Bibliographic record
Abstract
Abstract Prison radicalization poses a significant and evolving threat in Bangladesh's correctional facilities. This research article delves into the conditions fostering radicalization, including corruption, overcrowding, violence, and the lack of essential amenities. Drawing on extensive analysis of secondary data and expert interviews, this article argues that these conducive conditions have transformed Bangladeshi prisons into breeding grounds for radical ideologies, allowing militants to establish networks and plan attacks within and beyond prison confines. This article also points out the transformation of prisoners, even those with minimal radical tendencies, into militant leaders, along with the shift of non‐radical individuals toward extremism. Moreover, it underscores the lack of de‐radicalization programs within the current prison system as a crucial gap in countering this escalating issue. Furthermore, the research identifies societal denial, limited post‐release opportunities, and mistreatment by security forces as factors exacerbating radicalization post‐incarceration. As such, this study emphasizes the urgent need for comprehensive strategies to address prison radicalization. Related Articles Awan, Imran. 2012. “‘I Am a Muslim Not an Extremist’: How the Prevent Strategy Has Constructed a ‘Suspect’ Community.” Politics & Policy 40(6): 1158–85. https://doi.org/10.1111/j.1747‐1346.2012.00397.x . Heinmiller, B. Timothy, Matthew A. Hennigar, and Sandra Kopec. 2017. “Degenerative Politics and Youth Criminal Justice Policy in Canada.” Politics & Policy 45(3): 406–31. https://doi.org/10.1111/polp.12204 . Spalek, Basia. 2010. “Community Policing, Trust, and Muslim Communities in Relation to ‘New Terrorism.’” Politics & Policy 38(4): 789–815. https://doi.org/10.1111/j.1747‐1346.2010.00258.x .
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".