Open for Business: A Panel on Creating International Research Opportunities with Canadian Universities and IS Researchers
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
International research collaborations are essential for advancing knowledge and fostering innovation in Information Systems (IS). Given Canada’s strengths in IS research and its robust funding and innovation ecosystem, including support from SSHRC , Mitacs and other granting bodies and technology incubators/accelerators (such as Québec Tech ) there is a growing opportunity for global researchers to engage with Canadian institutions. This panel will explore pathways for international scholars to collaborate with Canadian IS researchers, addressing key challenges such as funding structures, institutional policies, interdisciplinary integration and entrepreneurial ecosystem growth. Featuring leading experts in IS research, Canadian funding bodies and technology incubation, this discussion will provide practical insights on building sustainable research partnerships that generate both academic and practical outcomes. Attendees will gain a deeper understanding of Canada’s research landscape, funding mechanisms, and best practices for fostering impactful international collaborations with tangible results.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 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