Spoiled Identity? Exploring the Impact of Wrongful Conviction on “Self,” Status, and Stigma
Bibliographic record
Abstract
Sociologists have long argued that arrest, conviction, imprisonment, and the possession of a criminal record impact individuals in consequential, often inescapable, ways. The many repercussions associated with a criminal label demonstrate the state’s ability to transform identities and create structural barriers to full participation in society. However, both classic and contemporary scholarship lack a nuanced understanding of how criminal labeling and punishment are experienced as the occurrence of wrongful conviction demonstrates that not all who are assigned a criminal label have offended. The wrongly convicted provide an opportunity to interrogate the impact of labeling, punishment, and stigma on those who possess objective knowledge of their own innocence and eventually have their criminal labels “officially” reversed. The clash between structure and agency in the presentation of self was apparent throughout in-depth qualitative interviews with 23 men and women wrongly convicted of violent crimes. Exonerees’ alteration from “normal” to stigmatized highlighted the ability of state-sanctioned labels to reduce autonomy and unsettle the lives of innocent citizens. Further, exonerees’ recollections of wrongful imprisonment drew attention to both the prison environment’s transformative nature and the value of having resources to support one’s broader, innocent identity while incarcerated. Finally, exonerees’ experiences of label reversal support the endurance that criminal labels possess and the criminal justice system’s power to spoil identities. The findings of this study ultimately inform recommendations aimed at reducing the burdens, injustices, and traumas faced by those who are demeaned and diminished by the criminal justice system, innocent or not.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".