Complementarities in Organizational Dispute Resolution Systems: How System Characteristics Affect Individuals' Conflict Experiences
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
In 1999–2000, a Canadian national government agency pilot-tested different employment dispute resolution systems (DRSs). The author analyzes how DRS characteristics in this natural quasi-experiment affected employees' approaches to conflict management, their attitudes toward conflict at work, and their rate of success in resolving conflict. A system that added negotiation training to a rights-based grievance procedure, she finds, was actually associated with worse conflict-related problems than a system consisting solely of a rights-based grievance procedure. In contrast, the joint use of a rights-based grievance procedure, negotiation training, and an interest-based neutral generated greatly improved outcomes. The author attributes the superior performance of a three-component DRS to complementarities among the components.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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