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Record W2520972207 · doi:10.1177/2156869316667448

“A Quintessentially American Thing?”

2016· article· en· W2520972207 on OpenAlexaff
Atsushi Narisada, Scott Schieman

Bibliographic record

VenueSociety and Mental Health · 2016
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndividualismCollectivismSocial psychologyPsychologyMental healthIndividualistic cultureDevelopmental psychologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

A popular image of Americans is that they are among the most individualistic people on the planet. This long-standing myth has informed theorizing about the sense of control and its relevance for stress and mental health. Prior claims have suggested that differences based on individualistic and collectivistic values contribute to group differences in the sense of control. We analyze data from the World Values Survey to test this hypothesis, focusing on a comparison of Americans and individuals in East Asian societies. Findings demonstrate that Asians report lower perceived control than Americans—but adjustments for individualistic values do not explain these differences. The positive association between individualistic values and perceived control is stronger among Asians compared to Americans. Perceived control is associated most strongly with subjective well-being for Americans, but individualistic values do not explain the differences. Our observations question claims that Americans gain more from individualistic values while Asians are sanctioned for them. Given its significance for stress and mental health, it is essential to document social patterns in the levels and effects of perceived control. We contribute to that effort by uncovering unexpected patterns that challenge the claim that individualistic values—and their benefits for control—are a quintessentially American thing.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.045
GPT teacher head0.398
Teacher spread0.353 · 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
GenreCommentary

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

Citations9
Published2016
Admission routes1
Has abstractyes

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