Basic Income and Anishinaabe Worldview: Exploring Tensions and Compatibilities
Bibliographic record
Abstract
Abstract Jurgen De Wispelaere and Lindsay Stirton point out that basic income must be designed in light of the features of the society in which the policy is to be implemented. Yet, in Canada, scholars and politicians have neglected one crucial aspect of the context in which basic income stands to be implemented – namely, a settler-colonial one. In a settler-colonial context, we must consider the compatibility of such a policy proposal with the worldviews of Indigenous peoples who continue to assert, apply, and revitalize their laws on this land. As such, in this paper, I consider the compatibility of a basic income with Anishinaabe worldview and legality. Ultimately, I find that while dominant justifications for basic income are not compatible with Anishinaabe worldview, the implementation of the policy may nonetheless support the urgent imperative of Indigenous law revitalization.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.063 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".