Solidarity: The history and future of Canadian BIPOC co-operation and co-operatives in context
Bibliographic record
Abstract
This paper is a reflection of my research and experiences over the course of my Masters of Environmental Studies degree, which culminated in my co-founding Freedom Dreams Co-operative Education, an organization designed to educate about the co-operative model from an intersectionality lens specific to Black, Indigenous and People of Colour communities and to enable coalition building in the solidarity economy. Culturally diverse forms of co-operation are not recognized or understood well by the Canadian co-operative sector, which has led to a dominant model of co-operatives held up by and continuing to perpetuate colonial, heteropatriarchal constructs. This is problematic in the active erasure of BIPOC contributions to the co-operative sector, ignoring the diverse, rich cultural traditions of co-operation, and leaving out demographics of groups and individuals who may benefit from the co-op model. My research was guided by the following questions: How do Canadian co-operators and co-op activists engage more diverse communities in the co-operative model and establish more equitable and inclusive co-ops? How does the co-op sector introduce tools and education to form co-ops for interested BIPOC co-operators? What is it about the Canadian co-operative model that has made it inaccessible to many BIPOC communities? Through my primary and secondary research via interviews, focus groups and a literature review I draw on what I have learned from various communities of Black and Indigenous co-operators, and engage with critical pedagogy, Community Based Participatory Research (CBPR), and decolonial theory. I argue that this is a pivotal time to reassess the Canadian co-operative sector in making room for more diverse voices and action, strengthening the wider solidarity economy with co-operative action and bringing co-operative values to work led by BIPOC co-operators, youth, and allies. The key findings of this research were that culturally diverse co-operation in Canada faces barriers of language, racism, and a lack of time, resources and trust. This paper is part of a portfolio which explores these themes and connects them to the broader body of work that explores co-operatives and the solidarity economy through an intersectional lens. This portfolio also includes a an appendix of partners building solidarity economy in Canada, a business plan outline for Freedom Dreams Co-operative Education and the framework for an upcoming workshop series analyzing the 7 Co-operative Principles using an anti-oppression lens, each intended to build on this reflection paper by creating practical tools for the co-operative sector.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.051 | 0.055 |
| Scholarly communication | 0.024 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".