A Journey towards Allyship: How Middle-class, Second Generation South Asian Canadian Mothers Challenge Anti-black Racism
Bibliographic record
Abstract
This study explores how self-identified middle-class second generation South Asian Canadian mothers journey towards allyship with racialized Black people in dismantling anti-Black racism. Using Participatory Action Research principles, as well as Critical Race Theory and Intersectionality Theory as frameworks, three key findings emerged from the data. First, the journey towards allyship begins with envisioning ourselves as racial justice allies and determining what that means to us, doing the introspection work to examine our own internalised racism, and then working to unlearn those perspectives. The journey towards allyship moves forward by acknowledging our capability to address anti-Blackness in our familial and social networks as well as in institutions such as schools and workplaces. And, the journey towards allyship is sustained by the support of middle-class, second generation South Asian Canadian mothers with similar anti-racism goals sharing resources and stories of their journeys thereby catalysing new understandings of privilege and oppression together. These findings are a meaningful contribution to larger scale efforts in addressing anti-Black racism and achieving social justice for racialized Black people. They are also a contribution to the growing body of research on middle-class second generation South Asian Canadians and, a source of inspiration for us as individuals and as a supportive community of mothers to continue our journey as aspiring allies of colour beyond the scope of this project.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".