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Record W2175349142

On the Problem of Re-Recognition in Contemporary Sino-Italian Relations

2015· article· en· W2175349142 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCross-cultural communication · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Political and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsLaggingChinaVariety (cybernetics)Political scienceSociologyLawComputer scienceArtificial intelligenceMathematics
DOInot available

Abstract

fetched live from OpenAlex

China and Italy enjoy a glorious history of friendly exchanges. In spite that the development of Sino-Italian relations has been relatively smooth and steady, the two countries are still facing a variety of problems, which are mainly due to the lack of necessary knowledge about each other. Mutual understandings between the two parts have been lagging behind their bilateral exchanges and cooperation. In other words, the two nations need to “re-recognize” each other in new situations and contexts. This paper reviews briefly the three main stages of Sino-Italian relations since the establishment of the People’s Republic of China, introduces different importance placed on their bilateral relations in different periods, deconstructs their changing understandings about “the other” and gives an explanation to a number of typical shortcomings that the two peoples are facing in the re-recognition.

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.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.134
GPT teacher head0.393
Teacher spread0.258 · 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