Fringe Banking in Canada: The Collective Economies of Toronto’s “Banker Ladies”
Bibliographic record
Abstract
Rotating savings and credit associations (ROSCAs) are regarded as a time-honoured tradition practiced by many people around the world. African Canadians value ROSCAs because of how they have helped people adjust to Canadian life. This study examines ROSCAs and the role that African Canadians have played in Canada’s social economy. It includes interviews with 77 people, 46 of whom are “Banker Ladies”—African Canadian women who create community-driven financial cooperatives in Canada’s largest financial centre, Toronto. ROSCAs have been incubating within the Canadian diaspora for the past 70 years as a way to counteract the business exclusion. For the social economy in Canada to be reflective of society, the research and theories that drive the sector must reflect a cultural awareness of the various cooperative forms led by racialized Canadians.Plusieurs personnes dans le monde suivent la tradition vénérable des associations rotatives d’épargne et de crédit (AREC). Les Afro-Canadiens valorisent les AREC pour la manière dont celles-ci ont aidé les gens à s’adapter à la vie canadienne. Cette étude examine les AREC et le rôle joué par les Afro-Canadiens dans l’économie sociale du pays. Elle inclut des entretiens avec 77 personnes, y compris 46 femmes banquières—des Afro-Canadiennes créant des coopératives financières communautaires dans le plus grand centre financier du Canada, Toronto. Depuis 70 ans, les AREC persistent au sein de la diaspora canadienne afin de contrer les défaillances du système bancaire classique. Pour que l’économie sociale au Canada puisse refléter la société telle qu’elle est, la recherche et la théorie relatives au secteur doivent tenir compte des divers formats de coopératives menées par des Canadiens et Canadiennes racialisés.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".