Bibliographic record
Abstract
The Official Language Act plays a key role in the lives of Canadians. Its purpose is to ensure respect for English and French as the official languages of Canada in governmental and parliamentary institutions, support the development and vitality of official language minority communities, set out powers, duties and functions of federal institutions with respect to the official languages of Canada. The Government of Canada has decided to modernize the Act to ensure that it continues to serve Canadians in a changing environment. That is why the Government of Canada showed its commitment to promote, protect and update a law by sharing its vision for official languages reform in February, titled French and English: Towards a substantive equality of official languages in Canada. After 30 years since the last major update, a modernization of the Official Languages Act is necessary to allow the law to keep pace with the social, demographic and technological realities in today’s society, which did not exist during the last revision in 1988. The bill recognizes the diversity of provincial and territorial language regimes and focuses on learning opportunities of the first language in minority settings and on learning opportunities of a second official language in a majority situation to improve the rate of bilingualism among Canadians. The bill also seeks to protect institutions of official language minority communities both for the English-speaking minority in Quebec and for the French-speaking minority in the rest of the country, and proposes new ways to better protect French in Canada, including in Québec.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".