In the eye of the beholder: Meaning and structure of informal status in women's and men's prisons*
Bibliographic record
Abstract
Abstract Applying an abductive mixed‐methods approach, we investigate the informal status systems in three women's prison units (across two prisons) and one men's prison unit. Qualitative analyses suggest “old head” narratives—where age, time in prison, sociability, and prison wisdom confer unit status—are prevalent across all four contexts. Perceptions of maternal “caregivers” and manipulative “bullies,” however, are found only in the three women's units. The qualitative findings inform formal network analyses by differentiating “positive,” “neutral,” and “negative” status nominations, with “negative” ties primarily absent from the men's unit. Within the women's units, network analyses find that high‐status women are likely to receive both positive and negative peer nominations, such that evaluations depend on who is doing the evaluating. Comparing the women's and men's networks, the correlates of positive and neutral ties are generally the same and center on covariates of age, getting along with others, race, and religion. Overall, the study points to important similarities and differences in status across the gendered prison contexts, while demonstrating how a sequential mixed‐methods design can illuminate both the meaning and the structure of prison informal organization.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".