Fear and Distrust Within the Canadian Welfare System: Experiences of People With Mental Illness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While experiences of fear and distrust have been documented as a part of recipients’ interactions with disability benefits, there have been few attempts to explore how they are shaped by system features and their impact on employment pursuits. The purpose of this article is to unpack how fear and distrust emerge among people with mental illness who have recently entered the welfare system. Using an interpretative qualitative approach, the authors draw on the findings from 69 in-depth interviews with key stakeholders about their experiences with employment. Stakeholders included recipients, welfare program and policy staff, and service providers in the community. Data were analyzed by exploring similarities and differences across perspectives and contexts. The findings highlight how system features shape and perpetuate fear and distrust through poorly communicating information about the system, a chaotic state of constant change and complexity, a lack of attention to building trusting relationships between caseworkers and recipients, ongoing system errors, and excessive reporting requirements. The impact of the current state of affairs is significantly harmful to recipients, especially those living with mental illness. Our findings also highlight a possible way forward by building trusting relationships and finding ways to improve communication channels.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it