The construction of at-risk youth: a qualitative study of community-based youth-serving agencies
Bibliographic record
Abstract
This thesis explores the ways in which the ‘at-risk’ designation of marginalized and disadvantaged youth within youth-serving agencies contributes to a program of governance within a neoliberalized welfare state. I argue that while there is considerable resistance to the risk designation within youth-serving agencies, officially accepting funding for programming designed to target at-risk youth continues to individualize the troubles youth face and responsibilizes youth to become their own risk managers. Through these structural funding constraints, youth-serving agency staff inadvertently disseminates expert knowledges that validate the notion of ‘at-risk’ youth as a growing problem while legitimating the perspective that social problems can and should be addressed through individual treatment rather than social policy. This both disciplines youth to become better liberal subjects while leaving structural constraints unaddressed. I conclude with some examples of resistance that show promise of working outside of these technologies of governance.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.019 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".