Sense of belonging to local community in small-to-medium sized Canadian urban areas: a comparison of immigrant and Canadian-born residents
Bibliographic record
Abstract
BACKGROUND: Sense of belonging is recognized as an important determinant of psychological and physical well-being. Research in Canada has shown that sense of belonging has increased in recent years although important variations exist between regions and among certain ethnic groups. METHODS: The objective of this paper is to examine differences in sense of belonging to local community between Canadian-born and immigrant residents in three small-to-medium sized urban areas using primary data collected in: 1) Charlottetown, PEI; 2) Hamilton, Ontario, and 3) Saskatoon, Saskatchewan. A mixed method approach is used in the analysis. First, a household telephone survey (n = 1529) asked respondents to rate their sense of belonging. This data was analyzed by way of summary statistics and ordered logistic regression. Second, a series of focus groups with immigrants in the three cities included questions on belonging and well-being (n = 11). RESULTS: The research found that sense of belonging is very high in the overall sample and in the three study sites, particularly in Charlottetown, and that there are no significant differences in levels of belonging between Canadian-born and immigrant respondents. However, among immigrants, sense of belonging was significantly lower for those living in Canada for 5 years or less. Consistent with the literature, positive mental health was found to be strongly associated with a positive sense of belonging for both Canadian-born and immigrant respondents. For immigrants, positive sense of belonging was associated with full-time work and home-ownership, two factors not associated with the Canadian-born population. The paper also revealed that immigrants placed greater importance on knowing their neighbours on a first name basis and generally trusting people as determinants of a positive sense of belonging. Finally, the focus groups revealed that in addition to displaying a sense of belonging to their city of residence, immigrants also maintain strong feelings of belonging to their ethnic group. CONCLUSIONS: The paper concludes by offering several public health recommendations on how belonging can be enhanced among recent immigrants in smaller Canadian cities; these include improved coordination of services in order to contribute to a less overwhelming settlement process for immigrants.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".