Bibliographic record
Abstract
This dissertation investigates the ways that pathologization, deficit model thinking, and negative school labels (i.e., learning disabled, at-risk, problem behaviour) are given institutional life within the relationships between students, staff, administrators, and policy makers at various levels of the alternative education hierarchy in British Columbia, Canada.A qualitative case study research design was selected to provide flexibility in data collection, and methods used include interviews, program observation, document collection, and focus groups.Data was analyzed using a three-tiered process of data reduction, data display, and conclusion drawing and verification.Findings consist of a series of paradoxes in relationships operating on multiple levels of the alternative education system: between students and staff at an alternative program, and within the language and labels used by professionals working in managerial/administrative positions at the high school, alternative program, local school board, and provincial ministry of education.Educational professionals in the province are seen to accept and resist processes of youth marginalization, such as deficit model thinking and pathologization, within the alternative education system.These contradictions, suggested by Ivan Illich to be inherent to large, modern social institutions, imply deeper ideological problems within the educational endeavour and the society at large.Implications for the educational institution, educators and administrators, students, and alternative programs are iv discussed in the final chapter, along with limitations and suggestions for future research.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.078 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".