Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In the midst of unprecedented attention to gender-based violence (GBV) globally, prompted in part by the #MeToo movement, this book provides a new analysis of how higher education cultures can be transformed. It offers reflections from faculty, staff, and students about how change has happened and could happen on their campuses in ways that go beyond implementation of programs and policies. Building on what is already known from decades of scholarship and practice in the United States, and more recent attention elsewhere, this book provides an interdisciplinary, international overview of attempts to transform higher education cultures to eradicate GBV. Change happens because people act, usually with others. At the heart of transformative efforts lie collaborations between faculty, staff, students, activists, and community organizations. The contributors to the book reflect on what makes for constructive, effective collaborations and how to avoid the common mistakes in working with others to end GBV. They consider what has worked to challenge the reluctance—or outright hostility—they have encountered in their work against GBV and how their collaborations have succeeded in transforming the ways GBV is considered and dealt with. The chapters focus on experiences in Canada, the United States, England, Scotland, France, and India to examine different approaches to tackling GBV in higher education. They reveal the cultural variations in which GBV occurs as well as the similarities across cultures. Together, they demonstrate that, to make higher education a safe environment for all, nothing short of a transformation is required.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it