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Record W3157308839 · doi:10.5663/aps.v9i2.29381

How Can Urban Parks Support Urban Indigenous Peoples? Exploratory Cases from Saskatoon and Portland

2021· article· en· W3157308839 on OpenAlexafffundvenueabout
Chance Finegan

Bibliographic record

Venueaboriginal policy studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto MississaugaUniversity of TorontoYork University
KeywordsIndigenousGeographyExploratory researchEnvironmental planningNational parkPolitical scienceColonialismEnvironmental protectionSociologyArchaeologyEcologySocial science

Abstract

fetched live from OpenAlex

In Anglo settler states, parks and Indigenous peoples interact in myriad ways, given the tight connection between Indigenous peoples and land and that parks are manifestations of settler control of land and heritage. Current park–Indigenous research is limited by a focus on rural locales, despite that more than half of Indigenous peoples live in urban areas. This exploratory paper draws connections between literature rooted in urban Indigenous studies and park management. I argue the literature’s current emphasis on rural locales neglects to consider how urban parks, might contribute to reconciliation if they affirmatively support urban Indigenous identities and cultural activities. I use two mini case studies—the Meewasin Valley Authority (Saskatoon, Saskatchewan) and Fort Vancouver National Historic Site (Portland, Oregon)—to highlight some of the ways in which urban parks can support urban Indigenous peoples’ responses to persistent urban settler-colonialism.

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)0.002
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 score0.581
Threshold uncertainty score0.832

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.005
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.342
Teacher spread0.316 · 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

Citations8
Published2021
Admission routes4
Has abstractyes

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