Introduction to the Special Issue: ‘The public good of higher education: A comparative study’
Bibliographic record
Abstract
Abstract The Special Issue provides the first consolidated outcomes from a large cross-country research project, conducted by the UK-based Centre for Global Higher Education, on the contributions of higher education to public good outcomes. The public good outcomes of higher education are outcomes other than private pecuniary benefits like individual earnings, employment or social status: (a) shared collective social goods, such as the contributions of higher education to social tolerance, or democratic governance and (b) non-pecuniary individual goods such as the lifetime contribution of higher education to the subjectification (self-formation) of students and to their socialisation as citizens in relational settings. This non-pecuniary domain is underplayed or hidden in those economic policies in the Anglosphere that imagine social life in exclusively transactional terms and model students as consumers, universities as businesses and higher education systems as competitive markets, suggesting the need to move beyond the Anglosphere. The research studies reported here compare approaches to public good outcomes (or their nearest lexical equivalents) in Chile, China, Finland, France, Japan and Poland, as well as Canada and England. This introduction explains the project and presents the country studies, also acknowledging the limitations of the research. It concludes with a summary of the research outcomes across the eight countries, including similarities and differences, and a generic transpositional analysis that integrates the separate findings into a single overall picture of the contribution of higher education to the public good in the eight countries.
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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".