Bibliographic record
Abstract
Many feminists today are challenging the outmoded aspects of both the conventions and the study of religion in radical ways. Canadian feminists are no exception. Gender, Genre and Religion is the outcome of a research network of leading women scholars organized to survey the contribution of Canadian women working in the field of religious studies and, further, to plot the path forward. This collection of their essays covers most of the major religious traditions and offers exciting suggestions as to how religious traditions will change as women take on more central roles. Feminist theories have been used by all contributors as a springboard to show that the assumptions of unified monolithic religions and their respective canons is a fabrication created by a scholarship based on male privilege. Using gender and genre as analytical tools, the essays reflect a diversity of approaches and open up new ways of reading sacred texts. Superb essays by Pamela Dickey Young, Winnie Tomm, Morny Joy and Marsha Hewitt, among others, honour the first generation of feminist theologians and situate the current generation, showing how they have learned from and gone beyond their predecessors. The sensitive and original essays in Gender, Genre and Religion will be of interest to feminist scholars and to anyone teaching women and religion courses.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.023 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".