Governing 'dual-use' research in Canada: A policy review
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
National and international organisations have implemented governance mechanisms to address a diversity of ethical, security and policy challenges raised by advances in research and innovation. These challenges become particularly complex when research or innovations are considered ‘dual-use’, i.e. can lead to both beneficial and harmful uses, and in particular, civilian (peaceful) and military (hostile) applications. While many countries have mechanisms (i.e. export controls) to govern the transfer of dual-use technology (e.g. nuclear, cryptography), it is much less clear how dual-use research from across the range of academic disciplines can or should be governed. Using the Canadian research and policy context as case study, this paper will first, examine the governance mechanisms currently in place to mitigate the negative implications of dual-use research and innovation; second, compare these with other relevant international governance contexts; and finally, propose some ways forward (i.e. a risk analysis approach) for developing more robust governance mechanisms.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: yes · About a Canadian topic: yes | Not applicable | low |
| gpt | MetaresearchScience and technology studies Domain: Methods · Genre: Review About the Canadian research system: yes · About a Canadian topic: yes | Other design | high |
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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it