The Unbelieved and Historians, Part I: A Challenge
Bibliographic record
Abstract
Abstract In 1855, Thakur led a rebellion of the tribal Santals against the British in eastern India. Some historians refused to admit Thakur's involvement in the event because of a three‐century‐old prejudice against giving supernatural beings agency when we write history. In Provincializing Europe , Dipesh Chakrabarty argues that historians must “anthropologize” such beliefs rather than take them seriously. Taking a cue from their less‐than‐marginal place in scholarship today, we call supernatural beings the “Unbelieved” and the explicit or implicit denial of them “Dogmatic Secularism.” We argue that objective historians should not discount, in advance, evidence that points to the existence or involvement of the Unbelieved in history; instead, we should cultivate a sceptical attitude towards all sources. In this, the first half of a two‐part essay, we trace the boundaries of this epistemological problem in the scholarship about the Santal Rebellion and beyond.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.079 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".