Educational Programs and the Ontario Disability Support Program: A Critical Literature Review
Bibliographic record
Abstract
My major research paper (MRP) is a critical literature review of educational programming available to Ontario Disability Support Program (ODSP) recipients. Specifically, I review financial literacy education (FLE) programs and ODSP employment training programs. The purpose of my research was to gain a critical understanding of how these programs incorporate learners’ experiences with governmental institutions that impact financial wellbeing and employment. I analyze the literature through the lens of two critical theories: critical pedagogy and critical disability theory. Previous literature indicates that involvement with the social assistance system in Ontario influences recipients’ sense of identity related to disability (Crooks et al., 2008; Lightman et al., 2009). The impact on recipients’ identity is influenced by the binary categorization of able/disabled within social assistance institutions. Some ODSP recipients identify as neither able-bodied nor disabled, rather on a spectrum of illness and wellness. Research into these types of educational programming can support educators and policymakers in identifying the barriers ODSP recipients encounter while pursuing personal goals related to financial security and employment. In this MRP, I report on findings that indicate the presence and the usefulness of critical pedagogy and critical disability theory to improve FLE and employment training delivery. Through this research, I aim to understand the gaps in current FLE and employment training delivery and offer recommendations for future program development.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".