Bibliographic record
Abstract
Violent and property crime rates in all Western countries have been falling since the early and mid-1990s, after rising in the 1970s and 1980s. Few people have noticed the common patterns, and fewer have attempted to understand or explain them. Yet the implications are essential for thinking about crime control and criminal justice policy more broadly. Crime rates in Canada and the United States, for example, have moved in parallel for forty years, but Canada has neither increased its imprisonment rate nor adopted harsher criminal justice policies. The implication is that something other than mass imprisonment, zero-tolerance policing, and three-strikes laws explains why crime rates in our time are falling. The essays in this volume of Crime and Justice explore the possibilities cross-nationally. They document the common rises and falls in crime and look at possible explanations, including changes in sensitivity to violence generally and intimate violence in particular, macro-level changes in self-control, and structural and economic developments in modern states. The contributors to this volume include Marcelo Aebi, Eric Baumer, Manuel Eisner, Graham Farrell, Janne Kivivuori, Tapio Lappi-Seppala, Suzy McElrath, Daniel S. Nagin, Richard Rosenfeld, Rossella Selmini, Nico Trajtenberg, and Kevin T. Wolff.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".