Realigning individual behavior with societal values: The role of planning in injunctive‐norm interventions aimed at increasing voter turnout
Bibliographic record
Abstract
Abstract Voting is highly valued in democratic societies. However, in recent years there has been a marked decline in voting. To realign voting behavior with democratic values, we turn to the study of injunctive‐norm interventions. These interventions advance that by making injunctive norms, the norms representing collective values, salient to a targeted group of individuals, individuals will likely conform to the promoted norm. However, studies testing the effectiveness of injunctive‐norm interventions have produced mixed results. We hypothesize that individuals with few plans to vote are those who will be most influenced by these interventions. Individuals with few plans should be more receptive to normative influence because they do not have preconceived commitments about how to engage with voting. Study 1 (N = 141) shows that injunctive‐norm interventions influence the voting behavior of those with few plans about voting. Studies 2 (N = 152) and 3 (N = 195) bring forth evidence that this influence is also present when the salient injunctive norms are from close meaningful groups, such as family and friends.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".