Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: This paper investigates sociodemographic and family structure factors that predict men's involvement (n = 773) in different gendered dimensions of filial caregiving: traditionally male, gender neutral, and traditionally female care. METHODS: The concepts that guide this research relate to family obligations or motivations to provide care, specifically, commitment to care, legitimate excuses, and caring by default. Data for this research come from the Work and Family Survey (1991-1993) conducted by the Work and Eldercare Research Group of CARNET: The Canadian Aging Research Network. RESULTS: Although such factors as geographic proximity and sibling network composition predict men's involvement independent of the type of task, the gendered nature of the task is important in how other factors, such as filial obligation, parental status, education, and income influence involvement in care. DISCUSSION: The findings suggest that, for traditionally male tasks, legitimate excuses or a commitment to care may play a more minor role in influencing men's involvement than is true for traditionally female tasks. Overall, this research demonstrates the importance of examining the gendered nature of the care tasks and highlights the value of the conceptual framework for explaining variations in men's filial care.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it