It’s time for Canadian decisions on lethal drones
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
The newly-elected Canadian government of Prime Minister Justin Trudeau is engaged in a defence review process that will result in a new Defence White Paper. There is a strong possibility that Canada acquires more Unmanned Aerial Vehicles(UAVs) for a range of military tasks including disaster relief, surveillance, reconnaissance and the provision of close air support to soldiers in combat. States and sub-state actors can decide to use UAVs or drones to carry out strikes against targets in relatively distant or inaccessible locations. However, this article argues that more consideration, review, transparency and international law regarding drone policy are needed. It suggests Canada take the lead and abide by emerging international law concerning drones as well as become one of the first countries to establish impartisan and unbiased commissions to consider their merits and demerits. Further consideration, monitoring and stringent overview of this relatively new defence technology will be important. It is suggested that Canada’s Department of National Defence declare its intention to take the initiative in the international community in terms of abiding by new and emerging international law, if and when the government decides to acquire significantly more numbers of drones as part of its current defence review process.
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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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