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Record W2988654853 · doi:10.1017/s1752971919000162

Social bonding in diplomacy

2019· article· en· W2988654853 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.

fundA Canadian funder is recorded on the work.
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

VenueInternational Theory · 2019
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsnot available
FundersUniversity of OxfordLondon School of Economics and Political ScienceBritish International Studies AssociationMcGill University
KeywordsDiplomacySociologyPoliticsSocial psychologyFace (sociological concept)Interpersonal communicationSocial relationInterpersonal relationshipEpistemologyEmpirical researchPolitical sciencePsychologySocial scienceLaw

Abstract

fetched live from OpenAlex

Abstract It is widely recognized among state leaders and diplomats that personal relations play an important role in international politics. Recent work at the intersection of psychology, neuroscience, and sociology has highlighted the critical importance of face-to-face interactions in generating intention understanding and building trust. Yet, a key question remains as to why some leaders are able to ‘hit it off,’ generating a positive social bond, while other interactions ‘fall flat,’ or worse, are mired in negativity. To answer, we turn to micro-sociology – the study of everyday human interactions at the smallest scales – an approach that has theorized this question in other domains. Drawing directly from US sociologist Randall Collins, and related empirical studies on the determinants of social bonding, we develop a model of diplomatic social bonding that privileges interaction elements rather than the dispositional characteristics of the actors involved or the material environment in which the interaction takes place. We conclude with a discussion of how the study of interpersonal dyadic bonding interaction may move forward.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.071
GPT teacher head0.427
Teacher spread0.356 · 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