Honouring the Jay Treaty: Cross-Border Tuition Policies at Vancouver Island University and the University of Saskatchewan
Bibliographic record
Abstract
Aware of my position as a Settler researcher, I explore the question, “How can universities act on their responsibilities to Indigenous students under the Jay Treaty?” The Jay Treaty of 1794 recognized the pre-existing right of Indigenous peoples to cross the border between the United States and British North America (later Canada). Over the last 230 years, Indigenous communities have used the Jay Treaty to advocate for their rights to cross the border — a colonial division across Indigenous homelands. In 2023 Canada still does not recognize the Jay Treaty, while the United States does, though with blood quantum restrictions. In the absence of Canadian federal action, a growing number of Canadian universities have acknowledged the Treaty and waived the international tuition fee differential for Indigenous students crossing the border. Within a polishing the chain framework, a Haudenosaunee legal concept that describes a renewal of lapsed treaty relationship, I carried out interviews, surveying, and document analysis to understand how the Indigenous and Settler administrators at both universities relate to the policy, to Treaty, and to each other. Among my findings are that the policies were passed quickly through university administration once introduced, but only after decades of advocacy from both Indigenous students and staff. Settler respondents saw the passage of the policy as imperative, especially in the recent context of reconciliation in Canada. Policies differed among institutions, particularly around student eligibility and documentation requirements. All respondents noted the symbolic importance of the policies in recognizing Indigenous sovereignty across borders, but certain aspects of the policy reveal that the Treaty relationship has yet to be fully polished by universities. Institutions may have the power to set tuition rates, but they cannot adjust immigration status. At some research sites, few students have accessed the policy’s benefits, and eligibility criteria may be more restricted than the original Jay Treaty language. Finally, financial aid is only one factor in student success and should be matched with other supports, such as sufficient on-campus student services. In summary, universities, often hostile to Indigenous students, may have begun polishing the chain, but much polishing remains.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.045 | 0.014 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".