ERIC ED499856: Global Higher Education Rankings: Affordability and Accessibility in Comparative Perspective, 2005
Bibliographic record
Abstract
Over the past few decades, higher education has become available around the world to a degree unimaginable to earlier generations. In many ways, accessible mass higher education is the foundation of the modern knowledge economy, and without it, the bright futures of many youth around the world would be dimmed. Preserving and enhancing the accessibility of higher education is an issue that confronts governments and stakeholders all over the world. This inaugural edition of the Global Higher Education Rankings is the first systematic and rigorous exploration of the affordability and accessibility of higher education within an international comparative context. The report is effectively divided into four parts following an introduction: methodology, affordability rankings, accessibility rankings, and conclusions. The end of the report also includes individual country reports which profile national results, and two appendices relating to data and indicator scores. The affordability section of this report looks at the complete and high quality data on affordability of higher education in fifteen countries: Australia, Austria, Belgium, Canada, Finland, France, Germany, Ireland, Italy, Japan, The Netherlands, New Zealand, Sweden, the United Kingdom and the United States. The accessibility section of the report looks at the relevant, complete data on accessibility of higher education in thirteen countries: Australia, Austria, Belgium, Canada, Finland, France, Germany, Ireland, Italy, The Netherlands, Sweden, the United Kingdom and the United States. Given the difference in national focus and priorities regarding higher education accessibility, data on accessibility is far less open to international comparison than is data on affordability. While there is some clustering, the data and rankings suggest quite strongly that the links between accessibility and affordability are not straightforward. For instance, with the exceptions of Finland and the Netherlands, no country hasconsistently high scores across both the affordability and accessibility rankings. Data Sources and Indicator Scoring/Weightings Sensitivity are appended. (Contains 7 figures and 29 tables.) [This document was published by the Educational Policy Institute. Abstract modified to meet ERIC guidelines.]
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.271 | 0.122 |
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".