The evolution of the third sector during the COVID-19 pandemic: Next generation diasporic civic organizations (DCOs) among Bangladeshis in Toronto
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper examines the confluence of civic engagement and cyberspace by studying diasporic civic organizations (DCOs) within superdiverse and digitizing contexts. Civic engagement is crucial for DCOs, which often originate in superdiverse locales in migrant-receiving cities like Toronto. The paper explores how studying superdiverse locales provides a framework to move past ethnocentric interpretations of diasporic civic engagement and how digitization affects their organizations. The study focuses on three next-generation Bangladeshi Canadian DCOs through semi-structured interviews, digital archival analysis, and field notes. Findings show that digitization initially posed challenges due to inadequate support and resources during the early stages of the pandemic. However, digitization ultimately provided less resource-intensive interventions for a more dispersed audience. Simultaneously, unequal access to digital tools negatively impacts less-resourced, volunteer-run DCOs and their service recipients. Policymakers and service providers must find ways to support more effective and equitable digitization for DCOs originating in superdiverse locales.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it