Bibliographic record
Abstract
Capitalism is everywhere. Many Indigenous leaders and scholars argue that it is unavoidable and must be engaged, despite capitalism's sordid history as a means of assailing Indigenous lands and waters. I ask: Can capitalism be adapted to Indigenous values and principles? Can Indigeneity survive the encounter with capitalism? In this article, I look at the writings of three Indigenous academics - Robert Miller, Duane Champagne, and David Newhouse - and examine their positions on Aboriginal capitalism. Each author offers their perspective on the key problems facing Indigenous communities and individuals as well as the realities of tribal poverty and ubiquitous capitalist markets. How each author understands the key problems in "Indian Country" greatly determines their positions on potential solutions. I argue that capitalism cannot be Aboriginalized or Indigenized without radical, possibly transformative changes to core capitalist tenets. Similarly, I do not believe that Indigenous people and communities can actively engage with capitalist markets without radically changing their core values and principles. I acknowledge that change is a fact of life and society, but I do not believe that capitalism, as pervasive as it is, has to be the inevitable outcome of Indigenous desires for political, cultural, and economic autonomy. There are alternatives, and maybe some not yet imagined, but true alternatives that do not exploit our relatives and maintain balance and harmony in our homelands are worth our best efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.049 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".