The Creation of a Massive, Multi-team Organized (MMO) Course
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
Instructors and administrators recognize that our world demands graduates who are not only prepared to meet today's challenges but are also equipped to tackle novel problems of the future. This article describes the creation of an interdisciplinary, team-taught course designed using features of collaborative learning and problem-based learning with a focus on the impact of teaching with a large number of faculty. The course was well-received by students with positive feedback about integration of previous curricular content and a low-pressure learning environment. However, the course was not without its challenges. Participation from over half of the program's teaching faculty required a considerable investment of time and resulted in weekly inconsistencies throughout the semester. This article highlights successes, challenges, and recommendations for others seeking to design a course with a similar number of faculty. This course style is referred to as a "massive, multi-team organized (MMO) course."
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 | 0.002 | 0.006 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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