Implementation of the Canadian Language Benchmarks in Manitoba: 1996 to the present.
Bibliographic record
Abstract
At the 1996 national TESL Canada Conference in Winnipeg, Manitoba, the Canadian Government launched the Canadian Language Benchmarks: English as a second language for adults: A working document as its national language proficiency standards. In 2000, following a comprehensive review, the Canadian Language Benchmarks (CLB) were revised and released as the Canadian Language Benchmarks 2000: English as a second language for adults (Pawlikowska-Smith 2000). The development of the CLB took a number of years and involved extensive consultation across the country and abroad. The approach taken in the Australian Certificates in Spoken and Written English (NSW AMES 1992) was particularly informative in the CLB development, and there are some significant similarities between the CLB and its Australian counterpart. The CLB describes language functionally through 12 levels of proficiency organised into three stages. It is learner-centred and competencybased, stresses community, academic and work contexts, and assessment is intended to be task-based. This article describes the Manitoba immigration context, the adult English as an Additional Language (EAL) programming context, the approach taken in implementing the CLB in Manitoba since 1996 and future directions. the Manitoba context Manitoba is often referred to as the keystone province because of its shape and location in the centre of Canada. Although the province has a large landmass, only 3.6% of Canada’s population resides there, mainly clustered along its southern border. Its capital is Winnipeg, a city of about 700 000, with several other much smaller cities and towns dotting the landscape. Manitoba is a major transportation hub and a prairie province, with an economy based principally on manufacturing, mining, agriculture and forestry. Like Australia, Canada is a country of First Nations people and immigrants, and Manitoba has always had a strong commitment to receiving
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".