MétaCan
Menu
Back to cohort
Record W4389050327 · doi:10.29173/wclawr89

A Day Late and a Dollar Short: Examining Perceptions of Which Exonerees Deserve Compensation

2023· article· en· W4389050327 on OpenAlexvenueno aff
Alexandra Olson, Kelsey S. Henderson, Mark G. Leymon, Chris Carey

Bibliographic record

VenueThe Wrongful Conviction Law Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsConvictionJuryAffect (linguistics)Compensation (psychology)Criminal justicePsychologyPopulationEconomic JusticeJury trialSocial psychologyCriminologyPerceptionPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

Many exonerees do not receive compensation from the state after they are released (43%) because most states have exclusionary laws that bar exonerees from receiving compensation (n = 16 states) (Compensation Primer, 2022). This study examined public perceptions of exoneree compensation, exclusionary laws and addressed the broader question of who deserves compensation (according to community members). Online participants (n = 225) read an article about a fictional exoneree who either pleaded guilty or was convicted by a jury trial and who either did or did not have a subsequent conviction. An exoneree with a subsequent conviction was perceived as less deserving of financial compensation (roughly $8,000 less annually) and less deserving of support services. It was rated less positively than an exoneree who did not have a subsequent conviction. No differences were found between an exoneree who pleaded guilty and an exoneree who was convicted by a jury trial, demonstrating little impact of this common exclusionary rule on community members’ perceptions and decisions. Overall, participants overwhelmingly supported exoneree compensation (only 6.7% disagreed). However, there are caveats. Community members are less supportive of compensating exonerees who have subsequent involvement with the justice system. These results illustrate possible biases the public has against an already marginalized population that has experienced a miscarriage of justice. Because public opinion can affect policy change, these results significantly affect state exclusionary rules and exoneree compensation policies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.071
GPT teacher head0.348
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe Wrongful Conviction Law ReviewSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207