"'Anchorless Unknown': Affective Annotation and the Komagata Maru Beyond Repair"
Bibliographic record
Abstract
This article examines contemporary responses to the 1914 Komagata Maru incident, wherein 376 South Asian migrants seeking work in Canada were refused entry upon their arrival in Vancouver, British Columbia. Specifically, this piece studies three affective objects: two state apologies from Canadian prime ministers Stephen Harper and Justin Trudeau in 2008 and 2016, respectively, as well as a creative work—a hybrid of poetry and archival record—by South Asian Canadian writer Phinder Dulai, 2014's dream/arteries. The article argues that, through a focus on feeling and form, the state apologies operate as a performative liberal genre, whereas Dulai's poetry offers a unique affective counterpoint to the apologies. Given both forms' attention to official narratives and archives, their pairing reflects a study of what I name the "affective annotation" of historical record.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.029 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".