Confronting the Gap: Why Religion Needs to be Given More Attention in Womenââ¬â¢s Studies
Bibliographic record
Abstract
This essay comes out of my experience of finding my work marginalized in both Religious Studies and WomenA¢â¬â¢s Studies. It seems that religion is not a primary concern in mainstream WomenA¢â¬â¢s Studies scholarship. When I talk about taking religion seriously, I am pointing to both aspects of religious/spiritual life. I am calling for an inclusion of religion/spirituality in feminist scholarship which does not necessarily say religion is all good, but rather recognizes that it exists and can, and in fact does, have multiple meanings for womenA¢â¬â¢s lives. Feminist scholars who are concerned with intersectional analysis and addressing womenA¢â¬â¢s lived experiences need not radically change their theoretical approaches in order to take into account the integration of religion/spirituality with other aspects of womenA¢â¬â¢s lives. Addressing womenA¢â¬â¢s religious lives/experiences very simply adds another category of analysis to a theoretical approach which already calls for multiple categories of analysis.
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 | 0.037 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.048 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".