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Enregistrement W1537467089

Variations on Three Bodies of Knowledge

2003· article· en· W1537467089 sur OpenAlexvenueno aff
Gerhard van der Linde, Els Wouters

Notice bibliographique

RevueInternational fiction review · 2003
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueIntelligence, Security, War Strategy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAgathaMeaning (existential)EncyclopediaSet (abstract data type)Computer scienceGestureProcess (computing)Body of knowledgeEpistemologySociology of scientific knowledgePsychologyCognitive scienceArtificial intelligenceHistoryPhilosophyArt history
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

A notable aspect of the problem-solving process--the primary task of the literary detective--is the continuous interplay between existing knowledge and knowledge directly related to the case in hand. This article focuses on describing and comparing the investigative approaches of arguably the three most famous literary detectives of the first half of the twentieth century, created respectively by Arthur Conan Doyle, Agatha Christie, and Georges Simenon, namely, Sherlock Holmes, Hercule Poirot, and Inspector Maigret, with reference to three bodies of knowledge: a body of knowledge existing prior to the investigation, knowledge of the investigative methodology to be used, and case-specific knowledge, gained in the course of the investigation. Knowledge that the investigator has prior to the investigation includes specialized factual knowledge and/or knowledge gained through previous experience. By drawing on a reservoir of specialized technical knowledge, the investigator is able to identify and interpret concrete data of which the meaning and significance escape his rivals. At the same time, or alternatively, the investigator has a mental catalogue, derived from previous investigations, containing information on crimes, criminal types, patterns of behavior and so on. Confronted with a set of events for which he has to find a rational explanation, the detective could use this body of knowledge as basis for a kind of encyclopedia, in which phenomena are grouped, annotated, and contextualized, and for a dictionary which enables him to interpret certain gestures and other observable phenomena; (1) or, through analogical thinking, to anticipate or interpret certain actions or events; to typify a suspect or clarify the profile of the victim; or to open up a line of investigation based on a technical understanding of particular data. In this respect, the investigator resembles a scientist who, upon observing a set of unexplained phenomena, first of all tries to explain it in terms of knowledge already at his disposal. The scientist works from the observed phenomena to its possible causes. If he succeeds in finding a readily explanation that adequately accounts for these phenomena, further investigation becomes superfluous. Only if such an explanation cannot be found, or if a readily explanation is found inadequate, do the phenomena become a problem worthy of further investigation. The search for a solution to the problem is continued by advancing conjectures that the investigator attempts to refute in view of the data, until a solution is found that can stand up to critical scrutiny. In the process of looking for a satisfactory explanation, the investigator makes use both of a first body of knowledge concerning phenomena similar to those constituting the problem (2) and a second body of knowledge related to the methodology accepted in the discipline concerned. (3) The detective usually cannot simply apply existing explanations to the case in hand in order to arrive at a solution, inasmuch as each case presents a new problem, involving different persons and events. Yet, knowledge gained from previous cases could facilitate the identification of clues and assist the detective in finding the correct lines of investigation, especially where problems are generically related. The nature of the problem remains basically constant, in that it always involves identifying the perpetrator of a crime, so that the investigative method of a particular detective does not change significantly from case to case. The scientific process is largely conventionalized; it starts with the unambiguous formulation of a problem that can be solved with the available methods of scientific inquiry, moves through the formulation and testing of one or more possible solutions, and culminates in the presentation of a solution that can be confirmed at least provisionally. (4) Similarly, the methodology to be used by the detective usually follows a basic pattern: once the basic facts of the problem are known, the detective systematically interviews and interrogates those involved, searches for and follows leads, regularly reviews the case up to that point, and puts forward hypotheses for the solution. …

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)0,011
score de la tête « metaresearch » (Gemma)0,027
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,060

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,027
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0070,008
Études des sciences et des technologies0,0060,038
Communication savante0,0160,018
Science ouverte0,0030,013
Intégrité de la recherche0,0060,005
Charge utile insuffisante (le modèle a refusé de juger)0,0090,002

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 Opus0,067
Tête enseignante GPT0,391
Écart entre enseignants0,324 · 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'étudeSans objet
Domainenon disponible
GenreAutre

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

En bref

Citations1
Publié2003
Routes d'admission1
Résumé présentoui

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