The Effectiveness of Feminist Pedagogy in Empowering a Community of Learners
Bibliographic record
Abstract
The purpose of this study was to determine whether a pedagogy grounded in feminist ideals has the potential to empower students to make changes consistent with those ideals in their personal and professional lives. In Phase I, qualitative data were collected through e-mail questionnaires from students in two nursing schools, one in Canada and one in the United States. Findings were used to identify an appropriate tool to measure the empowering influence of feminist pedagogy. In Phase 2, a pretest-posttest design used Barrett's Power as Knowing Participation in Change Tool (PKPCT) to measure student empowerment. A clinical setting was added in a third baccalaureate nursing program. A total of 218 students participated in seven course offerings-four classroom and three clinical. One hundred one matched pairs were obtained, for an overall response rate of 46%. Repeated measures ANOVA revealed that overall empowerment scores, as measured by the PKPCT, and classroom empowerment (CE), as measured by the addition of a variable (i.e., the ability to contribute in class), increased significantly from pretest to posttest. Interaction between Sites 1 and 2 was also significant. Regression analysis indicated posttest CE scores added to pretest PKPCT and CE scores provided a strong model to predict overall empowerment scores, measured by the PKPCT at Time 2 (R2 = .703). Despite limitations related to loss of follow up and low response rates at one site, the results of this study supported both hypotheses: that empowerment would increase over the course of the class in which feminist pedagogical principles were used, and that classroom empowerment is likely to extend beyond the classroom to personal and work environments.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".