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
In the fall of 2010, and again in spring 2012, the Author taught a course entitled Gender & Criminal Law inside the Western Massachusetts Correctional Alcohol Center in Springfield. Participants in the course included roughly equal numbers of law students from the Author's home academic institution, Western New England University School of Law, and residents of the facility. For fourteen weeks, the class met weekly at the institution to discuss issues including domestic violence law reform, the role of family ties in sentencing, and gender issues in prisoner reentry.The Author taught this course in a modified form of the Inside-Out format. Inside-Out is a national training program founded by Lori Pompa and based at Temple University. It offers training programs several times each year. The program has trained more than 300 instructors to date who have offered 300 Inside-Out courses around the U.S. and in Canada. Most of these instructors are college professors who typically teach undergraduates. The Author participated in training in summer 2009, becoming the first law school professor to join the Inside-Out network.This Essay reflects on the Author's Inside-Out experience. It makes the case for Inside-Out as a particularly useful form of experiential learning for law students. It also describes some techniques she learned through teaching an Inside-Out course that can be implemented in a more traditional law school setting.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.010 |
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