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Record W4381284111 · doi:10.7202/1099940ar

Cosmopolitanism and Decolonization: Contradictory Perspectives on School Reform to Advance Reconciliation with Indigenous Peoples

2023· article· en· W4381284111 on OpenAlexaffabout
Terry Wotherspoon, Emily Milne

Bibliographic record

VenueInternational Journal for Talent Development and Creativity · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsMacEwan UniversityUniversity of Saskatchewan
FundersForskningsrådet om Hälsa, Arbetsliv och Välfärd
KeywordsCosmopolitanismVisionIndigenousContext (archaeology)CurriculumSociologyCitizenshipPedagogyDecolonizationCompassionPolitical scienceEnvironmental ethicsPublic administrationLawPolitics

Abstract

fetched live from OpenAlex

Canadian school jurisdictions have taken steps to accommodate objectives to advance cosmopolitan education reflecting principles such as global citizenship, compassion, tolerance, responsibility, and respect within school curricula and educational practice. At the same time, a parallel set of reconciliation-related educational reforms, aligned with the Calls to Action that accompanied the 2015 Truth and Reconciliation Commission final report, have also gained urgency. Elements of reconciliation processes complement visions of cosmopolitanism, including objectives to foster dialogue and understanding between groups and advancements towards more holistic orientations to pedagogy and knowledge. However, conceptually and in practice, several tensions emerge, especially in a context in which educational priorities are contested. In this paper, we explore these connections and tensions with reference to findings from our research examining public perspectives on educational reforms to support reconciliation.

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)0.020
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0140.087
Scholarly communication0.0120.008
Open science0.0020.012
Research integrity0.0040.007
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 head0.023
GPT teacher head0.345
Teacher spread0.322 · 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 designTheoretical or conceptual
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

Citations1
Published2023
Admission routes2
Has abstractyes

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Same venueInternational Journal for Talent Development and CreativitySame topicGlobal Education and MulticulturalismFrench-language works237,207