When women athletes transgress: an exploratory study of image repair and social media response
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
Following the violation of laws or social norms, professional athletes commonly work to improve their public image and protect their livelihoods. Yet little research has focused on image repair efforts or their reception for women athletes. We consider the cases of two transgressions that took place in 2016: soccer player Abby Wambach’s arrest for driving under the influence and tennis player Maria Sharapova’s admission of a failed drug test. Using Benoit’s image repair theory, we examine each athlete’s image repair strategies on Facebook and Facebook users’ responses. Wambach used mortification and corrective action strategies, while Sharapova used evading responsibility and reducing offensiveness strategies. While there was some rejection of the athletes’ image repair strategies, most users accepted the athletes’ arguments, emphasized their support, and engaged in additional image repair work on behalf of the athletes. We consider contextual factors related to Facebook responses to the athletes’ image repair strategies.
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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 | 0.005 | 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 | 0.000 | 0.001 |
| 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