Intellectual disability and Aboriginal people, an overview of current practise and process in institutionalization
Bibliographic record
Abstract
Currently in Manitoba, Aboriginal people with intellectual disabilities are more highly represented in institutional placements than they are in community based services. At a time when citizens with intellectual disabilities are demanding to be included as full participants in society, it appears that the institutional experience continues to be the norm for people who are Aboriginal. The purpose of this thesis is to determine the reason for this. Qualitative research was the method of inquiry used in this study. Interviews were conducted with people from federal and provincial governments, community service agencies, Aboriginal service agencies, advocacy groups, and perhaps most importantly, people with intellectual disabilities and their families. These participants identified several themes that help to explain why Aboriginal people with intellectual disabilities have been institutionalized. These themes include: a lack of services in reserve communities, a lack of clear legislation and policy about which branch of government is responsible, and consequently a lack of funding from which to draw. Issues such as poverty, racism, and a history of off-reserve service provision further compound the problems. Even in off-reserve communities Aboriginal people are not highly involved in community based services. In spite of the array of difficulties that exist participants also identified several reasons for optimism.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".