Bibliographic record
Abstract
With Pushkin's narrative poem Prisoner of the Caucasus (1822), Circassians entered the Russian imperial imaginary as exemplary personifications of the savagery and freedom of the Caucasus as a whole (Layton 1994; 1997; Grant 2005; 2007). Accordingly, the Russian imagination of Circassian polity, now as egalitarian “free societies,” now as hierarchical aristocracies, now as “noble savages,” now as ignoble brutes, Muslim “fanatics,” or “Asiatic despots,” was a microcosm of the Russian colonial engagement with the Caucasus as a whole, often as not reflecting tensions in the self-perception of imperial autocracy and its elites more than indigenous political organization of Caucasian groups like Circassians in reality (Layton 1997; Jersild 2002; Grant 2005). Inasmuch as such imperial imaginings informed the fantasies of young men, causing them to enlist in search of the poetry of warfare, or informed fantasies of conquest among agents of the Russian state, these imaginings became real in their consequences for various Caucasian groups (Layton 1994; 1997). Nor was the exemplary alterity accorded Circassians limited to Russian audiences; it exerted a considerable fascination across Europe as well (King 2007: 241–45).
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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 | 0.013 | 0.040 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".