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Record W1979591668 · doi:10.1080/09640560020001719

Brownfield Redevelopment versus Greenfield Development: A Private Sector Perspective on the Costs and Risks Associated with Brownfield Redevelopment in the Greater Toronto Area

2000· article· en· W1979591668 on OpenAlexfundaboutno aff
Christopher De Sousa

Bibliographic record

VenueJournal of Environmental Planning and Management · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBrownfieldRedevelopmentGreenfield projectEnvironmental planningBusinessAttractivenessPrivate sectorVariety (cybernetics)Natural resource economicsCivil engineeringEngineeringEconomicsEconomic growthGeography

Abstract

fetched live from OpenAlex

This paper examines the nature of the economic costs and risks involved in brownfield versus greenfield redevelopment in the Greater Toronto Area (Ontario, Canada) from a private sector perspective, and assesses the potential effectiveness of different policies and programmes designed to attenuate associated costs and risks. Through interviews, case-studies and an analysis of hypothetical development scenarios, it has been found that the perception that brownfield redevelopment is less cost-effective and entails greater risks than greenfield development, on the part of the private sector, is true for industrial projects in the province, but not for residential ones, which were found to be feasible, given the assumptions of the present study. Furthermore, the study has found that the attractiveness of residential brownfield projects can increase considerably with minor policy changes, but that promoting industrial redevelopment will require a more vigorous approach that employs a variety of environmental policy and economic development measures.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.671

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.049
GPT teacher head0.288
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations157
Published2000
Admission routes2
Has abstractyes

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