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Record W2323466647 · doi:10.1080/11926422.2014.934864

About face: explaining changes in Canada's China policy, 2006–2012

2014· article· en· W2323466647 on OpenAlexafffundabout
Kim Richard Nossal, Leah Sarson

Bibliographic record

VenueCanadian Foreign Policy Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsQueen's University
FundersAsia Pacific Foundation of Canada
KeywordsBeijingChinaSalience (neuroscience)Government (linguistics)Foreign policyPolitical scienceGeneral partnershipConstructivePolitical economyFace (sociological concept)Public administrationEconomicsPoliticsSociologyLawPsychology

Abstract

fetched live from OpenAlex

From the “strategic partnership” of the mid-2000s, the Canada-China relationship deteriorated rapidly after the election of the Conservative government of Stephen Harper in January 2006. The Harper government left no doubt that it had little desire to cooperate with the government in Beijing, and the Chinese government reciprocated with a series of snubs directed at Ottawa. By 2009, however, the Harper government abruptly changed its approach and both sides demonstrated a renewed commitment to constructive engagement. Using the literature on foreign policy change, we explore the endogenous and exogenous reasons for this turn, focusing on the implementation of a new Conservative brand of foreign policy, Ottawa's response to the global financial crisis, and the salience of the particular people-to-people links that form the backbone of the bilateral relationship.

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)0.001
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.780

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0070.003
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0140.000

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 head0.013
GPT teacher head0.261
Teacher spread0.248 · 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

Citations22
Published2014
Admission routes3
Has abstractyes

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