Tertiary Education for the Knowledge Society
Bibliographic record
Abstract
This book provides a thorough international investigation of tertiary education policy across its many facets – governance, funding, quality assurance, equity, research and innovation, academic career, links to the labour market and internationalisation. It presents an analysis of the trends and developments in tertiary education; a synthesis of research-based evidence on the impact of tertiary-education policies; innovative and successful policies and practices that countries have implemented; and tertiary-education policy options. The report draws on the results of a major OECD review of tertiary education policy – the OECD Thematic Review of Tertiary Education -- conducted over the 2004-08 period in collaboration with 24 countries around the world. "The new ‘bible’ of Post-secondary education." -Paul Cappon, President of the Canadian Council on Learning "An exceptionally useful and interesting review." -Tom Boland, Chief Executive, Higher Education Authority of Ireland "The reference text for the future debate on tertiary education." -José Joaquín Brunner, Professor and Director, Centre for Comparative Education Policies, University of Diego Portales, Chile
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.096 | 0.049 |
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".