The costs of infill versus greenfield development: a review of recent literature
Bibliographic record
Abstract
This paper reviews recent literature related to assessments of the total community costs of developing infill versus greenfield areas. These cost comparisons include: essential infrastructure such as roads, transport, water and sewerage; other infrastructure such as new schools versus under-utilised schools; community services, such as police and health; public transport; and social costs such as comparisons of environmental conditions and air quality. Given the unique mix of infill and greenfield development in Sydney, we undertake this literature review with specific reference to Sydney as an Australian case study. We found that while there are many comparisons of specific costs such as transport infrastructure, there are few studies that have attempted to quantify all the costs in a structured and comparable manner. The trend to sprawl is not generally seen in the older developed nations, such as those in Europe, to the extent that it occurs in rapidly growing wealthy western countries such as the United States, Canada, and Australia. Overall, the literature tends to favour infill redevelopment over greenfield development, because of lower costs, demand for housing close to the CBD, and reduced contribution to greenhouse gas emissions. (a) For the covering entry of this conference, please see ITRD abstract no. E214666.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".