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Record W4417477035 · doi:10.1017/9781009608282

Justice for Some

2025· book· en· W4417477035 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCambridge University Press eBooks · 2025
Typebook
Languageen
FieldSocial Sciences
TopicJury Decision Making Processes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInnocencePresumption of innocenceCriminal justiceAppealAdversarial systemPrejudice (legal term)Economic Justice

Abstract

fetched live from OpenAlex

This book defines the differing concepts of miscarriages of justice, wrongful convictions and innocence in relation to the presumption of innocence and the rationing of justice. It compares inquisitorial systems, with examples from Europe, South America and Asia to adversarial systems. It contrasts England's focus on the miscarriage of justice and the remedial institutions of the Court of Appeal and the Criminal Cases Review Commission, with the United States and China's narrower focus on proven factual innocence It highlights new laws enacted in India in 2023 that increase the risk of wrongful convictions, and details how the International Criminal Court has taken steps to reduce the risk of false guilty pleas that may have been accepted by previous international criminal courts. The book examines the roles of racist prejudice and gender stereotypes in wrongful convictions. It also examines false guilty pleas such as those in the Post Office scandal, as well as wrongful convictions for crimes that did not happen. This title is also available as open access on Cambridge Core.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.309
Teacher spread0.251 · 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