Diversity and Postmaterialism as Rival Perspectives in Accounting for Social Solidarity
Bibliographic record
Abstract
This article explores the empirical support for the two rival perspectives of diversity and postmaterialism, each of which predicts different patterns and trends of social solidarity in the Western world. The diversity perspective holds that ethnocultural heterogeneity undermines social solidarity, and consequently expects social solidarity to be weaker in more heterogeneous societies. In the diversity logic, social solidarity should have declined in Western societies as these societies have become more diverse due to continuous immigration. Postmaterialism theory, by contrast, posits a positive link between postmaterialism and social solidarity, and would expect social solidarity to have increased because of rising levels of postmaterialism across the Western world. This article found no relation between diversity and social solidarity at either the individual or the national level in cross-sectional analyses of WVS and EVS survey data. Neither was the diversity argument supported by trend data on opinions about the poor. The positive relations between postmaterialism and social solidarity on the other hand did confirm the postmaterialism perspective. Still, as postmaterialism contributed little to explaining the variance in social solidarity at the individual level and as there was no connection between postmaterialism and social solidarity at the macro-level, it can be questioned whether the solidaristic sentiments expressed by postmaterialists are sufficiently deep and lasting to underpin robust welfare policies.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".