Bibliographic record
Abstract
Abstract Team‐Based Learning: A High‐Impact Educational Strategy Neil Haave University of Alberta, Augustana Campus GLADO Ellen J. Langer Harvard University The “Finnish Miracle” in Education: Pedagogy, Policy, or Something Else? (part two) Mark Stoner with Matti Rautiainen, Olli‐Pekka Moisio, and Crystal Green CREATIVITY CAFÉ Creativity and the Flipped Classroom Charlie Sweet, Hal Blythe, and Rusty Carpenter Eastern Kentucky University DEVELOPER'S DIARY Metadisciplinary Awareness Can Illuminate the Meaning, Quality, and Integrity of College Degrees: Educating in Fractal Patterns XL Ed Nuhfer, (Geology & Faculty Development), Elisabeth Harrington (Music), Suzanne Pasztor (History), and Sarah Whorf (Art)—Humboldt State University AD REM … There's More To Critical Thinking Than We Think Marilla D. Svinicki The University of Texas at Austin
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.823 | 0.705 |
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".