Do needs for security and certainty predict cultural and economic conservatism? A cross-national analysis.
Bibliographic record
Abstract
We examine whether individual differences in needs for security and certainty predict conservative (vs. liberal) position on both cultural and economic political issues and whether these effects are conditional on nation-level characteristics and individual-level political engagement. Analyses with cross-national data from 51 nations reveal that valuing conformity, security, and tradition over self-direction and stimulation (a) predicts ideological self-placement on the political right, but only among people high in political engagement and within relatively developed nations, ideologically constrained nations, and non-Eastern European nations, (b) reliably predicts right-wing cultural attitudes and does so more strongly within developed and ideologically constrained nations, and (c) on average predicts left-wing economic attitudes but does so more weakly among people high in political engagement, within ideologically constrained nations, and within non-Eastern European nations. These findings challenge the prevailing view that needs for security and certainty organically yield a broad right-wing ideology and that exposure to political discourse better equips people to select the broad ideology that is most need satisfying. Rather, these findings suggest that needs for security and certainty generally yield culturally conservative but economically left-wing preferences and that exposure to political discourse generally weakens the latter relation. We consider implications for the interactive influence of personality characteristics and social context on political attitudes and discuss the importance of assessing multiple attitude domains, assessing political engagement, and considering national characteristics when studying the psychological origins of political attitudes.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".