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Record W3155238543 · doi:10.1177/26326663211005250

Prison gangs in Iran: Between violence and safety

2021· article· en· W3155238543 on OpenAlexaff
Nahid Rahimipour Anaraki

Bibliographic record

VenueIncarceration · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPrisonCriminologyInterviewSnowball samplingExtortionIdentity (music)Qualitative researchSociologyFieldnotesSymbolic interactionismPsychologySocial psychologyPolitical scienceLawMedicineSocial scienceEthnography

Abstract

fetched live from OpenAlex

This article aims to bridge the gap in our knowledge about Iranian prisons and the sociodynamic relations that animate them by illuminating the characteristics and activities of prison gangs in Iran. The interaction between gang affiliation and drug networks, security and violence will be discussed in detail. The in-depth qualitative research, which is informed by grounded theory, serves as the first academic study of gangs in Iranian prisons. Research participants included 38 males and 52 females aged 10–65 years. They were recruited in several different settings, both governmental and non-governmental organizations. The study employed theoretical sampling and in-depth, semi-structured interviewing. Results show that gang-affiliated inmates in Iranian prisons gain monopoly over the drugs market inside prison networks, which leads to inevitable extortion of both prisoners and correctional officers. Gang affiliation blurs the lines between violence and safety, while providing a sense of identity, belonging and financial and emotional support. Prison gang membership also offers some benefits to prisoners and staff, as their existence underpins an informal social order that can be used to govern prisoners. The article discusses this less well-known and unexplored dimension of the topic.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.321
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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