Bibliographic record
Abstract
Taking Control is a critical ethnography of the Native Education Centre in Vancouver, British Columbia. It presents an intimate view of the centre, focusing on the ways that people who work there – First Nations students, board members, teachers, and non-Native teachers – talk about and put into practice their beliefs about First Nations control. As Michael Apple comments in the preface, their stories “provide concrete evidence of what can be accomplished when the complicated politics of education is taken seriously.” The study is based primarily on fieldwork conducted in the centre during the 1988-9 school year. At that time, over 400 adult students were enrolled in eleven programs ranging from basic literacy and upgrading to “skills training” including Native Public Administration, Family Violence Counselling, and Criminal Justice Studies. Selected words of the people interviewed figure prominently in the descriptions of everyday life in the centre. The author contextualizes people’s notions of taking control, first within the space where they work, a building specially created using cedar planks, glass, and hand-carved poles, and second in relation to the efforts by aboriginal people to control their formal education in British Columbia. The book also contains a brief history of the centre itself. The work engages theoretically with Foucault’s notion of power as a relation, juxtaposing it with the National Indian Brotherhood document Indian Control of Indian Education (1972). Views of the programs of study are a central focus of Taking Control , which also includes a self-reflexive analysis of the non-Native researcher’s position in a study of First Nations control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.006 |
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".