LET'S TAKE THIS OFFLINE: A THEMATIC ANALYSIS OF VIRTUAL CONFLICT IN HYBRID COLLABORATIVE DESIGN TEAMS
Bibliographic record
Abstract
Abstract Conflict can be both a productive and detrimental reality of design collaboration. While most studies on conflict characterize findings by type (conflict about the task, process, or interpersonal relationships), we extend this typology to understand the causes, topics, and outcomes of conflict. To do so, we analyze communications in a virtual chat platform, collected in a hybrid work environment. A thematic analysis on over 6000 messages between student design teams on the enterprise communication platform Slack revealed three emergent conflict themes: Engineering Design, Project Management, and Communication. A mapping of the themes to a widely-cited typology of conflict found an over- representation of task (productive) and process (detrimental) conflict in the Engineering Design and Project Management themes, respectively. The distribution of types of conflict in the Communication theme is representative of the entire dataset, suggesting that communication can be a cause and outcome in all types of conflict. Overall, our classification of conflict is the first step towards describing triads of the causes, topics, and outcomes of conflict, a contribution which will drive the development of interventions for design team conflict.
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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 | 0.021 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".