Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The Board Speaks Career‐oriented education in high demand, but challenges remain Create link between your programs and local business partners, policymakers Distance Learning MOOCs can show adult prospects what online higher education is really like Know why you should at least consider offering free online classes Consider model to generate revenue from MOOC technology Briefing Embry‐Riddle launches drone program MIT introduces MOOC certificates Skepticism persists over online education Transitions Incoming student posts Facebook complaint about book costs What Would You Do? Campuswide universal design initiative requires your unit's participation Managing Your Office Ramp up your credibility by improving your listening skills Practice using the SIER listening formula Lawsuits & Rulings DISABILITY Court rules adult student can't base ADA claim on third party's disability ENROLLMENT MANAGEMENT Students can't blame law school for misreading information about employment prospects Leaders & Innovators MARIE BOUNTROGIANNI, INTERIM DEAN OF CONTINUING EDUCATION, RYERSON UNIVERSITY Focus on accessibility to better serve your older learners
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it