Bibliographic record
Abstract
The “cost-of-caring” thesis asserts that observed gender differences in psychological distress are largely a consequence of women’s greater emotional investment in the lives of their loved ones. Research on this topic has supported this thesis by showing that network events result in higher levels of depressive symptoms for women compared to men. However, other evidence challenges this claim. In light of these divergent findings, this paper elaborates this topic in three ways. First, susceptibility to network events is assessed in terms of two dimensions of psychological distress, depressive symptomatology and problem drinking. Second, within-gender analyses are conducted to examine the possibility that masculine and feminine personality traits condition the relationship between network events and psychological distress. Finally, this paper assesses age variation in the cost of caring. Data collected from 1,393 respondents ages 18 to 55 who participated in a Toronto-based community study are employed to address these issues. Findings reveal that the cost of caring for others extends to women and men, and that gender orientation modifies the relationship between network events and psychological distress. These results underscore the need to critically assess the social factors that differentiate risk and well-being for men and women.
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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".