MétaCan
Menu
Back to cohort
Record W2522887729 · doi:10.36939/cjur/vol24no2/art184

Indigenizing City Planning Processes in Saskatoon, Canada

2019· article· en· W2522887729 on OpenAlexaffvenueabout
R. Ben Fawcett, Ryan Walker, Jonathan Greene

Bibliographic record

VenueCanadian journal of urban research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsTrent UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousPolitical scienceIndigenizationSociologyMainstreamPublic administrationFraming (construction)Public relationsGeographyAnthropologyLawArchaeologyEcology

Abstract

fetched live from OpenAlex

The article examines how the City of Saskatoon’s strategies for working with Indigenouscommunities in high-level planning processes leading to its Strategic Plan 2013-2023 relate to three concepts framing the academic literature on how to re-calibratestate-Indigenous society relations at the urban municipal level: Indigenization, coproduction,and coexistence. We argue that indigenizing mainstream city planningprocesses through authentic forms of partnership will increase Indigenous densitywithin our shared cities. Qualitative interviews with leaders from City Hall andAboriginal communities revealed a disconnection between municipal and Indigenousparticipants’ ideas about inclusion. The City’s mechanisms of consultation engagedIndigenous communities as stakeholder interest groups, but not as autonomouspolitical communities wanting to share control as full partners. A civic culture andinstitutional structures that affirm and operationalize indigeneity would have improvedthe outcome of Saskatoon’s planning processes.

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 score0.146
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0200.006
Scholarly communication0.0060.001
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.067
GPT teacher head0.363
Teacher spread0.296 · 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

Citations18
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueCanadian journal of urban researchSame topicIndigenous Health, Education, and RightsFrench-language works237,207