Bibliographic record
Abstract
Chapter 6 will explore paths to moving forward with police interrogation reform in the United States, parting from the lessons of other countries that have undertaken reform, such as the United Kingdom, Australia, Norway, and Canada, while focusing on three key areas: 1) police interrogation techniques, 2) the interview of vulnerable populations, and 3) changes in case law related to the reading of rights, invocation of rights, the use of trickery and deception, as well as the use of confessions to build and prosecute a criminal case. The goal of the chapter is to consider ways in which the issues presented in this book can be revisited to change the current state of police interrogation in the United States. This will require changes across the board: legislative, legal, police interviewing training, and also an acknowledgment of the role of cognitive, cultural, and sociolinguistic factors in police-suspect discursive interactions. A change of perspective on the presence of counsel in the interview room is also explored, looking at other jurisdictions outside of the United States which provide access to counsel to custodial suspects.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".