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Record W4295706225 · doi:10.22329/tclr.v1i1.7480

Expanding the Role for the Minister of Foreign Affairs in a World of Conditional Extradition

2022· article· en· W4295706225 on OpenAlexaboutno aff
Joanna Harrington

Bibliographic record

VenueTransnational Criminal Law Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Criminal Justice and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsSurrenderLawEconomic JusticePolitical scienceState (computer science)Power (physics)ReceiptCommissionBusiness

Abstract

fetched live from OpenAlex

The imposition of conditions on extradition and the judicial acceptance of the use of assurances to address risks of unfair treatment or an unfair trial in a foreign state leads to a need to expand the role for the Minister of Foreign Affairs in matters of extradition. Using extradition from Canada as an example, this article recognizes that arguments of speed and efficiency have long given the Minister of Justice the determinative role in deciding whether a wanted person should be surrendered to another state. This concentration of power has not, however, sped up extradition in controversial cases, such as those concerning the extradition of Canadian citizens many years after the commission of the alleged crimes, and those involving crimes of a transnational nature that could be prosecuted in either Canada or another state. With the use of conditions and assurances as the means to improve the fairness of extradition, there is a need to make use of the expertise that resides within a foreign ministry to determine their content, appraise their credibility and reliability, and monitor their post-extradition performance. Amending the Extradition Act to require the justice minister to consult with the foreign affairs minister after the receipt of an extradition request and before ordering surrender is a recommended reform.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.081
GPT teacher head0.343
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2022
Admission routes1
Has abstractyes

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