119 Health status and crime of indigenous people in North America, Australia and New Zealand in the context of transmission of transgenerational trauma
Bibliographic record
Abstract
Abstract EP3.2, e-Poster Terminal 3, September 3, 2025, 13:05 - 14:00 Aims Indigenous communities can be defined as groups of those who have experienced exclusion and have survived modernization and imperialism. However, it seems most reasonable to consider the health and criminological situation of these communities through the lens of colonization. Colonization processes led to the destruction of Indigenous cultures and, consequently, to the weakening or complete destruction of the cultural identity of representatives of Indigenous communities. And the destruction of Indigenous cultures is closely related to the victimization and predisposition to crime of colonized people. It also seems to determine their health status. When examining the situation of these communities within a colonial context, it is important to consider the transmission of transgenerational trauma. So, the aim of the paper is to examine relationships between historical trauma experienced by Indigenous people and its current consequences in the areas of health and crime. Methods Literature review. Results The health status of Indigenous communities is significantly worse than that of the majority population. In the USA, for example, this applies to aspects such as alcoholic liver disease, overdose mortality, suicide, which are all conceptualized as components of deaths of despair. A growing body of literature has revealed consistent associations between parents’ participation in Indian Residential Schools and various forms of psychological distress, depression, anxiety symptoms, and post-traumatic stress disorder (PTSD) in their offspring. Meanwhile, in Canada, Australia and New Zealand, indigenous people are overrepresented in the criminal justice system. Conclusion The relationships between the transgenerational trauma and its contemporary effects on health and crime in Indigenous communities seems moderately evident. Historical trauma can be diverse in nature; for example, it may stem from witnessing a community massacre or the prohibition imposed on whaling among the northwestern coast communities of North America. Cultural factors play an important role in the treatment process.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".