International survey of research university leadership: views on supporting open access scholarly & educational materials
Bibliographic record
Abstract
This report looks closely at the attitudes on open access of a sample of 314 deans, chancellors, department chairmen, research institute directors, provosts, trustees, vice presidents and other upper level administrators from more than 50 research universities in the USA, Canada, the UK, Ireland and Australia. The report gives detailed information on what they think of the cost of academic journal subscriptions, and how they understand the meaning of the term “open access.” The study also gives highly detailed data on what kind of policies the research university elite support or might support in the area of open access, including policies such as restricting purchases of very high-priced journals, paying publication fees for open access publications, mandating deposit of university scholarship into digital repositories, and developing open access educational materials from university resources. Just a few of the report’s many findings are that: • The lowest percentage of those interviewed considering the high cost of journals a big problem was in the United States, where only 11.56% of higher education leadership had this opinion; the highest share, in Canada, 27.45% had this view. • More than 40% of administrators from public universities in the sample supported the idea of using university funds to develop open access textbooks from materials developed or owned by the university or its scholars. • Support for mandatory deposit requirements for scholarly output into university digital repositories was highest among the universities ranked in the top 41 worldwide. Data in the report is broken out by country, university ranking, work title, field of work responsibility, level of compensations, age, gender and other variables.
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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".