The Role of Nonprofit Sector Networks as Mechanisms for Immigrant Political Participation
Bibliographic record
Abstract
Issues of immigrant political incorporation and transnational politics have drawn increased interest among migration scholars. This paper contributes to debates in this field by examining the role of networks, partnerships and collaborations of immigrant community organizations as mechanisms for immigrant political participation both locally and transnationally. These issues are addressed through an ethnographic study of the Hispanic Development Council, an umbrella advocacy organization representing settlement agencies serving Latin American immigrants in Toronto, Canada. Analysis of HDC’s three sets of networks (at the community, city and transnational levels) from a geographic and relational approach demonstrates the potentials and limits of nonprofit sector partnerships as mechanisms and concrete spaces for immigrant mobilization, empowerment, and social action in a context of neoliberal governance. It is argued that a combination of partnerships with a range of both state and non-state actors and at multiple scales can be significant in enabling nonprofit organizations to advance the interests of immigrant, minority and disadvantaged communities.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".