Pitfalls of Emancipation and Discourses of Security: Reflections on Canada’s ‘Security with a Human Face’
Bibliographic record
Abstract
The call to develop self-consciously critical approaches to security stands as one of the more hopeful intellectual developments in recent years. It is argued that a critical – and hence, emancipatory – strategy is one which focuses on the more ‘empirical’ question of how security issues are framed in political discourse. Here the emphasis is on exploring how different conceptions of security – both traditional and expanded – find their way into public debates; how specific values are made socially concrete in this process, and how people both act and are acted upon in the process of history unfolding. The merits of this approach are illustrated by examining a concrete case: the evolution of security discourse in Canada in the latter half of the 20th century, and the function of that discourse in terms of changing forms of state and world order.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.066 | 0.085 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".