Bibliographic record
Abstract
The context for planning at the turn of the 19th century, in a newly industrialized world, was based on the need to find solutions to overcrowding and dire urban conditions.Planning decisions made in the post-World War II period were primarily motivated by the desire to reconstruct war torn cities.The forces of influence for planning and development in modern advanced capitalist societies are arguably set within the context of sustainable development.Many developed countries have witnessed a dramatic change in their territorial structures.Urban centres are extending into rural areas and surrounding hinterland, where large tracts of land are being developed in a 'leapfrog' low-density pattern.Urban sprawl is the outcome of both statistical realities such as population growth and the psychological catalyst that 'quality of life'is superior in the suburbs.This change has brought with it challenges commonly associated with unpredicted growth: traffic congestion, restricted access to education and a perceived lack of affordable housing.Smart growth, as an alternative philosophical and methodological approach towards urban planning may provide the antidote for the negative effects of urban sprawl.This paper examines the underlying theory of decentrist and centrist development and the emergence of the smart growth movement as the antonym of urban sprawl.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.009 |
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".