Moral Hierarchy Framework

Evidence & Visualization Hub

Every claim in the paper has data behind it. These pages lay it out -- datasets, hypotheses, comparisons, and the numbers that back the framework.

25/25
Perturbation Pass
92.9%
Satisfaction Match
100%
Norm Bank Agreement
9/9
Adversarial Tests
Core Analysis

Side-by-Side Comparison

Five scenarios run through Delphi, MoReBench, and MHF under two parameterizations. See exactly where flat approaches lose the thread and hierarchy adds structure.

5 Scenarios 4 Approaches Interactive
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Practical Summary

What each approach gives you, what it misses, and where MHF fills the gaps. Haidt profile divergence, feature matrix, and The Bottom Line.

6 Approaches Feature Matrix Haidt Profiles
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55

55-Scenario Scorecard

Every scenario scored across 5 frameworks: MHF Christian, MHF Secular, MHF Gert, flat rubric, and Delphi-style. Filter by category, expand for detail.

55 Scenarios 5 Frameworks 77% Ground Truth
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Try It Yourself

Explore 5 pre-loaded scenarios interactively. See stakeholders, constraints, recommendations under Christian and Secular parameterizations, and moral residue.

Interactive 5 Scenarios CLI Instructions
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Δ

Methodology Deep Dive

How Christian weights are derived from scripture vs how secular weights come from crowdworker data. Why the numbers don't compare directly. Full Rai/Fiske analysis.

Derivation Rai/Fiske Scale Explanation
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Datasets
A

AITA Dataset

Reddit "Am I The Asshole" corpus. Real moral dilemmas with community verdicts. Used for secular baseline weight calibration and stakeholder extraction validation.

Reddit Crowdsourced
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U

UniMoral Dataset

Unified moral judgment dataset combining multiple sources. Provides cross-dataset validation for MHF's constraint satisfaction scores.

Multi-source Unified
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P

Pew Surveys

Pew Research Center moral attitudes data. Grounds the framework's community-level parameterization -- how real populations weight moral foundations differently.

Survey Demographics
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Hypotheses & Experiments
H

Hypotheses Overview

The core claims: hierarchy-aware evaluation produces materially different scores, LLMs converge on low-dimensional moral reasoning, and relational graphs surface missing stakeholders.

Round 12 Experiment 20 Agents
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D

Hypotheses Detail

Detailed results from the variance experiment (Round 12), perturbation tests (25 pairs, 5 families), and three-way parameterization comparison (Christian vs. Secular vs. Gert).

25 Perturbation Pairs 100% Pass Rate
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Architecture & Data
G

Graph Architecture

The relational DAG structure: nodes (stakeholders), edges (obligations), Haidt-space weights, and constraint propagation mechanics. Interactive graph explorer.

DAG Haidt Space Constraints
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W

Weight Profiles

Christian and secular weight profiles side by side. Authority at 10x, Sanctity at 13.6x -- the dimensions that drive divergence, grounded in Haidt's empirical work.

Christian Secular 6 Dimensions
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