Islam in Iranian Prisons: Practicing Religious Rituals behind Bars
Bibliographic record
Abstract
The focus of research, pertaining to the practice of Islam in prisons, has been primarily on Western countries (the US, the UK, and France) where Muslim inmates struggle with discrimination and stigmatization as “religious radicals” or “terrorists”. Far less is known about the relationship Muslim prisoners have with their faith in countries where Islam is the official religion and imposed by the State, such as the Islamic Republic of Iran. Understanding the influence of political, legal, and religious institutions is crucial to exploring Islam in Iranian prisons, as well as the role of other less prominent determining factors. This qualitative study examines the practice and perception of Islam in Iranian prisons. Data were collected through 90 in-depth, semi-structured interviews with prisoners and former prisoners, and analyzed using grounded theory. Results show that practicing Islam rituals and converting from a “sinner” to a “believer” was pervasive among inmates on death row and incarcerated mothers who left their children for a life of confinement. Practicing Islamic rituals, which entail the achievement of privileges, especially memorizing the holy Quran or attending congregational prayers, question the authenticity of faith and religious beliefs in prison; prisoners disparage those who practice rituals as “fake believers” who are merely seeking preferential treatment. While practicing Islam rituals provoked hatred and humor among prisoners, attending the Ashura mourning ceremony and performing self-flagellation are respected and admired practices. Iranian prisoners create a subculture where Islam is not pivotal to constructing or reconstructing their identities, yet religious-based rehabilitation still exists.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".