R<scp>e‐imaging</scp> W<scp>ar</scp>: T<scp>he</scp> V<scp>oice of</scp> W<scp>omen, the</scp> C<scp>anadian</scp> A<scp>id for</scp> V<scp>ietnam</scp> C<scp>ivilians, and the</scp> K<scp>nitting</scp> P<scp>roject for</scp> V<scp>ietnamese</scp> C<scp>hildren</scp>, 1966–1976
Bibliographic record
Abstract
This essay focuses on a humanitarian knitting project to make dark camouflaged clothing for Vietnamese children residing in combat zones that was sponsored by the most significant Canadian peace association of the Vietnam War era, the Voice of Women/La Voix des Femmes (VOW). VOW members were inspired by an influential Canadian humanitarian group and aided by other North American women's peace groups—notably Women Strike for Peace and the Women's International League for Peace and Freedom. I will argue that the members of VOW sought to disrupt and contest the stereotypic Western image of the compliant and uncritical woman war worker by challenging an essentialized image of a girl or woman knitting for “her boys” during wartime. By placing the implicitly motherly female knitter in the service of the victimized Other (Vietnamese children), VOW women and their like‐minded sister peace activists in the United States helped to recast in critical fashion the hegemonic male‐privileged discourse of war in a manner unique to their gender and time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.099 | 0.024 |
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".