The Canadian and Argentinian textile industry: Gender and working process, 1888-1951, an exploratory research
Bibliographic record
Abstract
In this paper I analyze the working process of the Canadian and Argentinian textile industry between 1888 and 1951. Based in Buenos Aires and Montreal as case studies, these two cities concentrated the textile industry in the two countries. I approach this historical process from a gender, social history and economic perspective, doing an original research of the working process since I include the domestic work as part of it. The starting point of this analysis is that capitalism is patriarchal. One of the main conclusions of this work is that the women workers had not two workdays (domestic work and workday), but only one extended workday that included the domestic work and their work in the factory, for which they received a minimum paid. These workdays had a duration of roughly 17 or 19 hours in Canada or Argentina, respectively. Finally, in this work I demonstrate that gender relationships cannot be excluded of the study of the working process
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| 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 | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".