In Pursuit of Innocence: A Study of Race and Ethnicity Differences in Time-to-Exoneration
Bibliographic record
Abstract
The purpose of this study is to examine the impact of race and ethnicity on time-to-exoneration through the lens of focal concerns theory. Focal concerns theory has been used to demonstrate that criminal justice actors are influenced by legal and extralegal factors in decision making and rely on stereotypes to assess blameworthiness, protection of the community, and in navigating practical constraints and consequences. Utilizing data obtained from the National Registry of Exonerations (N =507) survival analysis was performed. The findings indicate that Black exonerees experienced a longer time-to-exoneration than did White exonerees and that Hispanic exonerees experienced the shortest time-to-exoneration of all. The findings offer support for focal concerns theory in the demonstration that racial and ethnic differences are present in time-to-exoneration resulting in disparities which disadvantage minorities. Further support for focal concerns theory is found in that the legal components of a case are shown to be associated with racial and ethnic differences in time-to-exoneration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".