Cross-Cultural Dimensions of Meaning in the Evaluation of Events in World History?
Bibliographic record
Abstract
The universality versus culture specificity of quantitative evaluations (negative-positive) of 40 events in world history was addressed using World History Survey data collected from 5,800 university students in 30 countries/societies. Multidimensional scaling using generalized procrustean analysis indicated poor fit of data from the 30 countries to an overall mean configuration, indicating lack of universal agreement as to the associational meaning of events in world history. Hierarchical cluster analysis identified one Western and two non-Western country clusters for which adequate multidimensional fit was obtained after item deletions. A two-dimensional solution for the three country clusters was identified, where the primary dimension was historical calamities versus progress and a weak second dimension was modernity versus resistance to modernity. Factor analysis further reduced the item inventory to identify a single concept with structural equivalence across cultures, Historical Calamities, which included man-made and natural, intentional and unintentional, predominantly violent but also nonviolent calamities. Less robust factors were tentatively named as Historical Progress and Historical Resistance to Oppression. Historical Calamities and Historical Progress were at the individual level both significant and independent predictors of willingness to fight for one’s country in a hierarchical linear model that also identified significant country-level variation in these relationships. Consensus around calamity but disagreement as to what constitutes historical progress is discussed in relation to the political culture of nations and lay perceptions of history as catastrophe.
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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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 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".