"""We are the blue berets:"" problematizing peacekeeping in postwar Canada"
Bibliographic record
Abstract
"This dissertation highlights some of the innumerable ways that participation in UN peacekeeping efforts became one of the central symbols employed in Canadian self-identification from 1956 to 1997. What emerges is a web encompassing forty or so years of continuity and change in how messages about peacekeeping and Canada were produced, disseminated, and received by Canadians. The strands which comprise this web are: the political rhetoric of peacekeeping, the use of peacekeeping in high school textbooks, National Film Board [NFB] documentaries about peacekeeping, newspaper coverage of peacekeeping, and editorial cartoons about peacekeeping. \n\nPeacekeeping's growing adoption as a national symbol in Canada depended considerably on writers' and artists' abilities to discuss more than the successes and failures of individual missions or peacekeeping as a governmental policy. UN peacekeeping operations have not been universally successful; Canadians, therefore, did not become attached to peacekeeping through the actual achievements of their peacekeepers. Rather, what largely determined the content of each medium's messages were persistent discussions which foregrounded Canada's participation in peacekeeping operations, as well as the existence of three parallel discourses about peacekeeping which referred to the past, the present, or the future for audiences. The nostalgic and progressive discourses encouraged Canadians to see peacekeeping as a symbolic activity. The words and images associated with these temporal understandings of peacekeeping helped blunt the impact of any criticisms which were made using functional criteria in the present. \n\nWhile internationalist in emphasis, peacekeeping was seen through domestic frames far more often. Individual missions mattered less than the idea of peacekeeping and Canada's part in its perpetuation. When missions went awry, the impact on Canada was discussed far more than the effects on the host nations. The domestic production and reception of messages about peacekeeping was therefore influenced by internationalism, but remained centred on the Canadian experience of peacekeeping. This domestic emphasis problematizes the Canadian attachment to peacekeeping while also providing answers to why so many Canadians strongly associate with peacekeeping. Or feel, as Stompin' Tom Connors put it, that "we are the Blue Berets.""
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.052 | 0.020 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".