Cross-national interaction and cultural similarity: A relational analysis
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
The study examines the relationship between the structure of cross-national relations and the dyadic cultural similarity of 19 countries over 10 years, based on the assumption that patterns of interaction between state, private sector, and civil society actors influence national cultures. The relations analyzed include trade, military alliances, IGO memberships, phone calls, and military conflicts. The findings demonstrate that cross-national interactions, particularly trade and IGO memberships, are strong predictors of cultural similarity that complement the modernizing effects of economic development. In addition to explaining variation in cultural similarity between country dyads, the study challenges primordialist approaches to comparative cultural research that rely on civilizational country classifications. Instead, systematic measures of religious tradition, geographic region, linguistic heritage, and imperial history are used to identify factors that shape countries’ dyadic cultural similarities. Of these, only membership in former empires is a significant predictor of cultural similarity.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it