Poverty Policy: Historic Institutional Approaches to Poor Relief in Canada
Bibliographic record
Abstract
In Canada, social assistance programs act as a ‘safety net’ to prevent those living in poverty from reaching destitution. However, this safety net comes with expectations – in the form of welfare-to-work programs that mandate beneficiaries’ participation in work-related activities. Underlying these welfare-to-work programs are ideas surrounding citizenship, activation, dependency, and the role of the state in supporting the welfare of its citizens. Embedded in these programs are the ideas of market citizenship and activation, two ideas that tell the story of the ideal citizen in Canada: a self-sufficient and appropriately activated market citizen, who fulfils their obligation of supporting themselves through participation in paid employment. Subsequently, through the ideas of market citizenship and activation, social assistance beneficiaries represent the antagonist to the ideal citizen: an unmotivated, dependent, support-needing citizen. Although scholars often situate the emergence of the ideas of market citizenship and activation during the late 20th century period of welfare reform in Canada, this perspective negates the history of these ideas in social assistance policies. Informed by the theory of Critical Human Ecology and the methodology of Ideational Analysis, this thesis explores the development of the ideas of market citizenship and activation across institutional approaches to poor relief in Canada. By taking a long-term historical perspective, this thesis finds evidence of the ideas of market citizenship and activation as early as the 17th century in Canadian institutional approaches to poor relief, and counters the prevailing perspective that market citizenship and activation emerged in the late 20th century in Canadian institutional approaches to poor relief.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.051 | 0.036 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".