"New Russian" Sightings and the Question of Social Difference in St. Petersburg
Bibliographic record
Abstract
They have money, so they think they can do anything they want."So commented a St. Petersburg art teacher in the fall of 1998.That day, I was talking with a group of his colleagues about what they thought of the New Russians: the nouveaux riches of the 1990s, dubbed "New Russians" in the Russian media and in the popular imagination.New Russians were characterized by money and stupidity, one teacher had said, while yet another colleague said that they were involved in "speculation," which had been illegal under socialism and has since become legal."They have their own fashions.We laugh at them all -they aren't worth envying," one of them went on, as listening teachers murmured their agreement.New Russians aren't simply wealthy, someone clarified, for wealthy, smart businessmen do exist.Rather, the New Russians are people who are "limited:" security guards (oxrana), for instance, and people who wear not black jackets, but green or raspberry-colored ones.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.021 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 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".