Employment after incarceration: managing a socially stigmatized identity
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the social stigmatization of the formerly incarcerated identity and how this affects employment post-release. The authors consider the characteristics of this identity and the identity management strategies that individuals draw from as they navigate employment. Design/methodology/approach The authors conducted semi-structured interviews with 22 men at various stages of release from federal institutions in Canada. Participants were actively searching for employment, intending to or would consider searching for employment, or had searched for employment in the past post-incarceration. Participant data were simultaneously collected, coded and analyzed using an inductive approach (Gioia et al., 2012). Findings Formerly incarcerated individuals have a unique awareness of the social stigmatization associated with their criminal record and incarceration history. They are tasked with an intentional choice to disclose or conceal that identity throughout the employment process. Six identity management strategies emerged from their accounts: conditional disclosure, deflection, identity substitution, defying expectations, withdrawal and avoidance strategies. More specifically, distinct implications of criminal record and incarceration history on disclosure decisions were evident. Based on participants’ accounts of their reintegration experiences, four aspects that may inform disclosure decisions include: opportune timing, interpersonal dynamics, criminal history and work ethic. Originality/value The authors explore the formerly incarcerated identity as a socially stigmatized identity and consider how individuals manage this identity within the employment context. The authors identify incarceration history and criminal record as having distinct impacts on experiences of stigma and identity management strategic choice, thus representing the experience of a “double stigma”.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.018 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".