Marital Decline in the Asian North of Russia and Generational Transition of Family Values
Bibliographic record
Abstract
The article discusses some questions of marital behavior of the population in the Asian North of the Russian Federation with the Republic of Sakha (Yakutia) as an example. This region is scarcely populated, yet it is the largest in the country by the occupied territory. The analysis of marital behavior revealed that on the background of some decrease in the number of marriages in the 1990s and marriage market decline, the number of divorces was growing. The attitude of the population towards the main circumstances of organizing one’s private life in a marriage is shown on the materials of a sociological and demographic survey. The authors reveal the differences in the views of representatives of different generations on marriage, its forms, marriage union basic principles, causes of conflicts in a marriage and divorces. Regardless of the marital status or presence of children, there is general agreement between the respondents that a conflict situation in a marriage is caused by a complex of reasons, the impact of which, in many cases, takes the form of a chain reaction. One central problem gives birth to a chain of discord that eventually shows the vulnerability of existing relations. The authors conclude that emergence and impact of conflictogenic factors on marital stability are the result of change of the place of marriage in the hierarchy of an individual’s life values in terms of modernization of demographic behavior as a whole.
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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 | 0.001 | 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) | 0.002 | 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".