Prison food and the carceral experience: a systematic review
Bibliographic record
Abstract
PURPOSE: This study aims to focus on studies that qualitatively explore prison food experience. The goal is to elaborate a framework to better understand how prison food shapes the worldwide carceral experience. DESIGN/METHODOLOGY/APPROACH: This systematic literature review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. It consists of four phases: identifying the studies, screening the studies, evaluating the eligibility of screened studies and inclusion of studies. After the four phases, ten studies (nine qualitative studies and one with mixed methods) were included in the review. FINDINGS: There is a consensus among the researchers in the reviewed literature that prison food shapes the carceral experience. More specifically, four themes that encompass the experience of people with prison food emerged from the reviewed literature: food appreciation (taste of the prison food and perceived nutritional value), food logistics (preparation, distribution and consumption), food variety (institutional menu and commissary store) and food relationships (symbol of caring or power or punishment). ORIGINALITY/VALUE: The literature reviewed demonstrated that when incarcerated individuals have a negative view of prison food, the carceral experience is negatively impacted. This systematic review identified four dimensions that encompass the food experience within the prison environment, providing a framework for navigating this subject.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".