DOMESTIC CONFLICTS IN THE FRENCH QUARTER OF SAINT PETERSBURG UNDER PETER THE FIRST
Bibliographic record
Abstract
The article deals with domestic conflicts in the French Quarter of Saint Petersburg under Peter the Great, namely: quarrels, brawls, showdowns with insults that arose among foreign artists and artisans who inhabited the settlement. The theoretical foundation of the research is such classical tools of sociology and cultural anthropology, as the concept of “Social fields” and the theory of “Social construction”. Based on archival sources and many published materials, the author solves questions about the causes of conflicts, the conditions of their occurrence, and the differences between domestic quarrels among the French and similar incidents common among Russian citizens. The author found out that in disputes, French masters primarily defended their personal dignity, translating Western European ideas of honor. Their high self-esteem inevitably led to conflicts, which usually occurred in the process of jointly spending leisure time. The article reveals that the French craftsmen not only sworn, but also used irony, which was almost unknown in Russia as an implement of social competition. It is clear that the most important factor in aggressive behavior was the contradictions between the ambitions of the masters, their social expectations, on the one hand, and the social reality of Petersburg, as the French imagined it, on the other.
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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 | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".