Evaluating the Planning Strategies for Urban Land Use: A Study on Bengaluru City, India
Bibliographic record
Abstract
Urbanization process emerges out of nonurban areas where the urban centres are created; basic services reach the villages and rural fringes. Here the land and inhabitants become urban and urbanization is well measured and expressed chiefly in terms of population, as more and more of the landscape becomes townscape, and people come to live in an environment, that is both physically and socially urban. Bengaluru, once called the Pensioners’ Paradise, where land was cheaper, and so where the fruits and vegetables. The British setup a cantonment and built beautiful villas to live in the comfort of the Garden City. As the city expanded with the blooming software industries and off shoring activities, it soon captured a firm position in the global map thus enhancing the process of urbanization. The challenge in this context, Bengaluru faces is to restore its livability while accommodating the over spilling population and their rising demand for housing, water supply, sewerage and transport facilities. Once a multisectoral land use, Bengaluru now possesses a concentric land use pattern which however maintains itself towards east and north thus projecting new suburb areas.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".