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Record W3211307013 · doi:10.32920/ryerson.14639595.v1

The role of multiculturalism policy in addressing social inclusion processes in Canada

2021· preprint· en· W3211307013 on OpenAlexaffabout
Ilene Hyman, Agnes Meinhard, John Shields

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsToronto Metropolitan UniversityVictoria Park
Fundersnot available
KeywordsMulticulturalismInclusion (mineral)Political scienceContext (archaeology)Ethnic groupIdentity (music)SociologyGender studiesPublic policyPublic administrationLawGeography

Abstract

fetched live from OpenAlex

As we approach the 40th anniversary of Canada’s multiculturalism policy, the concept of multiculturalism is under attack in many jurisdictions. The leaders of Germany, France and Britain, have each declared that multiculturalism has been a failure in their countries, serving to separate and segregate, rather than integrate (Edmonton Journal, February 13, 2011). It seems timely therefore, to briefly review the origins and evolution of Canada’s multiculturalism policy and examine future directions in light of the changing global and national situation, and newly emerging public discourses on integration, inclusion and the meaning of Canadian identity. The focus of this paper is on the role multiculturalism policy plays in creating a more inclusionary society in the twenty-first century in Canada. We set the context by presenting a brief historical overview of multiculturalism policy since its introduction in 1971 and summarizing some of the recent Canadian discourse surrounding multiculturalism. One of the key questions we explore is whether multiculturalism policy should move beyond focusing on the integration of population groups marginalized by national, racial, religious or ethnic origins, to addressing broader social inclusionary processes that influence inequities and impact on nation. Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series,TRSM, Ted Rogers School of Management Citation:

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.357
Teacher spread0.320 · 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 teacher head, not a consensus.

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

Citations25
Published2021
Admission routes2
Has abstractyes

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