MétaCan
Menu
Back to cohort
Record W7045426664

Age, culture, and coping with loneliness

2006· article· en· W7045426664 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Repository of the University of Porto (University of Porto) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessCoping (psychology)DistancingSocial supportSocial isolationPortugueseFaithAge groupsSocial distance
DOInot available

Abstract

fetched live from OpenAlex

There is a great diversity in the available strategies for coping with loneliness. The present study is an examination of the influence of age and cultural background on coping with loneliness of people from two diverse cultures, namely the Canadian and Portuguese. One thousand three hundred and forty seven participants were recruited in Canada and in Portugal. They answered an 86-item questionnaire, reflecting on the beneficial coping strategies which they have used to deal with the pain of loneliness. The four age groups in each culture were composed of youth (13-18 years old), young adults (19-30), adults (31-58) and the elderly (60 and older). The coping strategies which were examined included Acceptance and reflection, Self-development and understanding, Social support network, Distancing and denial, Religion and faith and Increased activity. Results indicated that loneliness is approached and dealt with significantly differently by Canadians and Portuguese, More specifically, Canadians had much higher mean subscale scores than the Portuguese. While the four Portuguese age groups scored significantly differently on all subscales, the Canadian age groups had significantly different mean scores on all but the Social support network and the Increased activity subscales.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.171
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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 teacher head, 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

Citations3
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueOpen Repository of the University of Porto (University of Porto)Same topicHealth disparities and outcomesFrench-language works237,207