Bibliographic record
Abstract
Lessons from two leaders in the liveable cities race, Vancouver and Melbourne, demonstrate that these cities have followed a quite similar development, policy and planning path and now ride the crest of the wave while facing comparable challenges in preparing for the future.Success in urban liveability speaks to the conditions of life for the luckily satisfied few.An urban liveability that is also sustainable is possible but demands thinking about two other groups for whom the city is responsible: those who cannot meet their needs today, and those who will live in the future city.Melbourne offers an exciting notion of what living in the city is for and a sociability in public life that benefits from an intact equity argument at the national scale.Vancouver, by contrast, offers a compelling vision of urban life, for good, throughout the life cycle, one that brings with it an increasingly interactive, partnership-oriented and aspiring relationship between urban residents and their local government.The City of Melbourne is the showpiece, the workplace, and the venue for the young and restless to play.Vancouver has a regional government able to do the heavy lifting of narrowing the urban/suburban divide in metropolitan vision and priorities.In Melbourne, no such metropolitan entity exists, and regional governance is the domain of the state government, protect-ing established relationships and sharing common interests with big developers.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.024 | 0.004 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.003 |
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".