Bibliographic record
Abstract
Philosophy for Comparative and Int'l Higher EducationThis is the official journal of the Comparative and International Education Society's (CIES) Higher Education Special Interest Group (HESIG), which was created in 2008.HESIG serves as a networking hub for promoting scholarship opportunities, critical dialogue, and linking professionals and academics to the international aspects of higher education.Accordingly, HESIG will serve as a professional forum supporting development, analysis, and dissemination of theory-, policy-, and practice-related issues that influence higher education. Submission and ReviewThe Editorial Board invites contributions dealing with the complementary fields of comparative, international, and development education and that relate to one of the areas listed in the Philosophy section above.Contributors may:1) Submit a research article of 1,500 -3,000 words.All articles will undergo a blind-review peer-editing process.2) Submit a comparative report analysis of 750 -1,000 words that examines current policies related to higher education institutional policy.3) Submit graduate student research in-progress of 500 -1,000 words that shares new research that will help to set the tone for current and emerging issues in the field. Electronic submissions are accepted on an on-going basis and should be sent to jcihe.hesig
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.713 | 0.538 |
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".