Bibliographic record
Abstract
The terms 'adult education', 'continuing education' and 'distance education' were used synonymously by Canadian universities in the creation of departments and courses over the years to promote literacy and the working skills of the adult population. Women, 25 years old and over, aboriginals, minorities and disabled adults benefited from distance education courses. In addition to universities and colleges, churches, school boards, non-governmental organisations, businesses and women's groups played important roles in adult education over the last 25 years. Teaching methods like portfolio development, holistic approaches, group sessions and identification of cultural groups helped in transmitting adult literacy courses effectively in Canada. The importance of the role of human capital was recognised by countries on the basis of the USA experience since the Second World War. Budget deficits, the information technology revolution and globalisation prompted universities to make partnership agreements with businesses and to promote accessibility and equity in higher education. Text, audio, video and a combination of the three were used in Canada to promote economic growth, both in the advanced and less developed nations. Canadians and Canadian post-secondary institutions should volunteer their services to the Third World.
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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 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".