On the Natural Intelligence of Women in a World of Constrained Choice: How the Feminization of Clerical Work Contributed to Gender Pay Equality in Early Twentieth Century Canada,
Bibliographic record
Abstract
This article examines some of the more pertinent details of the feminization of clerical work in the context of early twentieth century Canada and the impact that this had upon gender pay inequality. More generally, we address the question of the conditions under which labor market segmentation, such as the feminization of clerical work, can be expected to adversely affect the relative pay of women. To this end new labor market and related estimates for Canada are developed. The Canadian economy experienced significant economic change during the first three decades of the twentieth century. Output and population grew at unprecedented rates while agriculture became less important, Canada's urban population surpassed its rural, and, as well, new forms of business organization were implemented in the private and public sectors alike (Altman 2001a). It was during these times of dramatic economic and social change that the structure of Canadian women's market employment was transformed in fundamentally important ways. During the 1900-1930 period clerical work became the occupation of choice for a growing percentage of female labor force participants and, in turn, clerical work became increasingly feminized.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.034 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".