Canadian military involvement in humanitarian assistance: progress and prudence in natural disaster response
Bibliographic record
Abstract
In response to the 12 January 2010 earthquake in Haiti, Canada launched its largest international disaster-relief effort to date. The most visible aspect of its response came in the form of the over 2000 military personnel who were deployed to Haiti to assist in rescue, relief and recovery operations. As part of Canada's whole-of-government approach, this humanitarian intervention required close collaboration between the Department of National Defence (DND) and its primary civilian partners in humanitarian response, namely the Department of Foreign Affairs and International Trade (DFAIT) and the Canadian International Development Agency (CIDA). Using information from 27 confidential interviews with actors involved in the decision-making and administration of Canada's emergency humanitarian assistance, this paper investigates how the Canadian disaster-relief structure is able to facilitate a response of this magnitude, highlighting structural, ideational and decision-making features which foster interdepartmental collaboration. While the response was beneficial in many ways, however, this paper cautions against increased military involvement in disaster-relief efforts. Not only can this affect Canada's ability to uphold the humanitarian principles of responding based on needs on the ground, and in ways that are fair and impartial, it also increases the power of political leadership to shape the magnitude, timeliness and decision to intervene.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".