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Record W4378672571 · doi:10.32920/23257607

A Few Choice Words: Discourse, Decolonization and the Dissolution of Indigenous and Northern Affairs Canada

2023· preprint· en· W4378672571 on OpenAlexafffundabout
Lauren Dubay

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsToronto Metropolitan UniversityUniversity of TorontoToronto Public Health
FundersIndigenous and Northern Affairs CanadaAustralian Government
KeywordsDecolonizationIndigenousGovernment (linguistics)Public administrationMandatePolitical scienceRhetoricLawPoliticsLinguistics

Abstract

fetched live from OpenAlex

Throughout its tenure, the Trudeau government has made public commitments to reform the relationship between Canada and Indigenous Peoples. In particular, the Trudeau government’s decision to dissolve Indigenous and Northern Affairs Canada and divide its mandate into two separate departments: Crown-Indigenous Relations and Northern Affairs Canada and the Department of Indigenous Services Canada has been framed as an avenue for decolonization. This paper seeks to determine, through an analysis of the new departmental changes, whether this reform exemplifies the federal government’s claims that it will facilitate decolonization and build an equitable relationship between the Canadian government and Indigenous Peoples. This study also analyzes the Trudeau government’s discourse using a critical discourse analysis to evaluate the rhetoric and intentions surrounding the federal government’s decision to dissolve INAC. From these analyses, it is evident that the dissolution of INAC does not coincide with the reconciliatory and decolonization discourse the federal government employs.

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)0.006
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 score0.936
Threshold uncertainty score0.464

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0190.032
Scholarly communication0.0090.004
Open science0.0010.002
Research integrity0.0020.003
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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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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