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Record W6998713787

Assessing Human Trafficking in Canada Flawed Strategies and the Rhetoric of Human Rights

2006· article· en· W6998713787 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsConventionHuman traffickingRhetoricArgument (complex analysis)RefugeeTorture
DOInot available

Abstract

fetched live from OpenAlex

This paper will present the argument that Canada's rhetoric of protecting the human rights of trafficking victims is at odds with its practice. Trafficking victims are treated essentially the same as any other irregular migrant, and the specter of trafficking is invoked to justify acts which arguably violate Canada's international human rights obligations. This paper will offer an overview of what little information is available regarding the extent of trafficking in Canada, and then will conduct a close examination of the Canadian approach to trafficking and its victims. In addition to considering the logic and consequences of the Canadian strategy for trafficking victims, Canada's practices are also considered in light of its obligations pursuant to the United Nations Convention on the Rights of the Child, the Convention and Protocol Relating to the Status of Refugees, the Convention on the Elimination of all Forms of Discrimination Against Women, and the Protocol to Prevent, Suppress and Punish Trafficking in Persons, Especially Women and Children (hereinafter "Palermo Protocol"). This paper will close with a brief look at how Canadian border control measures may increase the likelihood that asylum seekers will be forced to put themselves into the hands of smugglers and traffickers if they wish to bring a claim for protection in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.278
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.013
Science and technology studies0.0250.034
Scholarly communication0.0200.006
Open science0.0020.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2006
Admission routes1
Has abstractyes

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