Alcoholism, Native and non-Native treatment technologies and the discourse of difference.
Bibliographic record
Abstract
This thesis explores the establishment of government-sponsored alcohol treatment facilities for Native people in Canada. An examination of treatment approaches suggests that Native recovery programs are a reflection of other existing treatment technologies. The development of government-sponsored programs represents negotiated territory between "self-determination" and the government's effort to re-define citizenship. The following sources of information were included in this project; face-to-face interviews with staff members from different treatment facilities, a review of websites outlining the treatment programs in Native facilities, an analysis of documents on Alcoholics Anonymous and a review of literature that outlines Aboriginality and "governable spaces." Seven interviews were conducted between the November 2000 and July 2001. The results suggest that the government-sponsored recovery facilities are not particularly different from most non-Native treatment centres. The conclusion is reached that applying the A.A. model, despite its emphasis on sameness, allows room for the incorporation of difference into Native recovery programs. Native facilities recognition of distinctiveness permits treatment to be applied in a less inclusive way.Dept. of Sociology and Anthropology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .H465. Source: Masters Abstracts International, Volume: 40-06, page: 1436. Adviser: M. Hedley. Thesis (M.A.)--University of Windsor (Canada), 2002.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.040 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".