Different Pasts for Different Political Folk: Political Orientation Predicts Collective Nostalgia Content
Bibliographic record
Abstract
Collective nostalgia is a bittersweet emotion that reflects sentimental longing for valued aspects of the past of one’s group. Given that conservatism is typically associated with a general desire to preserve the societal status quo or return society to its traditional way of being, nostalgia has been theorized to be characteristic of those on the political right (i.e., conservatives). In the current work, we proposed and tested the hypothesis that collective nostalgia is experienced by both conservatives and liberals, but the content of their nostalgizing differs. Across three studies in three socio-political contexts—United States (Study 1, MTurk, N = 352), Canada (Study 2, student sample, N = 154), and England (Study 3, online panel, N = 2,345)—we found that both conservatives and liberals experienced collective nostalgia for a more homogenous and open society. However, conservatives experienced more homogeneity-focused collective nostalgia, whereas liberals experienced more openness-focused collective nostalgia. Replicating previous findings, homogeneity-focused nostalgia emerged as a positive, whereas openness-focused nostalgia emerged as a negative, predictor of intergroup attitudes. The results have both theoretical and practical significance for understanding political attitudes and behaviors. To the point, variance in the conservative and liberal political agendas is, in part, a function of a difference in their respective predisposition to nostalgize about and thus desire the return of a particular aspect of the in-group’s past.
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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 | 0.001 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".