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Record W2206683831 · doi:10.1002/9781118769133.ch13

Vulnerable Individuals, Intermediaries and Justice

2015· other· en· W2206683831 on OpenAlexaffabout
Brendan M. O’Mahony, Ruth Marchant, Lorna Fadden

Bibliographic record

Venuenot available
Typeother
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIntermediarySuspectContext (archaeology)CriminologyPerspective (graphical)Economic JusticeCriminal justiceValue (mathematics)Identity (music)Political scienceSociologyLawPsychologySocial psychologyPublic relationsBusinessGeography

Abstract

fetched live from OpenAlex

Witnesses can be vulnerable during questioning in the justice context for a number of reasons, including psychological, developmental, environmental and cultural issues. This chapter explores different interpretations from an international perspective of how intermediaries can be used to facilitate communication with vulnerable witnesses. Using a case study approach, it examines the use of intermediaries in England and Wales with child witnesses, from the initial communication assessment prior to a police interview, through to oral testimony at court. It then examines how complex language is often used during police suspect interviews and during cross-examination in the criminal courts. The usefulness of intermediaries for vulnerable defendants is examined and the ways in which intermediaries understand their professional identity when working with defendants is explored. Finally, the issues that can result in miscommunication in a cross-cultural context are examined using examples from Australia and Canada and the value of intermediaries in this context is explored.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.087
GPT teacher head0.462
Teacher spread0.375 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2015
Admission routes2
Has abstractyes

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