Bibliographic record
Abstract
There are several themes which recur in this account. The first is that Windsor has had a lengthy and ongoing cycling presence. Repeatedly there have been efforts to marginalize cycling -and indeed write cycling out of the transportation history of Canada’s “motor city”- but Windsor’s engagement with cycling has been significant and unbroken. Engagement with cycling racing has come close to falling off at times but cycling for utilitarian and recreational reasons never has. Another (near) constant in Windsor’s cycling history is unique to the City’s co-location with Detroit; Windsor’s cycling history has often been a cross-border cycling history. Excitingly, with the provision for active transportation on the new Gordie Howe Bridge which will link the two cities, cross-border cycling is on the verge of a renaissance. As the environmental, health, equity and city-building benefits of cycling come into sharp focus in the twenty-first century, it is an opportune time to highlight Windsor’s cycling past and present. In short, Windsor has been and is a cycling city, even if we have never fully realised the potential of our flat topography, mild winters, the good bones of our urban core, and proximity to rich natural and built heritage
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.004 |
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".