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Record W3083763117

The MV Sun Sea: A Case Study on the Need for Greater Accountability Mechanisms at Canada Border Services Agency

2019· article· en· W3083763117 on OpenAlexaboutno aff
Lobat Sadrehashemi

Bibliographic record

VenueeYLS (Yale Law School) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityAgency (philosophy)Political scienceInternational lawPublic administrationLawSociologySocial science
DOInot available

Abstract

fetched live from OpenAlex

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

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.284
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2019
Admission routes1
Has abstractyes

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