“Mrs. Chatelaine” vs. “Mrs. Slob”: Contestants, Correspondents and the Chatelaine Community in Action, 1961-1969
Bibliographic record
Abstract
Scholars and critics alike have presumed that readers of popular women's magazines were merely passive consumers. That was not the case with Chatelaine magazine. Reader commentary was regularly featured in the magazine and often influenced editorial decisions. This analysis of the Mrs. Chatelaine contest provides a demographic profile of the reading community, an overview of the text and the producers, an examination of the national community of readers created at Chatelaine, it also explores the reaction of “average readers” to products of popular culture. In summary, readers' responded in a host of ways to the periodical. Some enjoyed the preferred meanings offered by the magazine, particularly of traditional fare (like the contest) which celebrated paragons of feminine virtue. Other readers were resistant to this material - they criticised, challenged, or parodied the contest - clearly demonstrating that “average” readers did not passively accept material which was at odds with their lives.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.054 | 0.025 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".