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Record W4416062011 · doi:10.1080/1068316x.2025.2585352

‘I made it home and i’m flourishing’: qualitative interviews investigating post-traumatic growth among the Ohio innocence project’s freed clients & exonerees

2025· article· en· W4416062011 on OpenAlexaff
T Henry, Guadalupe Blanco-Velasco, Donna Mayerson

Bibliographic record

VenuePsychology Crime and Law · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsInnocenceQualitative researchWork (physics)Perspective (graphical)Interrogation

Abstract

fetched live from OpenAlex

Wrongfully convicted individuals spend decades fighting for their freedom, and once released, they must reintegrate and adapt to society while dealing with collateral processes (e.g. legal issues). Despite research investigating the many issues that wrongfully convicted individuals experience post-release, little is known about how they might redefine their traumatic experiences to cope with their new routines. To that end, we interviewed 13 of the Ohio Innocence Project’s freed clients and exonerees using questions that were conceptualized based on the Post-traumatic Growth (PTG) cognitive model. The results showed that the interviewed clients did experience the five factors of PTG: New Possibilities, Relating to Others, Spiritual Change, Appreciation for Life, and Personal Strength. Moreover, the interviewees shared advice for new and future freed clients and exonerees about how to navigate reintegration and how to overcome common difficulties. Based on these interviews, individual-level positive outlets (e.g. maintaining and developing a community), innocence organization-level opportunities (e.g. conducting speaking engagements), and criminal legal system-level reforms (e.g. less expensive prison phone calls) that could improve incarceration, exoneration, and reintegration experiences, are discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.090
GPT teacher head0.426
Teacher spread0.336 · 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
Published2025
Admission routes1
Has abstractyes

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