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Record W4377822898 · doi:10.1177/00207020231175683

Hastening the inevitable: American intervention in the Canadian elections of 1962–1963

2023· article· en· W4377822898 on OpenAlexaffabout
Marshall Palmer

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsCarleton University
Fundersnot available
KeywordsVetoLegislatureIntervention (counseling)Political sciencePsychological interventionVulnerability (computing)Government (linguistics)Public administrationWork (physics)Power (physics)Political economyLawSociologyPoliticsPsychologyComputer securityEngineering

Abstract

fetched live from OpenAlex

In recent years, there has been much research on foreign electoral intervention (FEI). However, it is an open question as to whether successful interventions “work” for the intervener. Does the newly elected government adopt the policies that motivated the intervener to intervene in the first place? This paper makes a first step toward addressing that question. It argues that FEIs work when the elected government can overcome veto players in legislatures, be they parliaments, national assemblies, or congresses. For minority governments or cohabitational presidencies, overcoming these veto players is no easy task and may necessitate further interventions by the intervening power. American interventions in the Canadian elections of 1962 and 1963 serve as an illustrative case. The findings suggest that governments with large majorities or control over congressional/legislative branches are more likely to cooperate with intervening governments. These findings have implications for how we assess the vulnerability of democracies to FEI.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.995

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0220.006
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.017
GPT teacher head0.368
Teacher spread0.351 · 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 designNot applicable
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

Citations2
Published2023
Admission routes2
Has abstractyes

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