A comparison of socioeconomic status and mental health among inner-city Aboriginal and non-Aboriginal women
Bibliographic record
Abstract
Aboriginal women in urban areas have been reported to experience high rates of poverty, homelessness, interpersonal violence, and health problems. However, there are few prior ethnocultural comparisons of urban women from similar socioeconomic backgrounds. The current study explored the mental and physical health of Aboriginal and non-Aboriginal women accessing social services agencies and shelters. Half of the sample (n=172) was Aboriginal (48.3%). The lifetime rate of physical abuse was significantly higher in Aboriginal women, and they were more likely to have been victims of violence or crime in the past year (A=50.6%, NA=35.6%, p<0.05). Rates of teenage pregnancy (<18 years of age) were significantly higher among Aboriginals (A=51.3%, NA=30.6%, p<0.05) and they reported more parental drug/alcohol problems (A=79.2%, NA=56.5%, p<0.05). Aboriginal women were also more likely to have previously received treatment for a drug or alcohol problem. There were no differences in self-reported physical health, medication use, hospitalisations, and current substance misuse. Irrespective of ethnicity, lifetime rates of anxiety, depression and suicide attempts were extremely high. Future research should explore the effects of individual resources (e.g. social support, family relations) and cultural beliefs on women's ability to cope with the stress of living with adverse events, particularly among low SES women with children.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".