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Record W2020653602 · doi:10.1086/ahr.115.4.1211

A. Lynn Martin . Alcohol, Violence, and Disorder in Traditional Europe . (Early Modern Studies, number 2.) Kirksville : Truman State University Press . 2009 . Pp. ix, 269. $48.00.

2010· article· en· W2020653602 on OpenAlexaff
Jessica Warner

Bibliographic record

VenueThe American Historical Review · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsState (computer science)CommissionCriminologyPsychologyHistoryLawSociologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

In the late 1960s, anthropologists Craig MacAndrew and Robert B. Edgerton teamed up to study how people in different cultures behave when they are intoxicated. The book that came out of that project, Drunken Comportment: A Social Explanation (1969), created a sensation, for it said that drunken behavior is learned and varies from culture to culture. People in some cultures become aggressive when they drink; people in others do not. The same logic led MacAndrew and Edgerton to conclude that the norms governing drunken comportment can and do change as a culture changes, and that cultures are perfectly capable of having different scripts for different settings. Aggressive behavior may be acceptable in some settings and unacceptable in others. I mention Drunken Comportment because it is the touchstone of A. Lynn Martin's work. In his book, Martin casts a wide net, covering four centuries (1300–1700) and three different drinking cultures (England, France, and Italy). Under the circumstances, it is surprising that he finds so few variations over time and across cultures—Italians drank the most but complained the least, women were vaguely more tolerated in drinking establishments in England than they were in France and Italy, and English law was distinctive because it deemed drunkenness an aggravating factor in the commission of a crime. In each century and in each culture he returns to the same conclusion: high levels of drinking did not correlate with high levels of interpersonal violence, and if there was any correlation, it was because drinking establishments inevitably attracted a rogues' gallery of “thieves, gangs of criminals, prostitutes and their pimps, gamblers, vagabonds, and other denizens of the underworld” (p. 161).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Review · Consensus signal: Review
Teacher disagreement score0.316
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.282
Teacher spread0.247 · 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 teacher head, not a consensus.

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

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

Citations0
Published2010
Admission routes1
Has abstractyes

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