The MV Sun Sea: A Case Study on the Need for Greater Accountability Mechanisms at Canada Border Services Agency
Bibliographic record
Abstract
In the summer of 2010, the human rights record of Sri Lanka in the aftermath of its civil war remained dismal.1 In Canada, the Immigration and Refugee Board’s acceptance rates for refugee claims made by Tamils �� eeing Sri Lanka was at approximately 84 percent.2 On 13 August 2010, a cargo ship, the MV Sun Sea (Sun Sea), arrived off the coast of British Columbia carrying 492 Tamil men, women, and children who were �� eeing Sri Lanka. Their voyage took just over two months, under horrible conditions. One passenger had died at sea. Most, if not all, had paid tens of thousands of dollars to board the ship to take this dangerous voyage. All made claims for refugee protection on arrival
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.060 | 0.010 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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".