The Relationship between Background Variables and Sex-Typing of Gender Roles and Children’s Chores: The Israeli Case
Bibliographic record
Abstract
The article examines the relationship between sex-typing of adult gender roles and children’s chores in Israeli society. Adult gender roles were examined from a general perspective, while children’s chores were examined in five distinctive areas - domestic chores, help with siblings, self-care, outside, and technical chores. The research sample consisted of 238 married and unmarried participants (81 men and 157 women). Specifically, sex-typing of adult gender roles and children’s chores was examined in relation to three sets of background variables: (1) personal background variables (age, religiosity, and ethnicity); (2) education and employment variables (level of education, extent of job position, and earning patterns); and (3) family variables (marital status, length of marriage, number of children, and age of children). The women tended to have less sex-typed attitudes than the men did with regard to children’s chores. However, no differences were found between the genders with regard to sex-typing of adult gender roles. In addition, the married women expressed more sex-typed attitudes toward adult gender roles than did unmarried women, whereas the differences between married and unmarried men were less significant. Among both genders, a correlation was found between sex-typing of adult gender roles and domestic children’s chores.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".