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Record W2416967491

Допрос по «Тактике Рейда» в американском уголовном судопроизводстве: законность, целесообразность, эффективность

2015· article· ru· W2416967491 on OpenAlexaboutno aff
Н А Андроник, Т С Пачина

Bibliographic record

VenueЮридическая наука и правоохранительная практика · 2015
Typearticle
Languageru
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsnot available
Fundersnot available
KeywordsConfession (law)InterrogationSuspectConvictionHarmPsychologyStatement (logic)DeceptionLawInnocenceSocial psychologyPolitical scienceCriminology
DOInot available

Abstract

fetched live from OpenAlex

The Reid technique widely used by the US law enforcement agencies during conducting interrogation by the resistance of interrogated person is considered. The significant defects of this technique including eliminating the aim of the proceedings itself are revealed. The essence and purpose of the technique is confession of guilt by the accused obtained through nine steps: direct confrontation; rejection; superiority; transformation of denials into confirmation; displaying empathy; elaboration of various scenarios; statement of alternative questions; repetition; written fixation. The efficiency of this technique is conditioned by applying psychological manipulations and recognition of sign language, that gives rise to criticism: interrogation causes false confession, especially among minors (therefore the technique is prohibited in some European countries). In 2012 the Reid technique is recognized by the Ontario court's decision as confrontational, psychologically manipulating and especially dangerous when applying unduly or unfairly. The results of journalistic inquiry on the obtaining false confession of the accused Nga Troung (Massachusetts) when using this technique are provided. It's summarized that this technique is efficient if the person committed a crime confesses; in the cases of self-incrimination it tends to deception, conviction of innocent person; misidentifying a person liable to be put on trial. So, this method should be applied carefully using only such elements which cannot harm the investigation and make it impossible to elicit the truth in the case.

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)0.002
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0300.014

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 head0.160
GPT teacher head0.379
Teacher spread0.219 · 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
Published2015
Admission routes1
Has abstractyes

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Same venueЮридическая наука и правоохранительная практикаSame topicTorture, Ethics, and LawFrench-language works237,207