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Record W2581365168 · doi:10.1177/1948550616676879

Comparisons of Daily Behavior Across 21 Countries

2017· article· en· W2581365168 on OpenAlexaffabout
Erica Baranski, Gwen Gardiner, Esther Guillaume, Mark Aveyard, Brock Bastian, Igor Bronin, Christina Ivanova, Joey T. Cheng, F. Köck, Jaap J. A. Denissen, David Gallardo‐Pujol, Peter Haľama, Gyuseog Han, Jaechang Bae, Jung‐Soon Moon, Ryan Y. Hong, Martina Hřebı́čková, Sylvie Graf, Paweł Izdebski, Lars Lundmann, Lars Penke, Marco Perugini, Giulio Costantini, John F. Rauthmann, Matthias Ziegler, Anu Realo, Liisalotte Elme, Tatsuya Sato, Shizuka Kawamoto, Piotr Szarota, Jessica L. Tracy, Marcel A. G. van Aken, Yang Yu, David C. Funder

Bibliographic record

VenueSocial Psychological and Personality Science · 2017
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of British Columbia
FundersDivision of Materials ResearchGrantová Agentura České RepublikyNational Science Foundation
KeywordsPsychologyConscientiousnessOpenness to experienceNeuroticismExtraversion and introversionSocial psychologyHappinessBig Five personality traitsContext (archaeology)PersonalityDemographyPopulationGeography

Abstract

fetched live from OpenAlex

While a large body of research has investigated cultural differences in behavior, this typical study assesses a single behavioral outcome, in a single context, compared across two countries. The current study compared a broad array of behaviors across 21 countries ( N = 5,522). Participants described their behavior at 7:00 p.m. the previous evening using the 68 items of the Riverside Behavioral Q-sort (RBQ). Correlations between average patterns of behavior in each country ranged from r = .69 to r = .97 and, in general, described a positive and relaxed activity. The most similar patterns were United States/Canada and least similar were Japan/United Arab Emirates (UAE). Similarities in behavior within countries were largest in Spain and smallest in the UAE. Further analyses correlated average RBQ item placements in each country with, among others, country-level value dimensions, personality traits, self-esteem levels, economic output, and population. Extroversion, openness, neuroticism, conscientiousness, self-esteem, happiness, and tolerant attitudes yielded more significant correlations than expected by chance.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.311
GPT teacher head0.520
Teacher spread0.210 · 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 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

Citations8
Published2017
Admission routes2
Has abstractyes

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