Introduction to the Seventh Volume of Papers on Postsecondary Learning and Teaching
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
began the global transition, swift and unexpected, to online teaching and learning due to the COVID-19 pandemic.With time, reflection, and opportunities for research, academics have begun to document the impact on teaching and learning in higher education.Papers in volume seven were developed from presentations at the 2023 University of Calgary Conference on Postsecondary Learning and Teaching.Presenters were invited to explore the conference theme "Lessons learned on how blended and online learning changed postsecondary education" and the multiple aspects of the collective transformation experienced since the spring of 2020.Authors in this volume contribute their perspectives, practices, experiences, and scholarship related to the COVID-19 pandemic and how they, students, and their institutions adapted, thrived, and ultimately transformed or informed postsecondary teaching and learning.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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