Suspended identity: statelessness, citizenship challenges and the impermanence of identity status faced by Pakistani Bengalis
Bibliographic record
Abstract
Approximately 3 million ethnic Bengalis reside in Pakistan, some of whom have been refused citizenship rights and continue to face social and cultural exclusion despite being in their third and fourth generations. Many came following the creation of Bangladesh (formerly East Pakistan) in 1971 under challenging circumstances. This paper examines the ongoing citizenship challenges faced by the Pakistani Bengali community in Karachi, Pakistan, with a particular focus on their experiences within the space of the citizenship registration office. Drawing on 85 oral history interviews with both adult and young Pakistani Bengalis, our findings reveal that the treatment of Pakistani Bengalis in this space is shaped by dominant racialised commonsense representations of them as ‘eternal outsiders’ and ‘unworthy of belonging’, rooted in a historical past marked by conflict and a series of exclusionary citizenship and state-security policies. Consequently, many are met with discrimination and challenges around identity acquisition, resulting in lasting intergenerational impacts in their own and their family’s everyday lives, leaving them precarious. Our paper more broadly argues that within the social imagination of nations, particularly post-colonial ones, certain groups are constructed as outsiders, shaping racialised understandings that influence discriminatory citizenship practices in turn creating a state of suspended identity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.020 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".