Bibliographic record
Abstract
Abstract Cover Story Review program integrity regulations for programs authorized under Title IV Review new Title IV regulations to plan compliance Learn new disclosure, reporting requirements imposed by partial gainful employment rule News & Notes ED releases overview of student privacy laws, concepts British institution offers MBA through Facebook Dutch university grants new diploma to transsexual student First look at IPEDS data shows persistence, completion rates Compliance Prepare to communicate with third parties on redisclosure Tools of the Trade Automate dismissal process for efficiency, time savings Review advantages of automated dismissal processing Implement software that promotes automation Professional Development Take social cues from Hollywood stars to advance your career Use these strategies to be a star among registrars What Would You Do? What would you do about a staffer viewing pornography? Lawsuits & Rulings FERPA FPCO won't investigate without evidence of tapes, documents FPCO rejects complaint by student who didn't meet ‘burden of proof’ ACADEMIC AFFAIRS Court cannnot require university to allow plaintiff to revise dissertation Leaders & Innovators DAVID B. JOHNSTON, ASSOCIATE VICE‐PROVOST FOR ENROLMENT AND REGISTRAR UNIVERSITY OF CALGARY Accept leadership roles in your professional organization Build your profession through association activity
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.830 | 0.718 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".