Building sustainable adult literacy provision: a review of international trends in adult literacy policy and programs
Bibliographic record
Abstract
Rosa McKenna and Lynne Fitzpatrick summarise an extensive study of adult literacy policies and practices in vocational education in six countries - Canada, New Zealand, United States, Ireland, United Kingdom and Australia. Australia, compared to the other countries studied, has a strong focus on the integration of literacy with vocational education and training standards and national qualifications, and a relatively advanced quality assurance system. To build further on literacy policy and practice, the authors suggest providing national leadership, expanding national research and referral programs, expanding flexible funding arrangements and continuing to develop diverse delivery modes, promoting consistent reporting and quality assurance, and building the capability of the existing teaching workforce.Rosa McKenna and Lynne Fitzpatrick summarise an extensive study of adult literacy policies and practices in vocational education in six countries - Canada, New Zealand, United States, Ireland, United Kingdom and Australia. Australia, compared to the other countries studied, has a strong focus on the integration of literacy with vocational education and training standards and national qualifications, and a relatively advanced quality assurance system. To build further on literacy policy and practice, the authors suggest providing national leadership, expanding national research and referral programs, expanding flexible funding arrangements and continuing to develop diverse delivery modes, promoting consistent reporting and quality assurance, and building the capability of the existing teaching workforce.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".