Bibliographic record
Abstract
This article attempts to delineate what it means to be Shia in relation to home-making in Sunni-majority Bangladeshi society. Unlike longer established Shias, those primarily settled in Old Dhaka and who are integrated into Dhakaiya culture and linguistic traditions, the post-Partition Urdu-speaking Shia migrants within the “Bihari” fold, a pejorative term used by Sunni-majority Bengalis, continue to seek to root home-making in Bangladeshi society. Both groups, however, have repeated a common practice in making home to bridge geographical and historical distance from a culturally significant center by reproducing it in the new location. Yet, despite the clear connections with Iran, it is the post-Partition migrants who find themselves negatively represented as collaborators with West Pakistan (now Pakistan) and this hinders the integration of this group into their new home. The article demonstrates that home is never produced in isolation of wider geopolitical, spatial, and historical factors.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".