J<scp>OHN</scp> F<scp>ISHER</scp>, <i>Curzon and British Imperialism in the MiddleEast, 1916–1919</i> (London and Portland, Ore.: Frank Cass, 1999). Pp. 358.
Bibliographic record
Abstract
It should be noted from the outset that for this reviewer, Curzon and British Imperialism proved to be a very difficult read. It falls within the category of pure diplomatic history—the kind that unfolds dispatch by dispatch, direct quotation by direct quotation; that contains an overwhelming number of endnotes (1,170 for 244 pages of text); and that is packed with sentences such as: “Neither the objection raised by Chamberlain, that this would contravene the Hague Convention, nor the possibility of upsetting the Russians, to which Robert Graham alluded, deterred Curzon who, noting the concurrence of Hardinge and McMahon, suggested that the views of the Government of India be sought on a change in Cox's status” (p. 58). The inclusion of so much undigested material tends to obscure any larger theme that John Fisher may be pursuing. And although he claims to admire Elie Kedourie, that scholar, whatever one may think of his views, was a master at synthesis and pointed argumentation. These qualities are mostly lacking in Fisher's work.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".