William Arnold and Experimental Education in North India,1855-1859: An Innovative Model of State Schooling
Bibliographic record
Abstract
This article is about a progressive experiment concerning state-sponsored schooling that was carried out in north India in the early 1850s. It was on a large scale and, almost uniquely, aimed to engage the poor village boy by building a system designed to wean him onto a sympathetic curriculum that contained both Western and Eastern elements. Even though it was to eventually fail, William Arnold, who implemented the Indian experiment, aimed to avoid the pitfalls of the class-based, English education system by offering village boys the prospect of promotion across a unitary government curriculum that could eventually result in a college education. In this way he hoped to overcome the barriers of both race and class. Arnold’s government-run scheme predated William Forster’s Education Act of 1870 in England even though the precursors for the Indian experiment related to “orientalist” thought that had emerged on the subcontinent a generation earlier.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".