Bibliographic record
Abstract
Written by diplomatic practitioners, Human Security and the New Diplomacy is a straightforward account of challenges already overcome and the prospect for further progress. From the evolution of peace-keeping, to peacebuilding, humanitarian intervention, war-affected children, international humanitarian law, the International Criminal Court, the economic agendas of conflict, transnational crime, and the emergence of connectivity and a global civil society, the authors offer new insights into the importance of considering these issues as part of a single agenda. Human Security and the New Diplomacy is a case-study of a major Canadian foreign policy initiative and a detailed account of the first phase of the human security agenda. The story of Canada's leading role in promoting a humanitarian approach to international relations, it will be of interest to foreign policy specialists and students alike. Contributors include David Angell, Alan Bones, Michael Bonser, Terry Cormier, Patricia Fortier, Bob Fowler, Elissa Goldberg, Mark Gwozdecky, Sam Hanson, Paul Heinbecker, Eric Hoskins, Don Hubert, David Lee, Dan Livermore, Jennifer Loten, Rob McRae, Valerie Ooterveld, Victor Rakmil, Darryl Robinson, Jill Sinclair, Michael Small, Ross Snyder, Carmen Sorger, and Roman Waschuk.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".