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Record W4220918999 · doi:10.1007/s00181-022-02219-3

Drinking is different!

2022· article· en· W4220918999 on OpenAlexaboutno aff
Marco Caliendo, Juliane Hennecke

Bibliographic record

Venuepublish.UP (University of Potsdam) · 2022
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsnot available
FundersOtto von Guericke University Magdeburg
KeywordsLocus of controlAlcohol consumptionQuarter (Canadian coin)GermanPsychologyAssociation (psychology)Social psychologyConsumption (sociology)Control (management)DemographyEconometricsEconomicsAlcoholSociology

Abstract

fetched live from OpenAlex

Locus of control (LOC) measures how much an individual believes in the causal relationship between her own actions and her life’s outcomes. While earlier literature has shown that an increasing internal LOC is associated with increased health-conscious behavior in domains such as smoking, exercise or diets, we find that drinking seems to be different. Using very informative German panel data, we extend and generalize previous findings and find a significant positive association between having an internal LOC and the probability of occasional and regular drinking for men and women. An increase in an individual’s LOC by one standard deviation increases the probability of occasional or regular drinking on average by 3.4% for men and 6.9% for women. Using a decomposition method, we show that roughly a quarter of this association can be explained by differences in the social activities between internal and external individuals.

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)0.005
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.055
GPT teacher head0.305
Teacher spread0.251 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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