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Record W4401382414 · doi:10.3138/ijcs-2023-0012

A Comparison of Stephen Harper’s and Justin Trudeau’s Arctic Narratives: Toward a New Geography of the Canadian North

2024· article· en· W4401382414 on OpenAlexvenueaboutno aff
Laurence Cros

Bibliographic record

VenueInternational Journal of Canadian Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeArcticIndigenousPoliticsState (computer science)Identity (music)Political scienceSociologyEthnologyGeographyLawOceanographyAestheticsPhilosophy

Abstract

fetched live from OpenAlex

This article intends to compare the political narratives on the Canadian Artic produced by the governments of Conservative Prime Minister Stephen Harper (2006–2015) and Liberal Prime Minister Justin Trudeau (2015–2023), with a specific focus on the identity dimension of these two sets of political narratives. Harper’s Arctic narrative, served by a unique personal commitment of the PM, promoted a radical shift from the historic Canada centred on the Laurentian region to a new Arctic Canada and in so doing, created a new political geography of Canada. In Justin Trudeau’s Arctic narrative, priority was given to reconciliation through the development of state-to-state relations with Indigenous communities. Embodied by the person of Governor General Mary Simon and concretized by the cooperative approach of Trudeau’s Arctic and Northern Framework, this new agentivity of Northern Indigenous peoples has ushered in a new decolonial geography of the Arctic. Unexpectedly, these successive official narratives of Arctic Canada have proven complementary in striving to move the center of gravity of the country north, thus creating new perspectives on Canadian identity and political geography.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.091
GPT teacher head0.396
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes2
Has abstractyes

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