Theoretical and Empirical Advancements in Intimate Partner Aggression and Violence at Work
Bibliographic record
Abstract
Intimate partner aggression (IPA), a prevailing global health and social issue (United Nations [UN], 2020) have undeniable spillover effects at work. The criticality of examining how IPA affects work lives has become even more relevant given mounting reports of increased victimization in the current pandemic era. While empirical research on work-related IPA (WIPA) continues to accumulate, the application of theory in WIPA research has generally been limited. Advocating for more theory-driven scholarship, this symposium aims to present compelling works that applied a variety of theoretical perspectives in the study of WIPA. We offer three papers that applied strong theoretical perspectives (e.g., conservation of resources theory and work-home resources perspective, appraisal theory of emotions, and stigma theory) that enrich our understanding of WIPA. These studies also consist of both field and archival data collected in an extensive range of research designs (e.g., a cross-sectional nationally representative survey, longitudinal/time-lagged). Moreover, these studies were undertaken in different countries (e.g., USA and the Philippines) – welcoming the opportunity for discussion about cross-national differences in intimate partner aggression. These three papers set the stage for more theory-driven scholarship, thereby contributing to building a stronger body of scholarship on WIPA. Witnessing Interparental Violence and Leader Role Occupancy Presenter: Anika Cloutier; Rowe School of Business, Dalhousie U. Presenter: Julian Barling; Queen's U. Emotional Anguish at Home: Intimate Partner Aggression, Negative Emotional Reactions, & Work Outcome Presenter: Yaqing He; U. of Illinois at Urbana-Champaign Presenter: Simon Lloyd D. Restubog; U. of Illinois at Urbana-Champaign Suffering in Silence: Disclosure Dynamics of Intimate Partner Aggression and the Role of FSSB Presenter: Catherine Deen; RMIT U., Australia
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".