Designing Globally Networked Learning Environments Visionary Pedagogies, Partnerships, and Policies
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
I would like to begin by thanking the conference organizers for inviting me to join you here today and to share my research on globally networked learning environments. What I share with you here today is what I have learned through my work with many, many colleagues and students for whose collaboration I am deeply grateful. I would also like to acknowledge the support for this work from McGill University in the form of a teaching and learning grant and from the Council for Programs in Technical and Scientific Communication in the form of a research grant. For several years now, my colleagues and I have been studying partnerships and the role of the internet in higher education. More recently, we have focused on faculty innovations in globally networked learning—the visions they create and aspire to, the hard work and passion they put into helping students develop global understanding and make knowledge in new ways, the challenges they have faced, the successes they have celebrated, and the new opportunities for innovation they have created at their universities. As I will discuss in a little while, globally networked learning environments represent an exciting paradigm shift—an innovation in learning that is critical to the development of a global civil society. And while these learning environments are only emerging, they reflect deeper social and technological
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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