Bibliographic record
Abstract
This chapter explores the ways in which border imperialism, a concept widely attributed to Harsha Walia (2013), interacts with international postsecondary remote learning contexts to open opportunities to both extend and resist border imperialism. Historical and present contexts of border imperialism centered on Canada are consulted, uncovering a connection between technologies of labor and colonial power dynamics. Both temporal contexts serve to highlight the ways in which technologies of labor create a colonial power dynamic enacted through the usage of borders as imperialist tools. The body of literature concerning border imperialism is then reviewed to discern how remote learning contexts facilitate both resistance to and expansion of border imperialism. It is found that these contexts do support narratives of resistance to bodily racism and temporo-economic imperialism, however, in so doing also support neo-racism and unjust soft power dynamics within internationalization. The opportunities for resistance and expansion of border imperialism are then consolidated in pursuit of an ethical path forward with respect to the usage of new remote learning technologies in the context of internationalization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".