Volumes, Forms and Functions of Grandparental Labor: Estimates of Ural Parents
Bibliographic record
Abstract
The purpose of the article is to study the volumes, forms, content, specific subjects of grandparental labor, to assess the determinants of the frequency of implementation of this type of labor. We used the data of a sociological survey conducted in May-June 2021. Residents of the Sverdlovsk region who have both minor children and their parents and(or) their spouse’s parents living at the same time were interviewed. The main results are as follows: 1) every fifth parent surveyed uses the help of grandparents on an almost daily basis; the same number-on weekends. In a little more than a quarter of cases, there is no grandparental assistance to families; 2) raising grandchildren is the most common form of assistance to a family with children from the older generation; 3) parents on the part of the child’s mother often perform the functions of grandparental labor than parents on the part of the child’s father; 4) most often, grandparents perform a communicative function; then follows the introduction to work, then accompanying children to various educational institutions, organizing leisure activities, attending cultural events, etc.; 5) in the group of parents who are not helped by grandparents, the average number of children is higher; 6) more intense desire to increase the amount of assistance from the grandparents is expressed by those parents who are currently less often helped by grandparents. The results obtained can be used in the development of tools aimed at activating grandparental labor in Russia, as well as mechanisms for stimulating it.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".