Settler Colonialism and Mainstream Economics
Bibliographic record
Abstract
The general purpose of this research is to ask how mainstream economics understands the nature of being (ontology) and how the discipline produces knowledge (epistemology). In this Major Paper, I critically study the Settler colonial patterns embedded in Canadian mainstream economics, and economics in general. First of all, I perform a content analysis of several Canadian economics textbooks with a specific look at three critical terms: land, wealth and economics. For the surveyed textbooks, the latter terms are absolutely detached, erasing Indigenous thought and bodies from economics education. I understand the disconnection as a biased and constructed narrative, as theoretically depicted by critical Indigenous studies and Settler colonial studies. All in all, the ontological basis of Canadian economics education reproduces the systematic violence of Settler colonialism: dispossession and replacement. Second of all, I investigate early and modern versions of the Staples thesis to outline the Settler colonial discourse at the center of Canadian economics history. For instance, Staples theorists do not critically connect the colonial foundations that enabled the commercial development of staples industries since the 17th century. Indeed, some Marxist and political science scholars argue that the study of staples industries in Canada requires a better focus on the socio-political context embedding economic relationships pertaining to a staples commodity. Finally, with a clearer picture of Canadian mainstream economics' ontology, I investigate how the discipline (in general) produces knowledge. Indeed, as the mainstream method for economists, mathematical-deduction reproduces knowledge that follows prior beliefs. If colonialism is erased from the memory, the ontology, of economists then it is a very narrowed history that economists rely on. Ultimately, I argue that economics is not innocent in its study economic relationships - all economic relationships (e.g. trading, gifts, energy, love and such). To conclude, I dare experiment with an accounting methodology using a revised Staples thesis and ecological footprint analysis, with a focus on petrochemical economic relationships within itself, the people and the land.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".