A survey of police eyewitness identification procedures
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.
Bibliographic record
Abstract
Canadian (N = 117) and U.S. officers (N = 167) completed an online survey regarding their eyewitness identification procedures.Chapter 2 compared current procedures with each country's respective policy recommendations.In some cases, policy recommendations were the same.In other cases they were different.Hypotheses were that where recommendations were the same, no between-country differences would be observed, and that where recommendations were different, between-country differences would be observed in line with recommended procedures.Partial support for these hypotheses was found indicating that policies had some impact on procedures.Chapters 3 and 4 examined lineup construction and administration practices (respectively).Some reported practices are of concern since research demonstrates they may reduce witness accuracy, though caution is necessary in interpreting why certain practices may or may not be used as there are many possible reasons.One of the most marked findings across all chapters was the great variability found in procedure both within and between countries, demonstrating that 'typical' police procedures vary considerably.Major recommendations include policy mandates in order to achieve procedure consistent with best-practice recommendations, as well as provision of training materials in order to achieve such consistency.This survey provides a needed update in the literature regarding current police practices and offers a rich data source to help stimulate further research in the field.Rod: Thank you for being the kind of supervisor who prompted one student to say that I had "won the supervisor lottery" by getting to work with you.Your generosity with your time and knowledge, your patience, and your student-focused approach to supervision are appreciated beyond words and have had a profoundly positive impact on me as an academic and as a person.P.S.I agreed with the aforementioned student
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it