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Record W7110512612

A case study at The Forks

2018· dissertation· en· W7110512612 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanismGeneral partnershipIntervention (counseling)Urban designPracticumArchitectureUrban planningPsychological intervention
DOInot available

Abstract

fetched live from OpenAlex

In the summer of 2016, The Forks North Portage Partnership created a shared-use road using unique pavement markings and traffic calming infrastructure at The Forks on Fort Gibraltar Trail. This intervention was intended to provide cyclists equal right to the road and connect segments of The Forks’ cycle track. The design and implementation processes of the shared-use road contravened conventional planning practices, and were inspired by tactical urbanism – a relatively new approach to city-making emphasizing small-scale interventions. This practicum uses a case study approach to investigate The Forks’ shared-use road and explore tactical urbanism as a planning tool. Key informants and practitioners from Winnipeg’s planning community provide diverse perspectives on how to effectively incorporate tactical urbanism practices. The findings add to the growing library of tactical urbanism literature and provide lessons for future project proponents in the design and implementation of their own tactical interventions in Winnipeg.

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)0.002
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0180.003
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.027
GPT teacher head0.256
Teacher spread0.229 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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