Learned Women, “Leftover” Women, and “The Third Sex” Women's Learning in the Confucian Tradition and Contemporary China
Bibliographic record
Abstract
Abstract This paper investigates women's learning experiences in the Confucian tradition and the social dismay and stigma associated with them. Despite being considered a meta-virtue in the Confucian tradition, learning becomes rather complex when women are the learners. It is viewed by learned women as a curse rather than a blessing in pre-modern China; it is associated with the stigma of “leftover women” and “the third sex” in contemporary China. Based on an examination of works written by women thinkers, I argue that the asymmetry in social recognition for men's and women's learning is rooted in the social and family structure of nei (in) and wai (out), which does not assign sufficient cultural and moral significance to learning achieved in the nei domain nor permit its continuous and accumulative existence. I propose two preliminary steps to rectify the issue of the lack of social and moral recognition of women's learning: first, a reforming of the nei and wai structure to allow assigning more moral, cultural, and normative significance to affairs in the nei domain. Second, re-examine and utilize classical Confucian texts such as the Mencius and later works by women writers to support and guide such reformations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".