Bibliographic record
Abstract
In both the United States and Canada, the taxation of Indigenous people is often viewed as an innocent tool for financing government operations. In the settler colonial context, however, taxation is not strictly a tool for financing the government – it is a powerful instrument for racial domination and forced assimilation of Indigenous people. This paper examines how colonial legal systems have utilized taxation not purely as a method of revenue collection but as a means to both secure white settler possession and to force assimilation on Indigenous people in order to delegitimize Indigenous sovereignty and enforce the Eurocentric definition of economic productivity and citizenship. Additionally, these taxations cause disproportionate financial effects on Indigenous communities and limit their economic opportunities. Drawing on the works of scholars Brenna Bhandar and Cheryl Harris, this analysis will reveal how taxation serves not solely as a method of revenue collection, but as an apparatus for upholding settler colonialism. From historical policies that explicitly categorized Indigenous people as “civilized” or “uncivilized” based on their tax status to contemporary rhetoric that frames Indigenous communities as economic burdens, taxation’s purpose is to maintain racial and economic inequities and reinforce the legitimacy of the settler colonial project.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.346 | 0.112 |
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".