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Origins and Evolution of the North American Stable Peace

2020· book-chapter· en· W3098782235 on OpenAlexaffabout
David G. Haglund

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMilitary and Defense Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsHistoryGeographyGeology

Abstract

fetched live from OpenAlex

Abstract Interstate relations among the North American countries have been irenic for so long that the continent is often assumed to have little if anything to contribute to scholarly debates on peaceful change. In good measure, this can be attributed to the way in which discussions of peaceful change often become intertwined with a different kind of inquiry among international relations scholars, one focused upon the origins and denotative characteristics of “pluralistic security communities.” Given that it is generally (though not necessarily accurately) considered that such security communities first arose in Western Europe, it is not difficult to understand why the North American regional-security story so regularly takes an analytical back seat to what is considered to be the far more interesting European one. This article challenges the idea that there is little to learn from the North American experience, inter alia by stressing three leading theoretical clusters within which can be situated the scholarly corpus of works attempting to assess the causes of peaceful change on the continent. Although the primary focus is on the Canada–US relationship, the article includes a brief discussion of where Mexico might be said to fit in the regional-security order.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.088
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.012
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.210
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2020
Admission routes2
Has abstractyes

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