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Record W2895793480

A Calculus of Interest Canadian Peacekeeping Diplomacy in Cyprus, 1963-1993

2015· article· en· W2895793480 on OpenAlexaffabout
Greg Donaghy

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsDiplomacyPeacekeepingCalculus (dental)Political scienceLawMedicine
DOInot available

Abstract

fetched live from OpenAlex

Fifty years ago, Canadian peacekeepers landed on the small Mediterranean island of Cyprus, where they stayed for thirty long years.This paper uses declassified cabinet papers and diplomatic records to tackle three key questions about this mission: why did Canadians ever go to distant Cyprus?Why did they stay for so long?And why did they leave when they did?The answers situate Canada's commitment to Cypress against the country's broader postwar project to preserve world order in an era marked by the collapse of the European empires and the brutal wars in Algeria and Vietnam.It argues that Canada stayed-through fifty-nine troop rotations, 29,000 troops, and twenty-eight dead-because peacekeeping worked.Admittedly there were critics, including Prime Ministers Pearson, Trudeau, and Mulroney, who complained about the failure of peacemaking in Cyprus itself.But their frustrations were offset by a triumvirate of humanitarian, diplomatic, and partisan justifications for soldiering on, and so, Canada stayed until the balance sheet of interests shifted in the 1980s.T h e r e h a s o f t e n been a whiff of wry cynicism associated with Canada's long, thirty-year role in Cyprus.Early on, rotating Canadian commanders greeted new arrivals with an ambiguous line from Shakespeare's Othello: "You are welcome, Sirs, to Cyprus."Departing officers wordlessly handed their reliefs a large sink plug

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.964
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.072
GPT teacher head0.298
Teacher spread0.227 · 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.

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

Citations0
Published2015
Admission routes2
Has abstractyes

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