Relational conflicts during COVID-19: Impact of loss and reduction of employment due to prevention measures and the influence of sex and stress (in the iCARE study)
Bibliographic record
Abstract
This study explored the association between pandemic-related loss/reduction of employment, sex, COVID-19-related stress and relational conflicts. A sample of 5103 Canadians from the iCARE study were recruited through an online polling firm between October 29, 2020, and March 23, 2021. Logistic regressions revealed that participants with loss/reduction of employment were 3.6 times more likely to report increased relational conflicts compared to those with stable employment (OR = 3.60; 95% CIs = 3.03–4.26). There was a significant interaction between employment status and sex ( x 2 = 10.16; p < 0.005), where loss/reduction of employment was associated with more relational conflicts in males compared to females. There was a main effect of COVID-19-related stress levels on relational conflicts (increased stress vs no stress : OR = 9.54; 95% CIs = 6.70–13.60), but no interaction with loss/reduction of employment ( x 2 = 0.46, p = 0.50).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".