Re-Enchanting Higher Education Through Women's Private Lifeworlds
Bibliographic record
Abstract
This book chapter addresses the importance of recovering the treasures of knowledge and epistemology found in the private lifeworlds of women—knowledge that might otherwise remain underexamined or sidelined—as a means of reforming and re-enchanting higher education. Indeed, there is an intimacy in women's private worlds steeped in a special kind of knowledge. This approach not only preserves the often-underexamined stories of women's private lifeworlds, but also advocates for a more integrated model of education that facilitates pedagogical and epistemic osmosis between family, work, and personal life, rather than perpetuating a sharp disconnect between these spheres. By tracing epistemic shifts across the centuries in Michel Foucault's The Order of Things (1966), along with my own autoethnography as a previously homeschooled child, I aim to crystallize and materialize this thesis further, in line with my anthropological disciplinary approach.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".