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Record W2742042451

"Caveats Emptor: Multilateralism at War in Afghanistan"

2009· article· en· W2742042451 on OpenAlexaffabout
David P. Auerswald, Stephen M. Saideman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsMcGill University
Fundersnot available
KeywordsMultilateralismAllianceNorth Atlantic TreatyPolitical scienceDiscretionPublic administrationTreatyResentmentLawSociologyPolitics
DOInot available

Abstract

fetched live from OpenAlex

The North Atlantic Treaty Organization has been as the most robust alliance in the world, with deeply institutionalized processes, yet it has faced significant problems in running the International Security Assistance Force in Afghanistan. Specifically, the coalition effort has been plagued by the problem of caveats. Caveats place restrictions on what coalition militaries can and cannot do, and thereby create resentment within the coalition from countries that must bear a greater share of the burden as a result. In this article, we review key limitations facing military contingents operating in Afghanistan. We consider the sources of these restrictions and evaluate several explanations of the varying level of discretion experienced by deployed military commanders. We focus particular attention on the evolution of Canadian caveats to illustrate the dynamics in play and to generate hypotheses for future research. Finally, we address several strategies that commanders have used to diminish the effects of caveats. We conclude with implications for both research and policy. Acknowledgements: The Social Sciences and Humanities Research Council has funded much of this project as has the Canada Research Chair program, including the very helpful research assistance of Ora Szekely, Sarah-Myriam Martin-Brule, Mark Mattner, Lauren Van Den Berg, and Bronwen De Sena. Anne Therrien and Jamie Gibson of the Security Defence Forum, a unit of the Directorate of Public Policy within Canada's Department of National Defence, have been instrumental in setting up interviews with Canadian officers. We are very grateful for feedback we received when we presented earlier versions of this paper have been presented at Queen's University, Canada's Department of National Defence's Security and Defence Forum, the University of Ottawa, at the Canadian Political Science Association meeting in Vancouver, the International Studies Association meeting in San Francisco, and the American Political Science Association meeting in Chicago. Michael Tierney provided useful comments along the way.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.346
Teacher spread0.329 · 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

Citations4
Published2009
Admission routes2
Has abstractyes

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