Bibliographic record
Abstract
Loneliness is a universal experience, which transcends age, gender, geography, and culture. Religion, and one's degree of religiosity, is known to significantly affect one's approach to life, behaviour, and social involvement. To understand how religiosity affects the coping methods used to deal with loneliness. Explore whether the coping with loneliness is influenced by one's degree of religious observance. A total of two hundred and fifty participants who were composed of 28 secular/traditional, 54 conservative and 168 orthodox, self-identified Jews living in Israel volunteered to partake in the study. They answered a 34 yes/no loneliness questionnaire which tapped the following coping techniques: Reflection & acceptance; Self-development & understanding; Social support network; Distancing & denial; Religion & faith; and Increased activity Results indicated that the three groups significantly differed in their manner of coping with loneliness only on the Religion & Faith subscale, which was intuitively expected. An overall MANCOVA did yield significant group differences in the means of coping with loneliness. ANCOVAs were subsequently calculated. Significant differences amongst the three groups were found in the Religion and Faith subscale, with Bonferroni indicating that both the Conservative and Orthodox groups reported significantly greater use of religion and faith as a means of coping than those adopting a secular or traditional approach to religion. Religiosity does affect the manner of coping with loneliness. The present was a preliminary study directed at Israeli Jews. Similar studies with people of other religious denominations could further highlight that issue.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
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".