Adult Education and Training Survey, 1998 [Canada]: Courses
Bibliographic record
Abstract
The 1998 Adult Education and Training Survey is the sixth in a series of similar surveys designed to measure adult participation in education and 1training. Statistics Canada conducted the Adult Education Survey (AES) in 1984 on behalf of the Department of the Secretary of State and the Adult Training Survey (ATS) in 1986, on behalf of Employment and Immigration Canada. In the late 1980s, as the number of adult Canadians pursuing education and training programs increased, there was a renewed interest in education and retraining as economic development issues. These concerns resulted in Employment and Immigration Canada commissioning Statistics Canada to conduct the Adult Education and Training Survey (AETS) in November 1990, and again in 1992. The main objective of all four surveys was to measure participation rates.In general, each successive questionnaire evolved into a more detailed and comprehensive survey instrument, with greater emphasis on profiling the role of the employer and identifying barriers to training. In 1994, the AETS was modified to explore areas such as access to training. The 1998 Adult Education and Training Survey (AETS) is comparable to the 1994 survey. A few new questions on motivations and expectations have been added. And, for the first time, the survey was conducted using computer-assisted interviewing. As in 1994, Statistics Canada conducted the survey on behalf of Human Resources Development Canada.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.023 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.015 |
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".