Bridging and Bonding: Ethnic Background and Voluntary Association Activity in Canada
Bibliographic record
Abstract
This paper is the first Canadian analysis to consider voluntary association activity among a large array of ethnic groups, using national sample survey data and applying multivariate controls. Findings from the Economy, Security, and Community Survey of 2000 indicate that most of Canada’s major ethnic or racial minority groups differ little in their average number of voluntary association involvements. The main exceptions are relatively low levels of association membership for Latin/Central/South Americans and East Asians, especially before controls, and quite high levels for the Jewish minority. Further analyses reveal that minorities are more likely than other groups to join associations related to their own particular ethnic group and that this partly accounts for the relatively small differences in overall voluntary activity between ethnic minorities, on the one hand, and non-minorities, such as North/West European and British respondents, on the other hand. The implications of these results for understanding the “bridging” and “bonding” roles of voluntary associations in Canadian society are briefly discussed. Cet article présente la première analyse canadienne sur les activités d’associations de bénévolat au sein d’un grand nombre de groupes ethniques, à partir d’une enquête de 2000 sur l’économie, la sécurité et les communautés, portant sur un échantillon national et y appliquant des contrôles multivariables. Selon les résultats obtenus, au Canada l’engagement dans ces associations n’est en moyenne guère différent pour la plupart des groupes, qu’ils appartiennent à des majorités ethniques ou à des minorités raciales. Les principales exceptions sont soit des niveaux relativement bas de membres, quand ils viennent d’Amérique latine / centrale / du Sud et d’Asie de l’Est, en particulier avant les contrôles, soit des niveaux nettement plus élevés dans la minorité juive. Des analyses plus poussées révèlent que dans les minorités, on se joindra plus qu’ailleurs à des associations reliées à son propre groupe ethnique , d’où en partie les différences, somme toute mineures, dans les acti-vités de bénévolat en général entre les deux : minorités ethniques d’une part, et non-minorités d’autre part, telles qu’Européens du Nord et de l’Ouest, ainsi que britanniques. Nous examinons brièvement ce qu’impliquent ces résultats qui permettent de comprendre les rôles de “relais” et de “liaison” que jouent les associations bénévoles dans la société canadienne.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".