Civic Engagement in Canada: A Critical Analysis of Social Media, Care for Others, and Gender on Volunteering and Donating
Bibliographic record
Abstract
Canadians continually donate their time and money to charitable and non-profit organizations. Donating and volunteering are forms of civic engagement which many choose to engage in to improve the lives of others. Existing literature regarding civic engagement lacks focus on general volunteering and donating as opposed to event-specific volunteering and donating. We used Alberta survey data (n=1208) gathered by the University of Alberta’s Population Research Laboratory to explore relationships between social media, care for others, and gender on civic engagement. Using this data, we conducted a multivariate logistic regression analysis to investigate these relationships. Our findings demonstrated that ‘following’ or ‘liking’ a community organization on social media impacts both forms of civic engagement. Next, the analysis showed that the belief regarding the importance of caring for others worse off than oneself is only related to donating. Finally, we found that gender was a significant indicator of both forms of civic engagement. The findings of this study provide important insights about the role of social media, care, and gender on civic engagement. Faculty Mentor: Shelley Boulianne Department: Sociology (Honours)
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".