Sense of community referred to the whole town: Its relations with neighboring, loneliness, life satisfaction, and area of residence
Bibliographic record
Abstract
The aim was to explore the relationships between sense of community and various factors with respect to a fairly broad area (town, city, or large quarter of a metropolis). Degree of neighboring, life satisfaction, loneliness, and area of residence were also considered. Subjects included 630 men and women, aged 20-65 years, with different educational levels. They were individually administered a sociodemographic questionnaire, the Italian Sense of Community Scale, the Satisfaction with Life Scale, the University of California Loneliness Scale, and a Neighborhood Relations Scale. The subjects all live in Central Italy. They were divided into six groups as follows: one group living in a quarter of Rome, three groups living in three different areas of Grottaferrata (a hill town near Rome) and two groups living in two areas of Spoleto (the historical center and a working class suburb), a town in the Umbria region. Multiple regression analysis revealed the following: Neighborhood relations are stronger for women, for members of large families, for those with less education, for those living in the community for many years and for members of groups or associations. The strongest predictor of sense of community is neighborhood relations, although years of residence, being married, group participation, and area of residence are also significant factors. Sense of community is related to life satisfaction and loneliness in both the large and small town and in the city. Moreover, although sense of community is strongly associated with area of residence in Spoleto, this is not true for Grottaferrata. Overall, the results confirm the usefulness of conceptualizing the sense of community construct separately }}}{{{� Journal of Community Psychology, January 2001 }}}{{{from degree of neighboring. © 2001 John Wiley & Sons, Inc.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".