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Record W4394000308 · doi:10.1093/isq/sqae062

Credibility in Crises: How Patrons Reassure Their Allies

2024· article· en· W4394000308 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Studies Quarterly · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCredibilityPolitical sciencePolitical economyBusinessEconomicsLaw

Abstract

fetched live from OpenAlex

Abstracts How do citizens of US allies assess different reassurance strategies? This article investigates the effects of US reassurance policies on public opinion in allied states. We design and conduct a survey experiment in five Central–Eastern European states—Estonia, Latvia, Lithuania, Poland, and Romania—in March 2022. Set against the backdrop of Russia’s invasion of Ukraine, this experiment asked respondents to evaluate four types of reassurance strategies, each a critical tool in US crisis response policy: military deployments, diplomatic summitry, economic sanctions, and public reaffirmations of security guarantees. The international security literature typically values capabilities for their deterrence and reassurance benefits, while largely dismissing public reaffirmations as “cheap talk” and economic sanctions as being ineffective. Yet we find preferences for the use of economic sanctions and public statements as reassurance strategies during crises, in part because these approaches help states manage escalation risks.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.167
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.075
GPT teacher head0.403
Teacher spread0.328 · 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