Beyond Litchfield: An Orange Epilogue Examining The Role of Friendship in Women’s Narratives of Community Re-Entry
Bibliographic record
Abstract
Canada’s fastest growing incarcerated population is female offenders. While incarcerated, these women experience damage to their existing social networks and lose significant personal relationships, making the transition from carceral to community settings difficult. In the absence of effective social support at release, many offenders face re-incarceration, as they are unable to transition into lives as law-abiding citizens. Community reintegration is not simply the absence of recidivism, but also the transition to a law-abiding conventional lifestyle, including the maintenance of existing and acquisition of new social ties that discourage future criminality. Given the multifaceted nature of community reintegration and the competing theoretical understandings of crime and recidivism, there is a need for additional research and theorizing regarding how former inmates transition and adjust to life outside of prison. Motivated by this gap in the literature, this thesis research seeks to qualitatively assess the role of peer-to-peer relationships in the lived experience of community re-integration following incarceration for women in Edmonton, Alberta by analyzing 16 interviews conducted with 8 formerly incarcerated women. The definition of friendship was operationalized during data coding to include components of shared life experience, physical and emotional availability during times of need, opportunities for ‘venting’, and the provision of supportive words or words of encouragement. Friendships are primarily maintained through talking, shared hobbies and/or leisure activities, and shared criminal activity. The women interviewed expressed low expectations of their friendships, which was largely attributable to their feelings of low self worth and of being undeserving of friendship. Friendships were found to exert a positive influence on community reintegration through access to material and emotional resources, as well as a negative influence because they did not meet all of the former offenders’ needs and in some cases encouraged continued criminality. The women interviewed expressed mixed feelings towards their futures. Some felt negatively about their chances of successfully reintegrating because of reported loneliness, feelings of hopelessness, and stigmatization. Others felt more positively because of inspirational role models, renewed commitment to faith or culture, or simply aging out of crime.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".