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Record W4384697570 · doi:10.22215/etd/2023-15593

Reconciliation Through Canadian Cultural Institutions: Past and Future Perspectives on Federal Cultural Policy

2023· dissertation· en· W4384697570 on OpenAlexafffundabout
Daria Sleiman

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsCarleton UniversityCanadiana.org
FundersCrown-Indigenous Relations and Northern Affairs CanadaNational Cancer InstituteIndigenous and Northern Affairs CanadaAustralian Government
KeywordsGovernment (linguistics)ColonialismIndigenousFutures contractPolitical sciencePublic administrationCultural policyCorporate governancePublic policyLawManagementBusinessEconomics

Abstract

fetched live from OpenAlex

This thesis delves into the topic of reconciliation through Canada's national cultural institutions, offering new perspectives on the historyand possible futuresof federal cultural policy.It begins with an account of the history of Canadian cultural policy, including its imbrication with settler colonialism, up to when the federal government committed publicly to advance reconciliation.Then, drawing on NCI's annual reports for the years 2015-16 to 2019-20, it analyzes whether their activities meaningfully support the government's goal of reconciliation with Indigenous peoples.The thesis concludes that the government's approach of making reconciliation a priority for individual NCIs is ill-suited for addressing the colonial framework that made reconciliation necessary in the first place.Unravelling the intertwined histories of Canadian cultural policy and settler colonialism will require a coordinated systemic governance approach to reconciliation that unsettles epistemologies rather than ad hoc activities developed to meet broad government priorities in the short term.

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)0.008
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.826

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0400.030
Scholarly communication0.0180.006
Open science0.0020.005
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.000

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 head0.035
GPT teacher head0.373
Teacher spread0.338 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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