Reflections on Integration, Interaction, and Community: the Science One Program and Beyond
Bibliographic record
Abstract
We describe three interrelated programs in interdisciplinary, undergraduate science education, two at the first-year level and the third an upper-division degree program. They are administered through the Faculty of Science, rather than through individual departments, and are taught by multidisciplinary teams of professors from various departments. In contrast to many programs discussed in the literature, these programs are intended for majors and honors students in all scientific disciplines. They aim to develop transferable skills and a broad outlook on science, in addition to a rigorous foundation in disciplinary knowledge. Interactive engagement and integration of content across disciplines are at the core of the approach. Each program brings together a strong community of scholars that includes students, faculty, staff, and administrators. We explore the benefits of these communities to students and describe the attraction and challenges for the faculty and students who work in them. In that context, we discuss institutional challenges that we faced in creating and sustaining those communities, and in disseminating the ideas on which they are based. In conclusion, we consider the general problem of designing and implementing cross-disciplinary programs.
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 | 0.026 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.027 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.013 | 0.032 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".