The multilevel nomological net of team conflict profiles
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
Purpose This paper aims to offer an integrative conceptual theory of conflict and reports on the nomological net of team conflict profiles. Specifically, it integrates social self-preservation theory with information-processing theory to better understand the occurrence of team profiles involving task conflict, relationship conflict and process conflict. Design/methodology/approach The study collected data from 178 teams performing and engineering design tasks. The multilevel nomological net that was examined consisted of constructive controversy, psychological safety and team-task performance (team level), as well as perceptions of learning, burnout and peer ratings of performance (individual level). Findings Findings indicated mixed support for the associations between conflict profiles and the hypothesized nomological net. Research limitations/implications Future research should consider teams’ profiles of team conflict types rather than examining task, relationship and process conflict in isolation. Practical implications Teams can be classified into profiles of team conflict types with implications for team functioning and effectiveness. As a result, assessment and team launch should consider team conflict profiles. Originality/value The complexity perspective advanced here will allow research on conflict types to move forward beyond the extensive research examining conflict types in isolation rather than their interplay.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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