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Homicide in Chicago from 1890 to 1930: prohibition and its impact on alcohol‐ and non‐alcohol‐related homicides

2009· article· en· W2077902100 on OpenAlexafffund
Mark Asbridge, Swarna Weerasinghe

Bibliographic record

VenueAddiction · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsHomicidePoison controlInjury preventionSuicide preventionHuman factors and ergonomicsOccupational safety and healthAlcoholMedical emergencyPsychologyCriminologyPsychiatryMedicineBiology

Abstract

fetched live from OpenAlex

AIM: The aim of the current paper is to examine the impact of the enactment of constitutional prohibition in the United States in 1920 on total homicides, alcohol-related homicides and non-alcohol-related homicides in Chicago. DESIGN: Data are drawn from the Chicago Historical Homicide Project, a data set chronicling 11 018 homicides in Chicago between 1870 and 1930. Interrupted time-series and autoregression integrated moving average (ARIMA) models are employed to examine the impact of prohibition on three separate population-adjusted homicide series. All models control for potential confounding from World War I demobilization and from trend data drawn from Wesley Skogan's Time-Series Data from Chicago. FINDINGS: Total and non-alcohol-related homicide rates increased during prohibition by 21% and 11%, respectively, while alcohol-related homicides remained unchanged. For other covariates, alcohol-related homicides were related negatively to the size of the Chicago police force and positively to police expenditures and to the proportion of the Chicago population aged 21 years and younger. Non-alcohol-related homicides were related positively to police expenditures and negatively to the size of the Chicago police force. CONCLUSIONS: While total and non-alcohol-related homicides in the United States continued to rise during prohibition, a finding consistent with other studies, the rate of alcohol-related homicides remained unchanged. The divergent impact of prohibition on alcohol- and non-alcohol-related homicides is discussed in relation to previous studies of homicide in this era.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.348
Teacher spread0.323 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations17
Published2009
Admission routes2
Has abstractyes

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