Psychosocial Determinants Associated with the Incarceration of First Nations Male Youth in Australia: A Systematic Literature Review
Bibliographic record
Abstract
First Nations young people are significantly overrepresented in the Australian youth justice system. Although First Nations youth form only 5.8% of the population, they account for over 60% of those in detention (AIHW, 2024) and are 27 times more likely than other Australian youth to be incarcerated. This disparity is attributed to psychosocial risk factors that stem from deep rooted systemic and structural discrimination. To date, no systematic review has synthesised the evidence on psychosocial determinants contributing to youth detention among First Nations male youth in Australia. These factors include exposure to adverse childhood experiences, mental ill-health, maladaptive coping mechanisms, and underdeveloped psychosocial skills. Such psychosocial vulnerabilities are often shaped and intensified by broader social, cultural, and historical disadvantage. This systematic literature review aims to synthesise existing empirical evidence on the psychosocial determinants associated with incarceration among First Nations male youth in Australia. By clarifying what is currently known about these factors, this systematic literature review contributes to a better understanding of how psychosocial vulnerability intersects with systemic disadvantage. This knowledge is essential for developing culturally appropriate prevention strategies, improving mental health responses, and informing more effective and just policy for First Nations young people in contact with the youth justice system.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".