Income Assistance Receipt among Off-reserve Indigenous Peoples in Canada
Bibliographic record
Abstract
This study demonstrated income assistance (IA) receipt among Aboriginal people living off-reserve using data from the 2012 Aboriginal Peoples Survey (APS), a national survey of First Nations people living off reserve, Métis, and Inuit. In 2011, 12% of Aboriginal people living off-reserve received IA. It focused on socio-demographic, labour market and health characteristics found in different types of IA receipt. For almost half of the Aboriginal IA receivers, IA was their only source of income; it was the main (but not sole) source of income for 27%; and for the remaining 28%, IA was a secondary source of income. The receipt of IA was associated with socio-demographic characteristics such as never having been married; female; younger; less than high school levels of education; and living in lone-parent households. About 20% of IA recipients were employed in 2011. Compared with other Aboriginal workers not receiving IA, they were more likely to have a job with short tenure; to be part-time workers or temporary workers; and to work in the sector of sales and services. Compared to non-recipients, recipients of IA also reported significantly poorer mental and physical health conditions. The associations between health status and IA remained significant after controlling for other demographic factors. These results have important implications for policy makers and other stakeholders interested in IA for Aboriginal people. The complexity of employment, health, and other risk factors of IA need to be considered in further understanding these issues.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".