Revisiting the comparative outcomes of workplace aggression and sexual harassment.
Bibliographic record
Abstract
We focus on the differential outcomes associated with experiencing workplace aggression and sexual harassment by a supervisor. To do so, we identify and empirically address several issues within current workplace aggression and sexual harassment research, including the need to (a) conceptualize their multidimensional nature, (b) contrast comparable dimensions between the two, (c) recognize and control for covictimization, and (d) consider the role of target gender. Data were analyzed using multiple regression and dominance analyses on a sample of 467 employed women (M age = 40 years). Results showed that all forms of sexual harassment were more strongly associated with work withdrawal and psychological well-being than comparable forms of workplace aggression. Nonphysical workplace aggression accounted for more of the variance in attitudinal outcomes (job, coworker and supervisor satisfaction, intent to quit, commitment) than nonphysical sexual harassment. Sexual harassment accounted for more of the variance than workplace aggression in all outcomes when the harassment and aggression involved some form of threatened or actual physical contact. Conceptual and methodological issues are discussed.
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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 | 0.010 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".