A brief comparison of forensic psychology in South Africa, the United States, and Canada
Bibliographic record
Abstract
Considering forensic psychology’s varying stages of development across the world, this work briefly explores historical developments, the field of practice, training, licensing, legislation, and associated challenges in South Africa, the United States, and Canada. While there are numerous similarities, a few differences are evident. Among the common areas of practice, psychologists are involved in assessments to determine fitness (competency) to stand trial, criminal responsibility in adults, as well as assisting courts in making determinations on criminal responsibility in the case of children in conflict with the law. In South Africa, psychological assessments of sexual violence complainants with intellectual disability are also required by courts. Psychological intervention, research, and policy development work are also conducted in the three countries. Challenges appear in the intersection between psychology and the law, expectations of psychologists, and the inclusion of psychologists in evaluation panels in South Africa and Canada. It is clear that psychologists are playing an active role in the professional development of the field, research, and coordinating with legislative authorities in advancing forensic mental health and advocating for people with mental health problems. However, across the three countries, there is a need for continued focus on the broader issues of diversity, equity, and inclusion with respect to the forensic populations being served, and there has to be a concerted effort to address the psychosocial needs of marginalized communities.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".