Sorting the poor: A study of the management of the homeless in mid-sized Canadian city shelters
Bibliographic record
Abstract
The ability to access social services when in need is a fundamental component of the social safety net available to Canadians. When approaching such services, consideration is seldom given to the subtle forms of governance that accompany the administration of aid. This thesis questions: Through what means are shelter seeking persons categorized beyond the division between the 'deserving' and 'undeserving' poor and how is their treatment moralized, categorized, and legitimized within the shelter system? This study uncovers the inherent complexities in sorting, categorizing, and assisting the homeless beyond the traditional dichotomy of the deserving and undeserving poor. This thesis argues that moral regulation is occurring within contemporary social services, and homeless shelters provide an ideal site from which to observe moral regulation and its transition into the 21st Century. By studying moral regulation of the homeless, it is evident that previous studies have overlooked the roles of surveillance and external institutions in the regulation process, and their role in measuring resident's progress and the overall (re)construction of residents as liberal subjects. Using a moral regulation approach, the importance of considering social services staff as moralizing agents is uncovered.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.031 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".