MétaCan
Menu
Back to cohort
Record W4281293334 · doi:10.1177/10780874221100698

Municipal Parks, Recreation and Cultural Services in an Age of Migration and Superdiversity

2022· article· en· W4281293334 on OpenAlexaffabout
Livianna Tossutti

Bibliographic record

VenueUrban Affairs Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsBrock University
Fundersnot available
KeywordsRecreationMulticulturalismEquity (law)Ethnic groupPublic administrationMainstreamingCultural diversitySociologyDiversity (politics)Economic growthPolitical scienceImmigrationPublic relationsLawEconomics

Abstract

fetched live from OpenAlex

The goals of promoting diversity, equity and inclusion have gained currency in planning practice, and institutions are increasingly expected to address structural inequalities related to race, ethnicity and other forms of marginalization. This article examines how six Canadian municipalities have adapted their parks, recreation and culture strategic plans, policies, programs and services in response to international migration and racial diversity. The analysis of official documents and interviews with municipal officials and community representatives reveals that municipalities have adopted de facto multicultural planning practices aligned with the state paradigm of immigrant integration and national identity, even when the term “multiculturalism” is rarely employed in official discourse. They have also incorporated some aspects of mainstreaming into the planning repertoire. In Canada, mainstreaming is not an alternative to group-specific programing, but an additional mechanism for the recognition of difference in public institutions.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0040.005
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.029
GPT teacher head0.289
Teacher spread0.260 · 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 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

Citations5
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueUrban Affairs ReviewSame topicUrban Planning and GovernanceFrench-language works237,207