Bibliographic record
Abstract
Introduction Other-than-human life in Vancouver's Stanley Park may have never been more audible to so many people as it was in spring 2020, as COVID-19 transformed Canadian space and society. The renowned urban wilderness park, a colonial idea erected over the traditional territories of Coast Salish First Nations, including the Musqueam, Squamish and Tsleil-Waututh, opened in 1888. Not long thereafter, Stanley Park became inextricably bound to the motor vehicle, its roads, and their ecological ruin. Then, on the morning of April 8, 2020, came an extraordinary rupture: the car park nearly vanished. For the first time in its colonial history, Stanley Park's roads excluded automobiles. The Vancouver Park Board took this radical move in order to limit the number of visitors while increasing physical distancing and local access to the outdoors. The car closure was not total. It did not include emergency services, public transit, municipal vehicles, and a highway that slices Stanley Park in two. Nevertheless, partly released from the jaws of motor vehicles – including the car but also the float planes typically roaring over its tree canopy and carbon thirsty passenger jets shaking the skies above – Stanley Park almost seemed to revert back to a more primeval, unadulterated version of itself protected from human pollution. Stanley Park's transformation from noisy car park to resurgent nature was a common story after COVID-19, which precipitated both a global surge in cycling and noticing nature (see also Volume 4, Chapter Four). It was a strange, ironic rupture: one ecological catastrophe (COVID-19, a zoonotic disease) pressing pause on another (the system of automobility). Stanley Park's transformation did not last long – the motor vehicle returned in late June to half its former road space, and then all of it by late September when new dedicated space for cycling was fully removed – and the cycling surge has failed to put a dent in greenhouse gas emissions (GHGs). Far worse, it could well be succeeded by the ecological calamity of expanded car use, causing more deaths than COVID-19, as people recoil from busy sidewalks, eschew public transit, purchase their first cars, and flood the suburban real estate market. Of the two blades in COVID-19's double-edged sword for cycling, automobility's expansion threatens a longer, deeper cut.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.129 | 0.016 |
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".