A Black Perspective on Canada’s Third Sector: Case Studies on Women Leaders in the Social Economy
Bibliographic record
Abstract
While many Black Canadian women are innovators in the third sector, the contributions of Black people to the social economy go largely unnoticed in the academic literature. The social economy is not only a place of refuge for African-Canadians; it also provides a way for racially marginalized communities to co-opt resources. In fact, racialized Canadians are driven to be active in the third sector by the systemic bias and racism in the Canadian economy and society. To understand the place of the social economy among racialized people, we must recognize that Black and racialized people are not merely on the receiving end of aid and support, but that they lead and work within the social services sector. This paper utilizes Black liberation theory—specifically the concepts of self-help and co-operation—to analyze the work of five Black women leaders in non-profit organizations that reach thousands of people in Toronto. This study confronts the erasure of Black women in the third sector, and argues for the need to link liberation theory with the field of social economics in order to fully understand the significance of the social economy for Black and racialized people.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.048 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".