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
In Australia, New Zealand, the United States of America and the United Kingdom you can sue a negligent doctor, but not a negligent detective. You can sue both doctors and detectives in Canada and South Africa. Why the difference? Would making detectives liable for negligent police investigations improve their decision making or, as many judges assert, increase risk aversion and divert significant resources from tackling crime? This article explains the civil law of negligence but criticises its judicial application in cases of alleged negligent investigation. It argues that the current position is no longer sustainable. As increasingly recognised by senior judges, legislative intervention is inevitable and overdue. Police forces should not be opposing change but preparing to manage the consequences by seizing the opportunities available to ensure that a learning paradigm is embedded within a new scheme which limits costs and prevents many of the problems which the judges, albeit exaggeratedly, predict.
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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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