Bibliographic record
Abstract
In 1765, the Mughal emperor granted the East India Company the <italic>diwani</italic> of Bengal, Bihar, and Orissa. The Company thus acquired the right and obligation to collect taxes and administer civil justice for some thirty million people. Politicians and commentators disagreed about whether to extend English law to the Company’s new subjects. On one side, populists urged Britain to transplant English institutions in order to transform northeastern India into a neo-American plantation colony. On the other side, paternalists insisted on using legal pluralism to facilitate a more authoritarian and extractive form of colonialism. At a broad level, this was similar to the debate over legal pluralism in Quebec. In Bengal, however, the anti-pluralist argument lost ground more quickly. Although some politicians continued to urge anglicization, the primary debate after the 1770s was about what kind of legal pluralism Britain ought to support, not whether to have pluralism at all.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".