenous people, lived. In Seattle, more interventions occurred in areas where people with disabilities, on food stamps, and children lived. In Vancouver, more interventions occurred in areas where recent immigrants lived, or where people used public transit or cycled to work. Street reallocations could be opportunities for cities to redress inequities in mobility and access to public spaces. Going forward, it is imperative to monitor how cities use data and welcome communities to redesign these temporary spaces to be corridors for their own mobility.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".