IDA Accessibility: Learning More About Whether Individual Development Accounts Can Work for Canada’s Poor
Bibliographic record
Abstract
Individual Development Accounts (IDAs) or matched saving accounts are programs designed to facilitate the building of capital and assets in low-income households. Based on the model of asset-based welfare policy, these programs propose to combat poverty through inclusion of the poor in asset building opportunities, which traditionally have been available to only middle and upper income households. Described as an anti-poverty strategy, Individual Development Accounts are growing in international popularity with asset-based policies already being included in Canadian income assistance programs. In order to better understand what some of the barriers might be to this anti-poverty program structure, this thesis employed qualitative methods of inquiry to explore peoples’ experiences with Learn$ave and why they didn’t or couldn’t participate in this national pilot project.\nThis thesis presents information that lends insight into the context and experience of Individual Development Accounts as part of today’s social policy framework. Critically examined through a social justice and empowerment lens, this research discusses the limitations to this market integration, human capital development approach to poverty reduction. The results of this study conclude that a lack of flexibility in the program structure and inadequacies in current Ontario social assistance systems were barriers to Learn$ave enrollment and continued participation. Based on these results, and an exploration of the literature this thesis argues that the neoliberal based values that influence Learn$ave’s structure present barriers to program inclusiveness. Grounded in this argument I conclude that Learn$ave does not adequately acknowledge nor address complex socio-political layers of poverty and systemic oppression and as a result does not reach the status of an effective anti-poverty strategy. Recommendations suggest that if Individual Development Accounts are going to be implemented more broadly they need to offer more opportunity for participant self-determination and must work in collaboration with income support systems to ensure that a comprehensive and supportive antipoverty strategy is developed.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".