Bibliographic record
Abstract
Aboriginal people 6-7, 125, 134, 142 abuse against women 108-9, 129-30 by women 107 in childhood 28-9, 35-6, 108, 109, 145 incarceration trends 8 responsivity principle 129-30 accomplices 12-13 actuarial assessment 45-6, 50, 51, 52, 140 Historical Clinical Risk Scheme 78-9, 80 Level of Service/Case Management Inventory 74-8, 79-80, 140 need principle 83-4, 141 Psychopathy Checklist-Revised 59-74, 79-80 recommendations 81-2, 144-5 risk principle 55-6 Statistical Information on Recidivism 56-9, 79-80 adolescent offenders see girls advocacy brokerage 128 aggression family factors 89 gender differential 2-3, 13 overt 138 relational 3, 138 socialization theories 33 see also violent crime alcohol abuse 97-101, 122, 134 antisocial associates 92-4, 101 antisocial attitudes 94-7, 101 antisocial personality disorder (APD) 68-9, 71 anxiety 69, 124 assault 10, 13 assessment see actuarial assessment; criminogenic needs (dynamic risk factors), assessment; offender classification, assessment for; recidivism, assessment of risk for associates 92-4, 101 attachment 18, 19, 20, 90, 91 attitudes antisocial 94-7, 101 of staff 133, 134 behavioural genetics 27-8 behavioural interventions 116-17, 127-30, 136, 141 biological theories of offending 27-9, 139, 145 borderline personality disorder (BPD) 70, 71, 73, 124 California Psychological Inventory (CPI-So) 65, 66, 67 Canada, corrections service 133-4 CARE programme 136 caregivers, incarceration 8 child abuse by women 107 survivors 28-9, 35-6, 108, 109, 145 childcare 122 child-killings 9-10 child-rearing practices criminogenic needs and 89-91 socialization 32-3, 34 see also developmental (life-course) theories of offending The Assessment and Treatment of Adult Female Offenders
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.869 | 0.792 |
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".