The lone dissenter as a non-conformist in the Supreme Court: Extension of past research, cross-cultural analysis and influence model development
Bibliographic record
Abstract
Social influence is a potent force in small groups’ decision-making. Asch conducted his foundational lines study demonstrating conformity in such a setting and the difficulty in being a minority of one. His work has been used to assess conformity outside of the lab but may lack applicability to real-world situations. The current study replicates and extends earlier work by analyzing US Supreme Court (SC) jurisprudence (1945 – 2023) and includes Canadian SC voting trends (1953-2023) to investigate conformity cross-culturally. Consistent with past work, we identified unanimous outcomes (9-0) were most prevalent and a lone dissenter (8-1) least in both samples. However, unanimous outcomes were considerably more likely in Canada than in the US. The results are explained based on situational and psychological factors and used to develop a model to examine lone dissenters in small group decision-making. We highlight how the Asch paradigm is not a suitable prism to study SC adjudications and use the new model to suggest future directions for a more robust exploration of social influence in small group decision-making processes.
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".