Age, culture, and coping with loneliness
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".