Heterogeneity in Immigrants’ Municipal Engagement and Participation in Calgary
Bibliographic record
Abstract
Canadian political science has a long history of studying elections at the provincial and federal levels, but there is a gap in studying municipal elections. Additionally, Canadian political science has some interest in studying immigrant participation in provincial and federal elections, but more research on immigrant involvement in municipal elections is required. The limited research on immigrant voting behaviour also combines immigrant communities into homogeneous groups for research purposes, which does not allow for a nuanced understanding of immigrant communities. Canadian political science, therefore, needs more research regarding immigrant participation in municipal government, engagement in local elections, and the differences among immigrant communities. My research addresses these gaps in three ways. First, I explore the differences between immigrant and non-immigrant groups in Calgary to establish potential differences in their levels of interest and attention to municipal politics. I then address the differences among immigrant communities when it comes to their engagement with municipal governments and their participation in local elections. I then turn to potential policy implications that could help immigrant communities engage with local government and elections. My research finds that while there are similarities between immigrant communities, there are also significant differences. These differences are important because they can shape how immigrant communities see municipal politics or their desires to participate. My research finds that scholars need to think simultaneously less and more about immigrants in Calgary’s municipal elections. Scholars need to think less about immigrants and immigration in the sense that what matters most is the duration, or the amount of time spent in a city, not their immigration status. However, scholars also need to think more about immigrants, as there were substantial differences among immigrant communities regarding interest, knowledge, and policy preferences. My thesis helps to build on the current literature by suggesting how Canadian political science could expand research into municipal politics and immigrant voting behaviour in a way that helps demonstrate the similarities and differences among Calgary’s diverse communities. While the thesis discusses several aspects of municipal government and participation, my research emphasizes the heterogeneity of immigrant communities’ participation in municipal elections.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".