An Examination of Michigan State University’s Image Repair via Facebook and the Public Response Following the Larry Nassar Scandal
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
The purpose of this study was to examine how Michigan State University (MSU) utilized Facebook as a tool for image repair following the Larry Nassar sex abuse scandal. Specifically, the researchers were concerned with the image-repair approach utilized by MSU during Nassar’s hearing and in its immediate aftermath. Additionally, the researchers examined users’ responses via Facebook comments to determine reactions to MSU’s image-repair strategies. MSU primarily employed the image-repair tactic of corrective action along with rallying, bolstering, and mortification. Overall, individuals posting comments did not appear to buy into MSU’s image repair. Users focused blame on MSU for mishandling the situation and discussed various aspects of the Nassar case as well as MSU’s mistreatment of the victims. Additionally, there was a call for MSU to change its culture, take ownership of its mistakes, and become a leader in dealing with sexual assault on campus.
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 | 0.008 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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