FINANCIAL LITERACY AND THE ECONOMIC EXPERIENCES OF OLDER ABORIGINAL ADULTS IN CANADA
Bibliographic record
Abstract
Lifelong socio-economic development disparity between Indigenous Peoples and the general population across Australia, New Zealand, the United States, and Canada is a significant risk factor for marginalization in later years (Brascoupé, Weatherdon, & Tremblay, 2013). A scoping review on international financial literacy programs conducted prior to this study indicated the need to address financial knowledge gaps in Indigenous populations, specifically focusing on financial literacy across the lifespan. The findings of this review informed this mixed methods research study, drawing on results from a consensus meeting (n=15), survey (n= 50), and focus group data (n=25) to better understand the financial realities of Canadian elderly Aboriginals who live on and off reserves. The results of the study indicate that the financial capabilities of older Aboriginals are not well understood and that tailored money management initiatives must consider the needs of Aboriginal older adults with lower income. Strategies to improve financial literacy are also complicated by the implications of status, tax-exemptions, gendered income disparities, and band laws. The knowledge gained from this study led to the development of financial literacy resources that address the following issues: navigating financial resources and benefits, saving and education for grandchildren, legal and tax issues, and band issues. The findings from this study are applicable beyond a Canadian context to demonstrate the complexity of financial issues faced by the growing elderly Indigenous communities, and the need for diverse international financial literacy programs to include cultural elements of knowledge translation, cultural relevancy and cultural safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".