Overview of Benefits of First Nations Language Immersion
Bibliographic record
Abstract
In the wake of the Truth and Reconciliation Commission of Canada report into the ‘cultural genocide’ perpetrated by the State of Canada against First Nations, Métis and Inuit peoples, through the widespread use of Residential Schools, the federal government offered an apology and an apparent opportunity for reconciliation[i]. Part of this programme was new legislation that would govern the relationship between First Nations and the federal government over First Nations education. Entitled the First Nations Control of First Nations’ Education (FNCFNE), the proposed bill promised a new deal and an apparent chance to renew a tarnished relationship. Yet in spite of its name, the bill offered very little in terms of progress. Indeed if it had been implemented, in many cases, the bill would have done little to increase First Nations’ control over the education of First Nations’ children and likely would have made effective language education extremely difficult. Indeed, this article’s analysis of the bill shows that, at its core, the law represents little more than the reinforcing of existing settler-colonial power dynamics. In particular, while it would have shifted virtually the totality of administrative responsibility for on-reserve education to First Nations it would have reserved ultimate power – manifest through control over funding – to Ottawa. As a result the FNCFNE would have represented a profound step in undermining First Nations language rights and language education in Canada. [i] “Prime Minister Stephen Harper's statement of apology”, CBC News, 11 June 2008
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.065 | 0.004 |
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".