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Record W2903657202 · doi:10.22215/etd/2018-12938

Urbanville: Generative Urban Design in Vancouver's False Creek South

2018· dissertation· en· W2903657202 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNeighbourhood (mathematics)Futures contractProcess (computing)LimitingComputer scienceGenerative grammarSet (abstract data type)Urban planningMultitudeIdeal (ethics)Iterative and incremental developmentProcess managementManagement scienceOperations researchRisk analysis (engineering)Architectural engineeringEngineeringArtificial intelligenceBusinessCivil engineeringSoftware engineeringPolitical scienceMathematics

Abstract

fetched live from OpenAlex

As roadmaps for urban development, master plans have significant limitations. Such plans typically disregard the potential for change (economic, market demand, etc.) over the often-lengthy period of their projected build-out. As an alternative approach, can strategies be devised to ensure larger goals will be achieved without limiting the form that development takes along the way?Urbanville starts a discussion of alternatives to master planning in the form of an iterative and generative process that enables communities to establish goals, set targets, and devise metrics by which to assess various approaches to transformation. This performance-based process enables targets to be met in a multitude of formal variations.Vancouver's False Creek South neighbourhood is an ideal test case for this approach to urban design. As the city targets this neighbourhood for significant intensification, the process will help the community establish values and agree on performance standards by which to envision alternative futures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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 teacher head, not a consensus.

Study designNot applicable
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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