The Mixed Success of Nodes as a Smart Growth Planning Policy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
At a time of rising concern over urban sprawl and its adverse financial, quality-of-life, and environmental consequences, nodes assume growing importance within urban (and especially metropolitan) planning strategies. Nodes are defined as high-density multifunctional developments featuring a pedestrian-conducive environment and good public-transit accessibility. The article draws from the Toronto experience to explore reasons for the popularity of nodes among planning agencies, their limited capacity over recent years to attract new office and retail development, and difficulties in launching new nodes. It also investigates their problems in meeting walking and public-transit-patronage objectives. The article proposes four means of enhancing the smart growth performance of nodes: (1) improved planning coordination; (2) reliance on both incentives and coercion; (3) investment in public transit systems; (4) merging nodal and corridor approaches.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it