Personality: The Universal and the Culturally Specific
Bibliographic record
Abstract
There appears to be a universal desire to understand individual differences. This common desire exhibits both universal and culturally specific features. Motivations to view oneself positively differ substantially across cultural contexts, as do a number of other variables that covary with this motivation (i.e., approach-avoidance motivations, internal-external frames of reference, independent-interdependent views of self, incremental-entity theories of abilities, dialectical self-views, and relational mobility). The structure of personality traits, particularly the five-factor model of personality, emerges quite consistently across cultures, with some key variations noted when the structure is drawn from indigenous traits in other languages. The extent to which each of the Big 5 traits is endorsed in each culture varies considerably, although we note some methodological challenges with comparing personality traits across cultures. Finally, although people everywhere can conceive of each other in terms of personality traits, people in collectivistic cultures appear to rely on traits to a lesser degree when understanding themselves and others, compared with those from individualistic cultures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".