Bibliographic record
Abstract
This report provides observations and lessons learned by a study-visit team from the Centre for Curriculum, Transfer and Technology (Canada) and the British Columbian Council on Admissions and Transfer. The study-visit was a reconnaissance of the reform of the post-school education and training system in the United Kingdom (UK), chiefly in England and Scotland. The team had two general study objectives: (1) determine the form and extent to which the learning outcomes approach is central to teaching and learning in the system of colleges and universities in England and Wales; and (2) determine the extent to which their credit transfer arrangements exist within and between colleges and universities, and learning outcomes form the basis of the assessment for establishing course equivalencies for transfer. The UK education and training system is undergoing profound changes as it moves from a historical elitist model to that of more democratic mass education system. Some of inter-related themes that have been investigated in the UK, which are relevant to issues in British Columbia include the following: provision of core/key skills for employability, citizenship, and personal development; assessment modes for outcomes-based learning; quality assurance policies and procedures; assisting college teachers to learn new instructional roles; and widening access, especially for those who were socially excluded. Appendices include "Glossary, " "Study-Visit Itinerary and Key Informants, " "Improving Student Learning"Outcomes, " "An historic
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.405 | 0.239 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".