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Enregistrement W2022591664 · doi:10.2307/40204020

Learning Lessons (And How) in the War on Terror: The Canadian Experience

2004· article· en· W2022591664 sur OpenAlexaboutno aff
Wesley K. Wark

Notice bibliographique

RevueInternational Journal Canada s Journal of Global Policy Analysis · 2004
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueIntelligence, Security, War Strategy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPolitical scienceWar on terrorPolitical economyTerrorismSociologyLaw

Résumé

récupéré en direct d'OpenAlex

LEARNING LESSONS IS AN UBIQUITOUS URGE. Armies do it; international organizations such as the United Nations practice it; businesses engage in it; individuals rely on it to get on with life. The internet teems with examples of our appetite. Casual perusal of the amazon.com books site reveals thousands of current titles on learning lessons, spanning everything from business guides to success, to learning from nature and even, sadly, one's pets. The list speaks to a societal activity that seems both frenetic and routine.Yet in the world of security and intelligence, the practice of learning lessons has typically been viewed as more problematic. Resistance is generated by a host of factors, some unique to the culture of security and intelligence agencies. Internal exercises in learning lessons can be resource intensive, and therefore low in priority. They rarely have an obvious bureaucratic home, especially in decentralized systems, and can involve painful processes of self-criticism. They are seen as difficult to translate into practical, sustained measures. Perhaps most important, they cut against the grain of an intensive focus on current operations and forward-looking strategic assessments. To be willing to engage in learning lessons, security and intelligence communities have to be prepared to value the past, and to believe that there are important lessons to be learned from history. Such beliefs are rare. To add to the friction, externally generated exercises in learning lessons are often perceived by security and intelligence communities not just as diversions from important ongoing requirements but as exercises in scapegoating, coming as they usually do on the heels of scandal and failure. This only reinforces a reluctance to engage in an analysis of past performance and can create a climate in which failure or weakness is always cast off as an orphan.But the events of 11 September 2001 and the Iraq war have rocked the foundations of the world of intelligence. The enormity of the intelligence and policy failures that characterized both the al Qaeda strikes of 11 September and the origin and conduct of the war in Iraq have had two significant side-effects. One is the onset of a crisis of public confidence in security and intelligence services, along with enormous confusion about where the boundaries between intelligence and policymaking do and should lie. The reputation of intelligence services has been laid low, perhaps lower than at any previous moment in their modern history.An equally powerful side-effect of these recent events has been an enhanced desire and demand for greater transparency and accountability. In an age of counterterrorism and global preemption, where much rides on intelligence services getting it right, and where expanded government powers raise natural anxieties about threats to civil liberties, citizens want to know more, profoundly more, about hitherto secret or secretive institutions of the state.In the context of these twin effects-rock bottom confidence and greater public assertiveness-the practice of learning lessons takes on new meaning and gravity. Craig Whitney of the New York Times, in his introduction to an edition of the 9/11 commission report, gave efforts to learn lessons in the public domain a high calling: demanding accountability from the elected and appointed officials of government, and insisting on revealing and correcting their shortcomings, are the most basic rights and duties of citizens in a democracy.1The US 9/11 commission report is only one, albeit the most famous, of a spate of high-level reviews and inquiries into the performance of security and intelligence agencies that have flourished in a variety of countries since September 11. In addition to an intensive effort in the United States, the United Kingdom, Australia, and Israel have all embarked on significant public efforts to learn lessons about the failures of intelligence since September 11. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,012
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,835
Score d'incertitude au seuil0,969

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,012
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0840,020
Communication savante0,0130,007
Science ouverte0,0050,010
Intégrité de la recherche0,0060,013
Charge utile insuffisante (le modèle a refusé de juger)0,0260,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,025
Tête enseignante GPT0,364
Écart entre enseignants0,340 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2004
Routes d'admission1
Résumé présentoui

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