MétaCan
Menu
Retour à la cohorte
Enregistrement W2254997580 · doi:10.4324/9780203849897-11

The eroding distinction between intelligence and evidence in terrorism investigations

2010· article· en· W2254997580 sur OpenAlexaffabout
Kent Roach

Notice bibliographique

RevueSSRN Electronic Journal · 2010
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueTerrorism, Counterterrorism, and Political Violence
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésCircumstantial evidenceAdversarial systemHuman intelligenceTerrorismIdeal (ethics)Government (linguistics)LawNational securityPolitical sciencePsychologySociologyCriminologyPhilosophy

Résumé

récupéré en direct d'OpenAlex

These lines from Graham Greene’s classic Cold War novel, The Human Factor, capture traditional differences between intelligence and evidence. Intelligence is ‘patchy’2 and ‘circumstantial’ information about perhaps remote risks to national security. It can be contrasted with hard evidence that can withstand adversarial challenge in court. The proponent of the intelligence paradigm in The Human Factor is Dr Percival. He has no time for legal niceties or public trials. He poisons poor Arthur Davis, who turns out to be the wrong man, innocent of the charge of being a Russian mole in the British Secret Service. The proponent of an evidence-based approach is Colonel Daintry, nominally in charge of security but who is handicapped by having read law at Oxford University. Much water has crossed under the bridge since Greene wrote these words in the 1970s. Nevertheless, they provide an appropriate starting point for a discussion of the distinction between intelligence and evidence. The ideal types of intelligence and evidence are rooted in a Cold War consensus.Intelligence could be collected to inform government about security risks with the expectation that it would never be publicly disclosed beyond the narrow range of those who ‘need to know’ (and alas the occasional mole). In contrast, evidence was collected after a crime had been committed. It could be subject to cross-examination and adversarial challenge and would be used in a public trial to prove guilt beyond a reasonable doubt. These ideal types highlight the preventive aspirations of intelligence and the truth-seeking and retributive ideals of evidence. Although there have always been departures from the ideal types, the creation ofsweeping new terrorism offences after the 9/11 attacks in the United States has blurred the traditional distinctions between intelligence and evidence. These new offencesreflect an intelligence mindset that focuses on threats, risk, associations and suspicion as opposed to an evidence or criminal law mindset that focuses on acts, accomplices and guilt. One implication of the blurring of the distinction between intelligence and evidence is a convergence between the work of police forces and security intelligence agencies in terrorism investigations. This convergence is driven in part by the demands of prevention. The imperative that the dots must be connected before another major terrorist attack occurs is forcing police forces and intelligence agencies to work together more closely both at home and abroad. It is also likely to result in a greater tolerance for false positives, in which the innocent are identified as security risks or even arrested and charged with new offences designed to aid in the prevention of terrorism. The convergence is also being driven by a practical recognition that intelligence may have evidential value especially with respect to many new broad terrorism offences that criminalise remote acts of preparation and various forms of association. Intelligence may sometimes also be subject to disclosure to the accused in terrorism trials. The convergence between intelligence and evidence, and between the role ofsecurity intelligence agencies and the police, is not without difficulties. Sharp growing pains have been felt in both Australia and Canada. Police forces in the Dr Mohamed Haneef affair in Australia and in the Maher Arar affair in Canada made well-publicised mistakes in interpreting and using intelligence. In both cases, national police forces acted on patchy and inaccurate intelligence. Individuals who only had innocent associations with terrorist suspects were harmed in both cases. In the case of Arar, who was detained for almost a year and tortured when rendered from the United States to Syria, the harms were extreme. There are reasons to believe that domestic security intelligence agencies might not have made the same mistakes as the police did in these cases. The Australian Security Intelligence Organization (ASIO) did not view Haneef as a security threat and Arar was not included in the list of suspects that the Canadian Security Intelligence Service (CSIS) handed over to the Royal Canadian Mounted Police (RCMP) in the wake of 9/11. Intelligence agencies have more experience and expertise than the police in dealing with fragmentary intelligence and they may be less tempted to conclude that patchy intelligence is evidence of guilt. If the police have proved to be uncomfortable in the new world of intelligence,intelligence agencies have been just as uncomfortable in dealing with evidence. The failures of intelligence agencies in this regard can be seen in ASIO’s missteps in interviewing Izhar Ul-Haque without proper attention to his rights and in CSIS’s missteps in the Air India investigation, a number of security certificate cases and in its interrogation of a teenaged Omar Khadr at Guantanamo Bay. In all these cases, intelligence agencies have failed to respect basic legal standards with respect to the collection, retention and disclosure of evidence. The results of such missteps have been the dismissal of the prosecution in the Ul-Haque case and, in Canada, a series of adverse judicial rulings that CSIS has violated legal rights.3

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,372
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,003
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,044
Tête enseignante GPT0,336
Écart entre enseignants0,292 · 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 tête enseignante, pas un consensus.

Devis d'étudeThéorique ou conceptuel
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

Citations28
Publié2010
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueSSRN Electronic JournalMême sujetTerrorism, Counterterrorism, and Political ViolenceTravaux en français237 207