Prison and its Afterlives: Haunting and the Emotional Geographies of Formerly Incarcerated People’s Reintegration Experiences in Kingston, Ontario, Canada
Bibliographic record
Abstract
Kingston is undeniably a prison town. As the venue for Canada’s first prison and current home to nearly twenty percent of the nation’s federally incarcerated people in seven penitentiaries around the city, prisons undoubtedly influence the economic, political, and social life of Kingston. While Kingston’s identity as a prison town is touted by the local municipality as beneficial for the community, people who have been incarcerated and released into Kingston have a different story to tell. Reintegration – the process of leaving prison and re-entering the community – is inevitable for the majority of incarcerated people in Canada. However, people who are released from prison into Kingston have reported significant difficulties maintaining lasting or successful reintegration despite the overwhelming presence of local prisons, their supporting administration, and an extensive network of non-profit and charitable service providers. Reintegration into the community is not only a physically exhausting experience, but one that is emotionally fraught with feelings of anticipation, uncertainty, fear, anger, and boredom. Based on twenty-three interviews with formerly incarcerated people in Kingston, I argue that attending to the emotional geographies of reintegration in Kingston, where people both struggle with and resist violent reintegration discourses of risk and responsibility, is critical to developing a more equitable reintegration praxis. I contend that understanding how people with prison experiences feel in the community not only brings the ethics of current reintegration practices into question; it also reveals how neoliberal discourses of risk and responsibility extend beyond the walls of the prison, prolonging the haunting effects of the settler-colonial carceral state in the everyday lives of formerly incarcerated people.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.035 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".