MétaCan
Menu
Back to cohort
Record W2078728025 · doi:10.1163/18765610-02003015

Making Sense of Canada’s Public Image in China

2013· article· en· W2078728025 on OpenAlexaffabout
Yuchao Zhu

Bibliographic record

VenueJournal of American-East Asian Relations · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsChinaReputationNarrativeGovernment (linguistics)Identity (music)Image (mathematics)Nation brandingSoft powerProduct (mathematics)PerceptionPower (physics)PoliticsPolitical sciencePublic relationsAestheticsLawPsychologyLinguistics

Abstract

fetched live from OpenAlex

A country’s image is the product largely of one nation’s socially constructed perception (or misperception) of another nation. A country’s image may seem politically insignificant, but its image and associated identity are often socially meaningful and have an important impact on the overall milieu for narratives and discourses in international relations. This essay intends to make sense of Canada’s image among Chinese. It first defines the concept of “image” and specifically Canada’s image in China. Then, through examination of various aspects of image-making, such as symbolic individual figures, media venues, and popular topics, this article seeks to deconstruct this image. It argues that the Canadian image is important for Sino-Canadian relations because a country’s image and reputation are among the most valuable assets its people possess and a key component of soft power. The political weight of public image, however, is more the product of a country’s importance and less its image. For example, compared to the relatively negative public image of the United States in China, Canada’s more positive public image does not make it more important to China’s government or its people.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.847
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.301
Teacher spread0.285 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of American-East Asian RelationsSame topicInternational Relations and Foreign PolicyFrench-language works237,207