A Comparison of Stephen Harper’s and Justin Trudeau’s Arctic Narratives: Toward a New Geography of the Canadian North
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.042 | 0.027 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".