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Record W2752693067

Community-led planning in(action): the Case of Kingsland, Calgary

2017· article· en· W2752693067 on OpenAlexaffvenueabout
Chris Bell

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNeighbourhood (mathematics)ConformityEnvironmental planningRendering (computer graphics)Action planLand-use planningCommunity planningPlan (archaeology)Community participationLand usePolitical scienceGeographySociologySocioeconomicsComputer scienceEngineeringManagementCivil engineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

This article examines the impacts of the Kingsland Community Plan (KCP), a document prepared by a local neighbourhood group, in shaping the built environment of Kingsland, Calgary. The research methodology combines document analysis with Actor-Network Theory as a theoretical approach. Applications to ‘rezone’ land within the Kingsland community district, filed from the KCP’s creation in October 2009 to December 2016, were analyzed for reference to and conformity with the goals and intent of the KCP. Overall the KCP has not been effective at directing land use change in Kingsland. However, the Plan has acted as an ‘informal’ intermediary, rendering visible the local neighbourhood group’s influence and interests within the planning process. Given recent initiatives to formalize civil society participation in Calgary’s planning system, this research may aid decision-makers in determining the appropriate role for neighbourhood groups.

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)0.005
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 score0.099
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0210.012
Scholarly communication0.0070.002
Open science0.0030.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.186
GPT teacher head0.463
Teacher spread0.277 · 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
Published2017
Admission routes3
Has abstractyes

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