Bibliographic record
Abstract
The relevance of the study of the living conditions of rural women is related to the actual demographic situation in the Russian hinterland. In rural areas of the Russian Federation there is a stable decline in the population due, first of all, to natural population decrease, as well as migration outflow connected with low standards and quality of life, unattractiveness of labor in rural areas, and social infrastructure. Rural women as a socio-demographic group with typical socio-psychological, ideological, moral and ethno-cultural characteristics, similar spiritual values, social experience and lifestyles, being a more numerous part of the population of rural territories, act as a kind of bulwark for preservation of the village, its culture, traditions and rural economy as a whole. A quarter of all Russian women live in rural areas. Distribution of the country’s population by gender and age groups as of January 1, 2019 shows that women predominate in the rural population (52%). And the group of women over working age is twice as large as that of men (6775 thousand against 3230 thousand). In other words, Russian village has actually a female face. In this regard, the study of rural women’s issues is very important and timely. The article shows the role of women in the social development of the village, provides excerpts from interviews of rural female activists, their reasoning about how they live despite the difficulties that surround them. It highlights demographic trends in rural areas, assesses the quality of the labor potential of rural residents in comparison with urban residents, and shows a higher level of self-realization in labor activity among women than among men.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".