Preference for modernization is universal, but expected modernization trajectories are culturally diversified: A <scp>nine‐country</scp> study of folk theories of societal development
Bibliographic record
Abstract
Cultural sensitivity in societal development has been advocated for since at least the 1960s but has remained understudied. Our goal is to address this gap and to investigate folk theories of societal development. We aimed to identify both universal and culturally specific lay beliefs about what constitutes good societal development. We collected data from 2,684 participants from Japan, Hong Kong (China), Poland, Turkey, Brazil, France, Nigeria, the USA, and Canada. We measured preferences for 28 development aims. We used multidimensional scaling, analysis of variance, and pairwise comparisons to identify universal and country‐specific preferences. Our results demonstrate that what people understand as modernization is fairly universal across countries, but specific pathways of development and preferences towards these pathways tend to vary between countries. We distinguished three facets of modernization—foundational aims (e.g., trust, economic development), welfare aims (e.g., poverty eradication, education), and inclusive aims (e.g., openness, gender equality)—and incorporated them into a folk meta‐theory of modernization. In all nine countries, the three facets of modernization were preferred more than conventional aims (e.g., military, demographic growth). We propose a method of implementing our findings into a culturally sensitive modernization index.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".