Research at risk: Global challenges, international perspectives, and Canadian solutions
Bibliographic record
Abstract
Although traditionally viewed as paragons of international cooperation, research institutions and universities are becoming venues for hostile foreign activity. Research security (RS) refers to the measures that protect the inputs, processes, and products that are part of scientific research, inquiry, and discovery. While RS traces its roots to the 1940s, global economic and research and development competition, the nexus between dual-use technology and military power, a cluster of newly emerging industries, scientific responses to the COVID-19 pandemic, and societal shifts towards digitization, combine to challenge RS in unique ways. With an eye on safeguarding traditional notions of open science, our article refurbishes Canadian RS within the context of emerging challenges and international responses. Detailing the legal, extralegal, illegal, and other ways in which RS is threatened, we use a comparative assessment of emerging responses in the US, Australia, Japan, and Israel to draw lessons for Canada.
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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.028 | 0.038 |
| Scholarly communication | 0.025 | 0.011 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 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".