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Record W7132935255

Exploring non-compliance: the United States, international law and torture

2006· dissertation· W7132935255 on OpenAlexafffund
Henry Mark Lovat

Bibliographic record

VenueTSpace · 2006
Typedissertation
Language
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsUniversity of TorontoLibrary and Archives Canada
FundersUniversity of Toronto
KeywordsTortureInternational lawBureaucracyPoliticsInternational relationsWork (physics)Terrorism
DOInot available

Abstract

fetched live from OpenAlex

Using theoretical insights from International Law and International Relations, this paper examines US policies in the early post 9/11 period with respect to the treatment of detainees captured in Iraq, Afghanistan and elsewhere. The paper concludes that while these policies seem to have been driven primarily by political considerations of national security, international legal rules pertaining to the treatment of detainees were also marginalised in key policy debates partly because of the insufficient or uneven internalisation of these rules in domestic political and bureaucratic circles. Focusing on the theoretical work of Harold Koh, this paper suggests that to better understand how international law works in practice it would be useful to expand Koh's analysis of the processes of internalisation to allow for disparities in the evenness with which international legal rules might be internalised within domestic bureaucracies, and for the variable relationship between political and bureaucratic internalisation.

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)0.007
metaresearch head score (Gemma)0.009
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0060.019
Scholarly communication0.0080.010
Open science0.0010.006
Research integrity0.0030.005
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 head0.129
GPT teacher head0.394
Teacher spread0.265 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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