DEVIANTNESS IN FAMILY RELATIONSHIPS IN THE CONTEXT OF EVERYDAY HISTORY (ON THE MATERIALS OF KYIV PROVINCIAL NEWSPAPERS OF THE LAST QUARTER OF THE 19 TH – EARLY 20 TH CENTURIES)
Bibliographic record
Abstract
The article deals with the systematization of information about the negative types of deviant behavior in the families of the Uman district being one of the largest among the twelve districts of the Kyiv province in terms of the area size and population density given in Kyiv newspapers: «Zarja», «Kievskoe slovo», «Kievljanin». 16 announcements about the cruel treatment of family members to each other, beatings, violence in families were published in the mentioned newspapers from 1883 to 1912. The tonality of newspaper publications gave ground to conclude that such manifestations of deviant behavior were parts of everyday life and they were reported as common trivial occurrences. It breaks the stereotypes about the patriarchal nature of families, the religiosity of the population and the adherence to Christian commandments, enlarges the idea of public morality. Taking into consideration the fact that the family is the center of society, family relationships to a certain extent characterize social relations in general. On the basis of systematized information we made the conclusion that the published announcements about deviations in families in the newspaper columns were one of the manifestations of state intervention in personal life and interpersonal relationships. On the other hand, the dissemination of information by newspapers about violence, murders and drunkenness as the cause of illegal acts is aimed at forming public opinion regarding the condemnation of negative types of deviant behavior. In spite of the absence of evaluations concerning the outlined news in publications, the expediency of information dissemination about cruelty and violence may be elucidated by the necessity for drawing attention to such aspects of social existence. The material represented in the article supplements the idea of everyday life, family relationships, levels of well-being and material provision of the rural population. A microhistorical approach made it possible to provide details within the covered theme contributing to the accumulation of empirical material in local history and the history of everyday life.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".