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Record W2901496563 · doi:10.1080/11926422.2018.1543713

Political decision-making and the decline of Canadian peacekeeping

2018· article· en· W2901496563 on OpenAlexaffabout
Graeme Young

Bibliographic record

VenueCanadian Foreign Policy Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsBalsillie School of International Affairs
Fundersnot available
KeywordsPeacekeepingPoliticsPolitical sciencePolitical economyDevelopment economicsPublic administrationSociologyLawEconomics

Abstract

fetched live from OpenAlex

This article explores the reasons behind Canada’s declining participation in United Nations peacekeeping operations. It proposes a decision-making model that explains how politicians assess opportunities to commit personnel to peacekeeping missions by balancing their policy objectives with the pressures of electoral politics. Emphasizing the importance of voters in political decision-making processes, it argues that participation in peacekeeping is dependent on three key factors: a belief in the value of peacekeeping in principle; a belief in the value of a given peacekeeping operation; and risk aversion in response to the potential costs of peacekeeping. Tracing Canada’s declining participation in peacekeeping operations since the 1990s, it particularly focuses on how this calculus has, in different ways, limited Canada’s involvement in peacekeeping under Stephen Harper’s Conservative government and Justin Trudeau’s Liberal government, arguing that the former undervalued peacekeeping as a means of obtaining its foreign policy objectives and as a feature of national identity, minimizing the perceived benefits of participation, while the latter has focused on the inherent risks of peacekeeping despite a professed commitment to peacekeeping in principle, maximizing the perceived costs of further personnel commitments. The decisions of successive Canadian governments have led to a free-rider problem in which Canada is willing to enjoy the benefits of peacekeeping but unwilling to bear the costs.

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 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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
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 head0.022
GPT teacher head0.342
Teacher spread0.320 · 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 teacher head, not a consensus.

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

Citations10
Published2018
Admission routes2
Has abstractyes

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