A Black Epistemology for the Social and Solidarity Economy: The Black Social Economy
Bibliographic record
Abstract
A Black epistemology in economics is needed to bring ethics back into business. Contributions of racialized people in the economy are ignored. Black and racialized scholars also find that their work is not cited, even by the most liberal-minded social economists. In the Americas, Black and racialized citizens innovate in the social and solidarity economy; yet their work goes unnoticed in the academic literature, or scholars approach them as the "Other" without invoking theory that reflects the very people they are writing about. Although the ills of neoliberal variants of capitalism are known, the diverse economies in which Black folk engage are less understood. Forcing White and European ideas on a non-White experience is limited in what it can do effect social change. Nor can we sever the Western ideologies in the field because it is this very bias why the Black radical tradition and other Black theories come into being. There is no shortage of Black writings on solidarity economics and they can now be housed in Black social economy. A Black social economy epistemology is politicized for goodness, and it is grounded theory, inclusive of the Black radical tradition, and lived experience because of the explanatory powers of these theoretical approaches to disrupt mainstream business and society.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".