MétaCan
Menu
Back to cohort
Record W2991550914 · doi:10.1086/720647

Peaceful Neighborhoods and Democratic Differences

2022· article· en· W2991550914 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

VenueThe Journal of Politics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAllianceDemocracyArgument (complex analysis)EndogeneityGeopoliticsPolitical sciencePolitical economyPoliticsSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

Democracies are thought to behave differently from other states, particularly when cooperating in international institutions, such as alliances. We argue that these democratic differences depend on geopolitical environments that make cooperation possible. Although studies have demonstrated endogeneity between democracy and peace, few analyze the effects of this joint relationship on democratic differences. We explore this argument using the alliance literature and argue that the empirical finding that democracies are more reliable is driven by the tendency of democracies to cluster in peaceful environments. Alliances are more likely to be “scraps of paper” when found in more dangerous environments. By jointly modeling regime type and political environment using data on alliance termination from 1920 to 2001, we show that alliance reliability is a function of a threat environment. Our argument has important ramifications for a host of literatures focused on regime type, as well as current debates over the effectiveness of democratic deterrence.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.576

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 studies0.0010.000
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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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