Допрос по «Тактике Рейда» в американском уголовном судопроизводстве: законность, целесообразность, эффективность
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".