Bibliographic record
Abstract
In the Livable Region Strategic Plan formulated by its regional government, the Greater Vancouver Regional District (GVRD) in 1996, the Vancouver Metropolitan Area was highly rated as the most livable city in the world in the early 2000s due to growth management policies such as the formation of a compact metropolitan area and the development of and suburban centers linked to the expansion of public transportation networks. Since the late 2000s, the backlash of growth management policies and the rise in housing prices due to the activation of real estate speculation have become apparent, resulting in serious problems such as re-suburbanization and traffic congestion. The GVRD has formulated Metro 2050 in 2023 in cooperation with the metropolitan transportation authority, TransLink, and is trying to respond to the further population increase of one million by 2050, by forming a new urban center, Surrey Metro Centre, in the eastern suburbs where population growth is remarkable, and targeting stations and corridors with high public transportation convenience as Frequent Transit Development Areas for high-density development. Although such development imposes a large financial burden, it will continue to be widely supported as a universal attraction of a livable city that many residents desire.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.072 | 0.074 |
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".