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Record W4385074071 · doi:10.1111/add.16298

Addiction: A treatise from 1561

2023· article· en· W4385074071 on OpenAlexaff
Louise Nadeau, Marc Valleur

Bibliographic record

VenueAddiction · 2023
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAddictionThe RenaissanceMeaning (existential)PsychologyCognitionPsychiatryPsychoanalysisHistoryPsychotherapistArt history

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: In 1561, physician and philosopher Pascasius Justus Turq published a monograph on the description and treatment of pathological gambling. When the monograph came to the attention of the authors in 2006, there existed no known translation of it in any modern language. In 2014, it was translated and published in French. This paper analyses the monograph's key content elements and its place in the history of the concept of addiction. METHODS: A contextual analysis of the late Italian Renaissance, followed by key excerpts from the text and commentaries on the meaning and significance of the monograph. FINDINGS AND CONCLUSIONS: Pascasius Justus Turq's 1561 monograph on pathological gambling outlines a disease view of gambling, identifies cognitive processes and biological vulnerabilities as aetiological factors, avoids religious or moral judgements and recommends cognitive treatment to change the beliefs and expectancies of gamblers. This study shows that a 'disease formulation' of addiction was enunciated as early as the 16th century, and its contemporary resonance suggests that current clinical features of addictive disorders have existed for centuries.

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.005
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0080.003

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 head0.086
GPT teacher head0.377
Teacher spread0.291 · 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
Published2023
Admission routes1
Has abstractyes

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