Can emotional differences be a strength? Affective diversity and managerial decision performance
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 – The purpose of this paper is to extend earlier findings suggesting that affective diversity is always negative for group performance, by examining its influence on managerial decision performance in a more controlled environment. Design/methodology/approach – In an attempt to mitigate some of the many methodological challenges associated with studies in “real-word” contexts, the authors chose to adopt a quasi-experimental research design involving teams of master of business administration students engaged in managerial decision making. This research design is consistent with previous research conducted in the area of affect and individual or group-level outcomes. Findings – The results indicate that both positive and negative affective diversity are positively associated with managerial decision performance, although only the relationship with negative affective diversity is significant. Overall, these findings support the idea that affective diversity may constitute a strength in the context of managerial decision making. These results contrast with the findings of previous studies. Research limitations/implications – Further quantitative and qualitative investigation is recommended in order to clarify the contradictory results between the current study and previous research. Specifically, this investigation might concern the effect of contingency factors such as type of team (i.e. ad hoc vs long term), type of task and team-level self-regulation ability. Originality/value – Since the seminal work of Barsade et al. (2000), no further studies have attempted to resolve some of the empirical questions emerging from preliminary research on affective diversity. The paper thus provides new insights into the effects of affective diversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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