Bibliographic record
Abstract
This article analyses the diary entries made by a Persographic secretary (munshī), Aḥmad ʿAlī, who was employed by a retiring East India Company official to write an account of the journey they made together in 1780 across North India from Lucknow to the Mughal imperial capital in Delhi and back. Much of the landscape that they traversed—including a cluster of qasbahs, river passes, forests and fields—was formerly governed by a confederacy of Rohilla Afghans from 1737 to 1774. By 1780, however, this region was marked by the absence of well-defined, enduring state structures and witnessed an abundance of overlapping political claims. Under such conditions, Aḥmad ʿAlī, a novice secretary from this region who lacked access to major scholarly networks or courtly circles, found himself uniquely placed to observe and document the micro-level political and historical changes that he had lived through. Unlike his courtly counterparts, he witnessed transformations at a remove from both imperial politics and the regional courts that had developed through the eighteenth century. Rather than to a state or a single political project, his locus of service was aligned with the world of independent military entrepreneurs and their households, which were strewn across a region that he knew well. Questioning the view that secretaries were primarily cyphers of courtly culture or bureaucratic imperatives, the following pages demonstrate that while Aḥmad ʿAlī served his individual employer, he could imagine politics and history outside the constraints that came with corporate political affiliations, as a figure who was new to the work of secretarial penmanship and a seasoned bearer of textured regional knowledge.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.019 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".