Rajbir Singh Judge. <i>Prophetic Maharaja: Loss, Sovereignty, and the Sikh Tradition in Colonial South Asia</i>
Bibliographic record
Abstract
Prophetic Maharaja: Loss, Sovereignty, and the Sikh Tradition in Colonial South Asia by Rajbir Singh Judge revisits the efforts of Duleep Singh, the youngest son of Ranjit Singh (d. 1839), the ruler of the Greater Punjab State centered in Lahore, to return to Punjab and reclaim his inheritance in the 1880s. Utilizing psychoanalysis as a core analytic, the author tells us that there is “no ‘real’ Duleep Singh nor an authentic story to tell” (2); Singh instead should be seen “as a struggle to constitute meaning” (138).The author’s aim, then, is not to recover the history of Duleep Singh, but to understand how the idea of Singh circulated in late nineteenth-century Punjab, and the British empire more broadly, among Punjabis and colonial officials alike. The book thus highlights the unknowability of the colonial subject, which “oscillated between contradictory interpellations” (89). Still, it is not entirely clear how different the author’s approach to Duleep Singh is from already existing explorations of the multiple and contested views of this figure, such as Tony Ballantyne’s, despite the author’s disregard for it (and for history as a field). Frequent declarations of ambiguity, instability, contingency, and a “contested and discrepant tradition” may not be sufficient to differentiate this approach (120).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".