Bibliographic record
Abstract
“There is a white boy by the barracks waiting under a tree who is not a white boy.” Rudyard Kipling, Kim (1901) In 1901, Rudyard Kipling published one of the more famous and widely discussed imperialist texts of the late Victorian period: Kim . The title character is a child who is devoted to a Tibetan lama and reluctant to attend an English-run school, but is happy to spy for the British Raj. He is, moreover, uniquely fitted to act as a spy in India because he has been raised in India among Indians, rather than in British enclaves, and so can “pass” as Indian. But Kipling's Kim , as I would like to argue here by way of concluding my larger study, is the product not only of the Indian Mutiny of 1857–1858 and the consolidation of British power in Victorian India, but also of the cultural threads that I have been tracing which both align and carefully distinguish between Ireland and India as colonized spaces. Kim is Irish – in many regards a “wild Irish boy” because uneducated and largely unparented – and the specifics of Kipling's representation of Kim seek to detach useful Irish characteristics from the Irish context in order to put them to work in the Indian context. While postcolonial readings have generally conflated Kim with the British and, more recently, represented him as a figure of whiteness, Kipling specifies Kim's Irishness and on terms that necessarily complicate his alignment with imperial hegemony.
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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 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.058 | 0.021 |
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".