Bibliographic record
Abstract
The Factory Women is a fictional account of four Italian immigrant women in Toronto, Ontario in the 1960s. Told from the second person point-of-view, the narrative aims to challenge readers to see the story through the main character’s eyes. The women presented in the story sew uniforms in a small workshop that they have dubbed “the factory.” One of the women, Marta, lost her husband to the Hoggs Hollow disaster, an actual historical event in which four Italian workers were killed while building a water main tunnel in Toronto.When a mysterious man begins working at “the factory” alongside the women, he tries to encourage them to join a worker’s union, much to the disapproval of the workroom supervisor.While Toronto Italians have largely assimilated into mainstream Canadian society, The Factory Women strives to remind members of the ethnic community of their conflicted past in an effort to exhort them to speak out against social injustice now. While many young Italian Canadians have led privileged lives, they must remember the experiences of their own ancestors and continue to fight for the equality of all Canadians. While centred on the Italian experience in Canada, The Factory Women aims to remind all people of the importance of group solidarity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.016 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".