The Criminal Selfie: Conveying Grievance While Recording and Live Streaming Antisocial Behavior
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 Despite attempts to regulate content, social media platforms continue to host images of antisocial behavior and crime. These images include dashboard videos of road rage and CCTV footage of shoplifting, as well as more extreme recordings of torture, sexual assault, suicide, and mass shootings. These images are often produced by offenders of their own volition using smartphone cameras and wearable recording devices. We understand criminal selfies as media content of antisocial behavior or crime produced by or with the awareness of an offender. By producing a criminal selfie, an offender renders themselves vulnerable to public scrutiny, legal punishment, and other negative outcomes. Yet criminal selfies remain a popular form of toxic online communication. This manuscript theorizes that one of the previously underappreciated explanations for criminal selfies is a desire to broadcast personal grievances. In such cases, they allow an offender to publicize their motivating politics and to offer them to an online audience for consideration and discussion. Antisocial content often evokes an unfavorable ratio of denunciation versus supportive responses. We claim that some offenders wager that a criminal selfie nonetheless earns their grievances a degree of awareness and, potentially, consequence. Some criminal selfies reflect a willingness to self-incriminate by documenting antisocial behavior in hopes that their images will contribute to public discourse. This article contributes to studies of criminal visibility by addressing how it can be intended as political expression. We first outline the concept of the criminal selfie and how it reflects a changing relationship between visibility and criminality in contemporary digital society. We then review literature on the motives of criminals who film themselves. We seek to compliment this literature by considering socially and politically aggrieved individuals producing antisocial content. This includes livestreams of white nationalist mass shootings (Christchurch, Halle) as well as a series of Reddit groups that solicit and (counter-)denounce antisocial grievances by digital media users (r/iamverybadass, r/publicfreakout, r/iamatotalpieceofshit).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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