Research in carceral contexts: confronting access barriers and engaging former prisoners
Bibliographic record
Abstract
Prison systems, with the ability to reject or approve applications for conducting research with incarcerated populations, function as shapers of carceral knowledge and thus can potentially close opportunities for new qualitative studies as well as affect the quality and richness of the data obtained. This article describes a collaborative research process wherein access to current prisoners was not granted, and only former prisoners who were not on parole were eligible to participate in the study. We provide a unique reflective analysis of how access barriers altered the scope of our research and may have impacted our findings were it not for a change in our recruitment plan. We also incorporate insights from multiple literatures that speak to the value, challenges, and ethical concerns associated with doing research with former prisoners. Our contribution to the qualitative carceral literature sparks new questions worthy of further in-depth exploration, in particular how to more meaningfully involve former prisoners in the research process.
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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 | 0.043 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.031 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 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".