‘Angry and heartbroken for the failure of the system’
Bibliographic record
Abstract
As the number of wrongful conviction media productions released to the public increases, an understanding of their potential impact on viewers is prudent. One such production, When They See Us, depicts the wrongful conviction of five racialized youth, and we investigated the effect of watching this specific wrongful conviction media production on a subset of Reddit users’ online conversations about wrongful convictions and the criminal justice system in general. Following an inductive content analysis of Reddit comments shared to r/WhenTheySeeUs (N = 461), seven coding categories were observed. The ‘Wrongful Conviction Relevant’ coding category was the third most frequently occurring, representing 28% of total comments. Additionally, after conducting a deeper thematic analysis of the ‘Wrongful Conviction Relevant’ comments, the following themes and subthemes were identified: Risk Factors (Individual Characteristics and System Factors), Exoneration and Beyond (Impacts on Exonerees and Changes to System), and the Innocence Movement (Unmet System Expectations and Public Awareness). Users’ ‘Wrongful Conviction Relevant’ comments were situated within the academic literature investigating wrongful conviction correlates, outcomes, and preventative measures, and discussed in relation to viewer reactions to other wrongful conviction media productions.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".