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
This innovative volume explores a fundamental issue in the field of sentencing: the factors which make a sentence more or less severe. All sentencing systems allow courts discretion to consider mitigating and aggravating factors, and many legislatures have placed a number of such factors on a statutory footing. Yet many questions remain regarding the theory and practice of mitigation and aggravation. Drawing on legal and sociological perspectives and examining mitigation and aggravation in various jurisdictions, the essays provide practical illustrations of specific factors as well as theoretical justifications. After the foreword by Andrew von Hirsch, a number of contributors address broad conceptual issues raised at sentencing. These contributions are followed by several empirical chapters including an exploration of personal mitigation in English courts. The authors are leading scholars from a range of common law jurisdictions including England and Wales, the United States, Canada, Australia, New Zealand and South Africa.
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.
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 | 0.001 | 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) | 0.000 | 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