The "Other" Mexicans: Transnational Citizenship And Mexican Middle Class Migration In Toronto, Canada
Bibliographic record
Abstract
Mexico has one of the highest numbers of emigrants in the world (Martin, 2009) and Canada is one of the states with the highest per capita immigration rates globally (Léonard, 2011). Mexico and Canada are typical examples of immigrant and emigrant countries and both countries have developed policies and strategies that aim to foster civic participation among their immigrant and emigrant population respectively (Martin, 2009; Goldring, 2002; Barry, 2002; Li, 2002; Reitz, 2005; Bauder, 2011). In Canada, academic research on immigration has centred on the effect immigration policies and practices have on including and excluding immigrants from exercising citizenship rights but it has tended to ignore the effect emigration policies have in the development of transnational citizenship practices, such as civic engagement, political participation, social activism, and acts of solidarity that transcend the frontiers of the nation-state. This has left important questions unanswered on how transnational citizenship is developed and exercised in a migration context including: 1) which policies and practices immigrants use to exercise transnational citizenship; 2) what is the impact of transnational citizenship practices in terms of the expansion and contraction of citizenship rights in the context of migration; 3) who is included and excluded by emigration policies promoting transnational citizen engagement; and 4) how do internal community issues, conflicts, cooperation, and solidarity affect the process of transnational enacting of citizenship? I attempt to fill this research gap by studying the effects Mexican emigration policies have on promoting transnational citizenship practices among middle class Mexican immigrants in Toronto and other cities in Ontario and by showing the avenues these immigrants use in order to participate civically with Mexico and with the Mexican diaspora in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.028 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".