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Record W2884703046 · doi:10.1177/0020702018783321

US partisan perceptions of Stephen Harper’s shift in foreign policy

2018· article· en· W2884703046 on OpenAlexaffabout
Jonathan Paquin

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsForeign policyPrime ministerPerceptionWhite (mutation)Political scienceForeign relationsPolitical economyExecutive branchEconomic historySociologyPoliticsLawEconomicsPsychology

Abstract

fetched live from OpenAlex

While Stephen Harper’s foreign policy sparked heated debates during his entire tenure as prime minister, these debates were mainly confined to Canadian foreign policy circles. Little attention was paid to allies’ perceptions of these developments and, more specifically, to the perception of the United States, Canada’s main economic and security partner. How did the Bush and Obama administrations perceive these changes? Were they seen as a break from Canada’s past? Did Harper’s handling of foreign policy alter White House calculations with respect to Canada? Based on a series of semi-structured interviews conducted in Washington DC with executive officials a few months prior to the end of the Harper era in 2015, this essay shows that despite a widespread perception in Washington that Canada’s foreign policy approach had changed under Harper, partisanship was the main dividing line in terms of how this approach was perceived and assessed.

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)0.005
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.740

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0210.011
Scholarly communication0.0070.002
Open science0.0000.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.336
Teacher spread0.325 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

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