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Record W2943356497 · doi:10.4087/xylj9053

Culture Display Rules of Smiling and Personal Well-being: Mutually Reinforcing or Compensatory Phenomena? Polish - Canadian Comparisons

2016· article· en· W2943356497 on OpenAlexaffabout
Daniela Hekiert, Saba Safdar, Paweł Boski, Kuba Kryś, Joy H. Lewis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer sciencePsychologyCognitive psychologyHuman–computer interaction

Abstract

fetched live from OpenAlex

Cultures vary in terms of emotional display rules, which include the expression of satisfaction and dissatisfaction. In Poland there is a norm of negativity, deriving from a culture of complaining (Wojciszke & Baryła, 2005), whereas in Canada, there is a tendency to express happiness (Safdar, Friedlmeier, Matsumoto, Yoo, Kwantes, Kakai, & Shigemasu, E., 2009). In the present research project, norms and values regarding smiling in public situations, norms regarding the affirmation of life and complaining, as well as individual measures of optimism (LOT-R) and well-being (SWLS) were measured among Poles and Canadians. The results showed that the cultural display rules endorsed by Canadian students affirmed smiling and positivity in social life more than those for Polish students. Contrary to expectations, optimism and the level of satisfaction with their own lives were significantly higher among Poles than Canadians. This may indicate a compensatory mechanism between normative displays and subjective experience. Other potential interpretations are also considered.

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 score0.112
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.048
GPT teacher head0.317
Teacher spread0.269 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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