Metanorms generate stable yet adaptable normative social order in a politically decentralized society
Bibliographic record
Abstract
Norms are essential for social stability but can hinder adaptability in changing environments. Yet human societies have found ways to modify existing norms or create new ones in response to novel challenges. This paper proposes a framework for understanding adaptive norm evolution. First, drawing on a theory of legal order, we posit that societies balance normative stability and adaptability through metanorms-rules that govern the process by which norms are interpreted, changed and enforced. Second, we test this idea in the context of customary dispute resolution by elders among the Turkana, a pastoralist society in Kenya. Based on vignette experiments with 369 participants, we found that community members were significantly more willing to enforce decisions when elders aligned their conduct with metanorms. Elders are constrained in their ability to alter long-standing customs, but by following metanorms, they can create new rules for novel situations. These findings support our proposed mechanism: in the absence of centralized authority, metanorms governing normative institutions allow for adaptive norm change while preserving cultural continuity. We conclude by suggesting that group-level selection acts on cultural variation in metanorms, shaping the evolvability of normative systems and enabling societies to sustain adaptive legal order without coercive centralized power. This article is part of the theme issue 'Transforming cultural evolution research and its application to global futures'.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 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".