Commentary on “Redefining Interactions Across Cultures and Organizations”
Bibliographic record
Abstract
The authors make two basic points in their commentary, both stemming from the field of cross-cultural psychology. First, in their view, intelligence is a concept that is highly variable across cultures; its meaning, development, display, and assessment are all embedded in cultural contexts. Thus, they consider that a single concept such as cultural intelligence (CQ) is unlikely to be culturally appropriate in all sociocultural settings. Second, when groups and individuals of different cultural backgrounds come into contact, the process of acculturation is set in motion. In this situation, two differing meanings of intelligence are likely to engage each other, bringing some challenges to the intercultural interaction, often resulting in stress, and sometimes in conflict. Eventually, some forms of adaptation are achieved, with the emergence of some effective ways of acting in the intercultural situation. The authors believe that these two points need attention during the further development of the concept of CQ.
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.
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 | 0.012 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.067 | 0.076 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".