EMPOWERMENT OF OLDER IMMIGRANT WOMEN THROUGH IMPROVED FINANCIAL LITERACY
Bibliographic record
Abstract
A lack of financial literacy has far-reaching implications for economic security in old age for women as it may diminish women’s ability to plan effectively for later life and/or retirement. To understand and address these issues the National Initiative for the Care of the Elderly (NICE) led a research study to improve the financial literacy of low-income, older, unattached, and immigrant women in the Vancouver (N=201), Montréal (N= 65) and Toronto (N=204). Evidence-based financial literacy tools and workshops on topics related to money management, financial planning, and government assistance programs were developed and delivered. Survey data was collected at baseline prior to workshop and at three-months post-workshop, once a financial action-plan was implemented. Participants reported satisfaction with the workshops and information on: 1) budgeting, 2) estate planning, and 3) recognizing financial abuse. Participants indicated that resources being aligned with the socio-economic conditions of the participants was important. A gendered/feminist lens applied to the findings indicates that older women may have less opportunity to become financial literate if prescribed marriage roles and family dynamics lead to male spouses taking on the money management roles in earlier to late-life. A lifecourse approach is necessary to support financial literacy for women earlier in life and continued programs providing relevant financial information at predictable life transitions in later-life such as widowhood. Despite baseline differences, participants who completed the workshops felt they had enhanced their knowledge and were able to identify how they may be more responsive with money matters in the future.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".