In Others’ Words: Quotations and Recontextualization in Putin’s Speeches
Bibliographic record
Abstract
This article analyzes how Kremlinologists have attempted to understand ‘what Putin thinks’ by examining whom he has quoted. Kremlinologists have taken the quotations in Putin’s speeches and used them to claim that Putin is ‘ultranationalist’, ‘paleoconservative’, and even ‘fascist’. The article argues that in doing so, they have ignored the exact words of the quotations and the context in which they were used. To overcome this deficiency, the article carries out a careful examination of those words and that context, and points to much more nuanced conclusions. It shows that on occasion, Putin has used quotations to reinforce what might be considered relatively illiberal points, but more often he done so to reinforce moderately liberal rhetoric. Overall, Putin’s use of quotations would suggest that Putin positions himself as a relatively moderate conservative not as an extremist of the sort claimed by the Kremlinologists.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".