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Reconciliatory Federalism

2023· article· en· W4367369208 on OpenAlexaffvenueabout
Liam Nohr

Bibliographic record

VenueFederalism-E · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsBrandon University
FundersAustralian Government
KeywordsFederalismIndigenousTreatyState (computer science)Government (linguistics)Public administrationCorporate governancePolitical scienceFederalistNew FederalismSociologyPolitical economyLawPoliticsEconomicsManagementEcology

Abstract

fetched live from OpenAlex

In 2015, Canada saw a Liberal government form under the young and energetic leadership of Justin Trudeau. After a Conservative government under Stephen Harper, Trudeau set out to bring a ‘fresh and exciting’ vision of Canada that prioritized reconciliation with Indigenous peoples. Thus “reconciliatory federalism” was born. Since then, discussions between Indigenous leaders and the federal government have increased exponentially, yet the undertones of Canada’s colonial history still play an evidentiary role in Canadian federalism. This paper seeks to evaluate Trudeau’s “reconciliatory federalism” in relation to the scholarly literature pertaining to Indigenous self-determination and Canadian federalism. Moreover, using definitions of Kiera Ladner’s treaty federalism and Martin Papillon’s multi-level governance as a theoretical framework, I seek to investigate if Trudeau’s vision of reconciliatory federalism can bridge the two scholarly camps together. While treaty federalism argues for a top-down approach to establish a nation-to-nation relationship between Indigenous peoples and the state, multi-level governance argues for a bottom-up approach in which Indigenous peoples find multiple avenues within the existing federalist structure to integrate into. Using the examples of the Wet’sewet’en Cree First Nation and the Manitoba Métis Federation, I seek to contextualize the implications of reconciliatory federalism in relation to the two scholarly camps.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.406
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.005

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 head0.031
GPT teacher head0.280
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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