Bibliographic record
Abstract
ADHD has long been recognised as disproportionately present in both juvenile and adult prison populations. This is so for a number of reasons, including the potential for persons with ADHD to be disinhibited, impulsive, impaired in executive functioning and chaotic in their lifestyle. A major challenge exists, though, to assist courts to understand better how ADHD may have played a role in criminal offending and thus to be relevant to evaluations of criminal culpability or even responsibility. Another issue that arises for expert assessment is how ADHD may make the experience of custodial detention especially burdensome and be relevant in this respect also for sentencing. This article considers the overall forensic context of ADHD in criminal litigation and reviews a selection of illustrative decisions from Canada, Australia, New Zealand and the United Kingdom to identify principles on the basis of which courts can make nuanced decisions that are suitably informed by expert mental health evidence about the forensic ramifications of ADHD.
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.
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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".