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Record W1537467089

Variations on Three Bodies of Knowledge

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

Bibliographic record

VenueInternational fiction review · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsAgathaMeaning (existential)EncyclopediaSet (abstract data type)Computer scienceGestureProcess (computing)Body of knowledgeEpistemologySociology of scientific knowledgePsychologyCognitive scienceArtificial intelligenceHistoryPhilosophyArt history
DOInot available

Abstract

fetched live from 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. …

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0060.038
Scholarly communication0.0160.018
Open science0.0030.013
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0090.002

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 head0.067
GPT teacher head0.391
Teacher spread0.324 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2003
Admission routes1
Has abstractyes

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