Abolishing Migrant Detention in Canada
Bibliographic record
Abstract
It is a frequent misconception that the Canadian criminal justice system and immigration detention system is more benign and less violent than that of its neighbor to the south. An abolitionist pedagogical approach in Canada can challenge the enduring myth of Canada as a benevolent, post-racial, multicultural nation and reveal the shadowy carceral state. In 2022, four activists came together to implement an abolitionist learning experience designed to raise consciousness on migrant detention in Canada. Our collaborative project, titled the “Detention Review Observation Project,” experimented with giving undergraduate students the theoretical and practical tools to grapple with the injustice of migrant detention in Canada and to consider how they might work towards the abolitionist work of dismantling the system and building alternatives in its place.1 Students worked with a migrant-led abolitionist organization in Toronto and learned how to engage in collective, community-based advocacy work. Our project provided an introductory opportunity to consider some aspects of the injustice brought about by the institution, practice, and procedures of migrant detention in Canada and beyond. In our own distinct voices, we offer a three-dimensional parallax view of the “Detention Review Observation Project,” from our respective social locations. In dialogue with other scholars experimenting with abolitionist pedagogical possibility, we elaborate on the project, its abolitionist theoretical underpinnings, its failures, successes and lessons.
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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".