The Emergence of Collective Cultural Intelligence in Teams in Multicultural Contexts: A Dynamic Perspective
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
What makes a team culturally intelligent is under-studied. To address the gap in the literature and enhance the understanding of the dynamic nature of teams in multicultural contexts, we introduce a novel concept – team-level collective cultural intelligence – to explain how teams develop a collective property that helps them deal with cultural diversity more effectively. Integrating the literature on cultural intelligence, multicultural teams, and emergent states, we propose that collective cultural intelligence arises from the cultural intelligence of individual team members through their interactions, which involves team learning. This emergent process is contingent on the cultural diversity and power disparity within the team, as well as the specific characteristics of team learning that occurs. Collective cultural intelligence enhances team performance in multicultural contexts and members’ individual cultural intelligence.
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 | 0.000 | 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