From Lip Service to Neglect: The Evolution of Canadian Foreign Policy and the Darfur Genocide
Bibliographic record
Abstract
Students of Canadian political culture can expect to develop a deep pride for our illustrious and celebrated military history. From the victory at Vimy Ridge during the Great War to the invasion of Normandy during World War II, Canada has left a lasting mark in military intervention across the globe. More recently, Canada has stood back from any robust military commitment and has instead defined itself as a peacekeeping state concerned with issues of development and humanitarian assistance rather than war and peace. The purpose of this paper is to examine the evolution of Canada's policy concerning humanitarian issues, more precisely, in response to the Darfur genocide since 2003. This paper evaluates Paul Martin's policy during his prime ministership and then analyzes Prime Minster Stephen Harper's policy since his election in 2006. This examination demonstrates that Martin's rhetoric regarding Canada's contribution to stopping the Darfur genocide became so exaggerated that it was impossible for government action to accommodate. By contrast, although Harper's limited action in sending financial aid and military expertise to Darfur mirrors that of his predecessor, Harper has effectively taken the air out of Martin's inflated rhetoric. Harper's reluctance to publicly address Canada's response to the Darfur genocide represents a divergence from the trend in contemporary Canadian foreign policy; in other words, Harper's rhetoric matches his government's action. But Harper's rhetoric is the by-product of an overall strategy to focus his foreign policy message on missions that will achieve the most political points at home. In short, Harper has largely neglected the Darfur genocide in order to position himself as a decisive leader concerned with issues of peace and security instead of issues of development and human rights.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.031 | 0.017 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".