Migrant Memory, Movement, and Misrecognition: Reactivating Diasporic Experience Toward an Anticolonial Politics of Place
Bibliographic record
Abstract
How might diasporic experiences of loss and displacement aid immigrants in responding to and acknowledging Indigenous lands and territories? Drawing from my own immigrant experience, I retrace and reinvent my movement in Tkaronto through walking practices that recover memories of migrancy as a newcomer to the land known as Canada. Such memories can be useful sources for immigrants to consider their relationship to settler colonialism. Reactivating them through movement might elicit a new responsiveness to the land as well as recognition of its caretakers and their struggles. I reflect on the possibilities that such a practice of walking and thinking through embodied memories can open up for undoing the coloniality of thought that underpins migrant aspirations for “a better-than-survival kind of living” (Berlant) and that so often results in assimilation to, and participation in, a settler colonial state.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".