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Record W7013961019

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2018· dissertation· en· W7013961019 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBoundary (topology)OddsLiabilityAgricultureState (computer science)Investment (military)Agricultural development
DOInot available

Abstract

fetched live from OpenAlex

The Greater Toronto and Hamilton Area (GTHA) is in a state of constant and massive growth in terms of population, development and economic investment. This growth has generated pressures both within and at the peripheries of the cities contained within the Golden Horseshoe as they develop outwards to their legal boundaries. This pressure has taken many forms, including an explosive and unaffordable housing market, transportation infrastructure that is already at or beyond capacity, and corporate development pressures to bulldoze and build over the Greenbelt, the provincially-protected ring of vital ecological systems and agricultural enterprises that surround the GTHA. \nWhile the province has established certain legal frameworks to mitigate the pressures of growth and manage its future manifestations, so long as the interests of powerful developers and corporations are at odds with the strategies contained therein, there remains a risk that these frameworks – and the public interests that they protect – will be undermined or repealed. \nThis thesis is positioned at the boundary between rampant suburban development and the protected biological, agricultural and economic resources of the Greenbelt and lays out a case study for hybrid large format commercial retail development that addresses the needs of commercial land developers, a growing suburban population, a changing boundary landscape, and the ecological and agricultural interests of the Greenbelt.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.442
Threshold uncertainty score0.797

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 studies0.0050.001
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4420.095

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 head0.016
GPT teacher head0.225
Teacher spread0.209 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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