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Record W2993745820

The Use and Misuse of Secret Evidence in Immigration Cases: A Comparative Study of the United States, Canada, and the United Kingdom

2007· article· en· W2993745820 on OpenAlexaboutno aff
Stephen Townley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationKingdomPolitical scienceCriminologyLawPsychologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Secrecy is a hot topic. In particular, scholars and pundits have begun to fill the pages of law reviews and newspapers with their arguments about the extent to which the government should use secret evidence in legal proceedings. On the one hand, the government's conduct of the Combatant Status Review Tribunals and the rules of procedure it has promulgated for the military commissions at Guantanamo Bay have provoked complaints, as did the government's refusal to permit Zacarias Moussaoui access to certain terrorist witnesses detained abroad. On the other hand, many accept that the government may adduce secret evidence to justify blocking the assets of a charity that supports terrorism.

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)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.011
Science and technology studies0.0130.007
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.195
GPT teacher head0.382
Teacher spread0.187 · 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 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

Citations3
Published2007
Admission routes1
Has abstractyes

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