Bibliographic record
Abstract
In August-September 2024, Global Affairs Canada held public consultations on “Potential New Measures to Advance and Defend Canada’s Economic Security Interests.” The inputs provided will help the Government of Canada update or develop approaches and measures that would advance Canada’s economic security interests. The following analysis and recommendations were submitted by the author in response to the call for expert views on the subject. The author argues that, in addition to public consultations, Canada still needs a strategic framework to think about national security, prosperity and economic security in a comprehensive, whole-of-governmet fashion and makes five specific recommendations. Canada should: 1. Develop, promulgate and implement a whole-of-government National Economic Security Strategy; 2. Undertake an in-depth intelligence-based all-source threat assessment of foreign economic threats to Canada, including an unclassified version for Canadians, prior to deciding on the measures to be taken in the National Economic Security Strategy to secure Canada’s economic security and prosperity; 3. Undertake a full cost analysis of the gains and losses to the Canadian economy and individual economic security from the applications of all the measures delineated in the National Economic Security Strategy; 4. Undertake an in-depth analysis of how allies and other states would respond to the implementation of a new National Economic Security Strategy (taking into account the best, worst and most likely outcomes) and develop options, to be included in the Strategy, to mitigate the risk of harmful outcomes; and 5. Consider developing a National Industrial Strategy and an International Trade Strategy alongside or as key components of the National Economic Security Strategy. Received: 09-24-2024 Revised: 10-25-2024
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.023 | 0.011 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".