Disaster relief aid as soft diplomacy: Case of Canadian disaster diplomacy in Nepal 2015 earthquakes
Bibliographic record
Abstract
Abstract This article explores Nepal Earthquakes 2015 as a case of Canadian disaster diplomacy, tracing the diplomatic ties between Canada and Nepal. We argue that the warming up of diplomatic relations between these countries in the 50th diplomatic year sprinted Canada's support following the 2015 Nepal earthquakes. The earthquakes increased Nepali Canadians' involvement in the relief efforts, reinforced their diasporic identities, and increased their visibility as a visible minority community within the broader Asian diaspora in Canada while surfacing the political divisiveness amongst them. Against this backdrop, we ask: what lessons can be learned for Canadian disaster diplomacy efforts in the South Asian region? Based on field evidence, we argue that non-state actors, western disaster aid, and local government efforts fail to supply disaster relief in socially optimal quantities. We urge Canadian disaster aid actors to critically reflect on their aid strategies for effective help, not merely rhetoric and band-aid solutions.RésuméCet article explore les tremblements de terre au Népal de 2015 comme un cas de diplomatie canadienne en cas de catastrophe, retraçant les relations diplomatiques entre le Canada et le Népal. Nous soutenons que le réchauffement des relations diplomatiques entre ces pays au cours de la 50e année diplomatique a fait bondir le soutien du Canada à la suite des tremblements de terre de 2015 au Népal. Les tremblements de terre ont accru la participation des Canadiens népalais aux efforts de secours, renforcé leur identité diasporique et accru leur visibilité en tant que communauté de minorité visible au sein de la diaspora asiatique au Canada tout en faisant ressortir les divisions politiques entre eux. Dans ce contexte, nous nous demandons : quelles leçons peut-on tirer des efforts canadiens de diplomatie en cas de catastrophe dans la région de l'Asie du Sud ? Sur la base de preuves sur le terrain, nous soutenons que les acteurs non étatiques, l'aide occidentale en cas de catastrophe, et les efforts des gouvernements locaux ne parviennent pas à fournir des secours en cas de catastrophe en quantités socialement optimales. Nous exhortons les agences canadiennes de l'aide aux sinistrés à réfléchir de manière critique à leurs stratégies d'aide pour être mieux capable d’offrir une aide efficace, et non seulement de la rhétorique et des solutions de fortune.Keywords: disaster diplomacy, Canada, Nepal, Nepal earthquake 2015Mots-clés : diplomatie en cas de catastrophe, Canada, Népal, séisme au Népal 2015
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".