The <i>mohol</i> : The hidden power structure of Bangladesh local politics
Bibliographic record
Abstract
It is a common view that power in Bangladesh is exercised through patron–client forms of exchange. These patron–client relationships are held together by moral proximity and intimacy and are diffused and multidimensional. Most recently, Basu et al. (2018, Politics and Governance in Bangladesh: Uncertain Landscapes, 1–16. London: Routledge) argue for the persuasive presence of patron–client relationships and its role as the informal, ‘real’ structure as opposed to the formal state structure. The portrait, however, leaves us with the image of a vast undifferentiated web where the only node is the one at the centre. This article seeks to temper this portrait by arguing that at a certain point the web is no longer undifferentiated. It has locally real, tangible nodes of substantial power—often referred to as mohol (quarter) in Bangla. These nodes of power are often albeit not invariably centred on the local MP. The existence of these nodes indicates a decentralised power structure, wherein power is located in numerable nodes across the country rather than centralised in Dhaka.
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 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 | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".