Making Research Count: Analyzing Canadian Academic Publishing Cultures Higher Education Strategy Associates
Bibliographic record
Abstract
Higher Education Strategy Associates (HESA) is a Toronto-based firm specializing in research, data and strategy. Our mission is to help universities and colleges compete in the educational marketplace based on quality; to that end we offer our clients a broad range of informational, analytical, evaluative, and advisory services. Stoakley-Dudley Consultants is a long standing executive search firm that over the last three years has established itself as a proven partner in public sector searches, specifically in healthcare and education. Stoakley-Dudley Consultants partners with and sponsored the research behind the generation of the H-Index and the quantifiable use of Bibliometrics to level the playing field in academic institutional comparisons. Stoakley-Dudley and HESA have a strong track record of working together to bring forward new ways of thinking about the academy and implications for hiring senior leadership. Please cite as:
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 | 0.032 | 0.321 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.099 | 0.203 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.025 | 0.007 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".