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Record W7020618058

Loneliness and life satisfaction amongst three cultural groups

2008· other· en· W7020618058 on OpenAlexaboutno aff

Bibliographic record

VenueBrunel University Research Archive (BURA) (Brunel University London) · 2008
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessLife satisfactionCollectivismAssociation (psychology)Scale (ratio)UCLA Loneliness ScaleGroup cohesivenessCohesion (chemistry)
DOInot available

Abstract

fetched live from OpenAlex

Abstract
\nStudies into loneliness and life satisfaction have rarely assessed the role of culture in moderating the
\nrelationship between these variables. The present study examined the relationship between loneliness and life
\nsatisfaction using data from three nonstudent samples collected from Italian, Anglo-Canadian and
\nChinese-Canadian populations. A total of 206 respondents completed the Revised UCLA Loneliness Scale
\n(Russell, Peplau, & Cutrona, 1980) and the Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin,
\n1985). Two contrasting hypotheses were compared: one, a “postmodern” hypothesis, predicting that the
\nrelationship between life satisfaction and loneliness would be stronger in our individualist sample of
\nAnglo-Canadians, and a second, “relational” hypothesis predicting this association to be strongest in our
\ncollectivist, Chinese-Canadian sample. Our findings demonstrated that culture has a small but significant
\nimpact on the relationship between loneliness and life satisfaction, and, consistent with the relational
\nhypothesis, the relationship between the two concepts was strongest among our Chinese-Canadian
\nrespondents and weakest among our Anglo-Canadian participants This finding is discussed in the context
\nof the strong expectations of social cohesion in collectivist societies.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0030.007
Scholarly communication0.0000.002
Open science0.0030.004
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0020.005

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 head0.043
GPT teacher head0.261
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

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