"The Dresden Story": Racism, Human Rights, and the Jewish Labour Committee of Canada
Bibliographic record
Abstract
This article uses a case study to explore how organized labour, particularly the Jewish Labour Committee, contributed to the development of human rights values and anti-discrimination law in the immediate post-war period. The study focuses on the town of Dresden, Ontario, which at one time was infamous for its treatment of blacks. When a number of organizations (including labour groups) lobbied the Ontario government to create Canada's first Fair Accommodation Practices Act, they pointed to Dresden as an example of why this legislation was necessary. After the legislation was passed, they used litigation to ensure that discrimination in Dresden would come to an end. The paper demonstrates that, although the trade union movement in Canada was not free from racism, it nevertheless played an important and under-appreciated role in fighting for egalitarian human rights. Resume Cet article utilise une etude de cas pour explorer comment la main-d'oeuvre organisee, en particulier le comite de la main-d'oeuvre juive, a contribue a mettre en valeur les droits de la personne et les lois contre la discrimination raciale dans les annees d'apres-guerre. L'etude se concentre sur la ville de Dresden, Ontario, qui etait reputee a l'epoque pour la facon dont ses habitants traitaient les Noirs. Lorsque plusieurs organismes (y compris des groupes travaillistes) ont fait des pressions sur le gouvernement de l'Ontario pour qu'il adopte la premiere loi des pratiques d'equite au Canada, ils ont cite l'exemple de Dresden pour expliquer pourquoi cette loi etait necessaire. Apres l'adoption de la loi, ces organismes ont meme intente un proces pour s'assurer que la discrimination raciale a Dresden prenne fin. Selon l'article, bien que le mouvement syndical au Canada ne soit pas exempt de racisme, il a neanmoins joue un role important, mais peu apprecie, dans la bataille pour les droits a l'egalite.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.072 | 0.022 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".