Two Profiles, Two Methods

The secular and Christian Haidt profiles are not two versions of the same measurement. They are two fundamentally different instruments applied to two fundamentally different source corpora, producing numbers that live in different units and cannot be naively compared.

"One asks: where does society look? The other asks: how strongly does God command?"

On This Page

  1. Secular Derivation Pipeline
  2. Christian Derivation Pipeline
  3. Why the Numbers Don't Compare Directly
  4. The 12 Root Constraints
  5. Rai/Fiske Relational Models Analysis
  6. Practical Implications

Secular Parameterization Derivation Pipeline

The secular Haidt profile captures moral attention -- the relative share of moral reasoning that contemporary Americans devote to each of Haidt's five measured foundations. It is extracted from a large-scale crowdsourced dataset of descriptive moral norms.

1 Source Corpus: Social Chemistry 101 356,366 rules-of-thumb about social and moral behavior, crowdsourced via Amazon Mechanical Turk. Each entry is a natural-language statement like "It's wrong to lie to your spouse" with structured annotations for social judgment, moral foundation labels, and agreement levels.
2 Filter to Haidt-Labeled Subset Only entries with at least one Haidt moral foundation label are retained. This yields 175,465 entries -- approximately 49% of the corpus. Entries without moral foundation labels (purely social norms with no moral content) are excluded.
3 Count Foundation Frequency For each of the six Haidt foundations (care, fairness, loyalty, authority, sanctity, liberty), count how many entries carry that label. An entry can carry multiple labels. Raw counts reveal the distribution of moral attention across foundations.
4 Weight by Agreement + Social Pressure Raw frequency is modulated by two signals from the Commonsense Norm Bank (177,750 Overton-window entries): agreement rate (how many annotators concur with the norm) and social pressure (how strongly the norm is enforced). Higher agreement and pressure amplify a foundation's weight; controversial or low-pressure norms are attenuated.
5 Normalize to 1.0 The weighted counts are normalized so that all foundation weights sum to exactly 1.0. The result is a probability distribution: each weight represents the share of total moral signal attributable to that foundation.

Resulting Secular Profile

Output unit: Share of moral attention (sums to 1.0)

Care
0.4697
Loyalty
0.1893
Fairness
0.1762
Authority
0.0905
Sanctity
0.0743
Liberty
0.0000
Why is Liberty zero? The Social Chemistry 101 dataset does not include a "liberty" label in its annotation schema. This is a limitation of the source data, not a claim that secular Americans have zero concern for liberty. The foundation simply cannot be measured from this corpus.

Christian Parameterization Derivation Pipeline

The Christian Haidt profile captures moral intensity -- how strongly each foundation is commanded within the Protestant theological tradition. It is derived from scripture and validated against four major theological works.

1 Source Corpus: BSB + Theological Texts Primary: the Berean Standard Bible (BSB), a modern English translation. Secondary: four theological reference works -- C.S. Lewis (Mere Christianity), Charles Spurgeon (Morning and Evening), Oswald Chambers (My Utmost for His Highest), A.W. Tozer (The Pursuit of God).
2 Map Commandments to Haidt Foundations Each of the 12 root constraints (derived from the Decalogue, the Great Commandments, and key New Testament imperatives) is mapped to all six Haidt foundations. A single constraint activates multiple foundations at varying strengths. For example, "love your neighbor as yourself" maps to care=0.95, fairness=0.85, loyalty=0.70, authority=0.40, sanctity=0.50, liberty=0.50.
3 Extract Weight Signals from Language Intensity The obligation language of each constraint encodes intensity. Three signal levels are extracted from the deontic modals used in scripture and theological commentary:
Modal Obligation Type Base Signal Example
"must" / "shall not" MUST_DO / MUST_NOT_DO 0.90 "You shall not murder" (Exodus 20:13)
"should" / "ought" SHOULD_DO 0.70 "Be a faithful steward" (Matthew 25:14-30)
"may" / "permitted" MAY_DO 0.50 "Christian liberty" (Galatians 5:13)
4 Cross-Reference: Foundation Alignment TLR Each constraint is validated against the Foundation Alignment Seed v4.1 (TLR Protocol): Truth, Love, and Role gates. All three gates must pass for any action. The TLR gates serve as meta-constraints that modulate the final foundation weights. For example, the Truth gate (John 17:17) reinforces fairness=0.9 and sanctity=0.7, while the Love gate (Romans 13:10) reinforces care=0.95.
5 Validate 122 Scripture Citations Every constraint maps to specific scripture verses. Across all 12 root constraints and 3 TLR gates, 122 individual scripture citations are referenced and validated against the BSB text. Each citation has been verified: the verse text matches, the foundation mapping is defensible from the text, and the obligation type matches the deontic language of the passage.

Resulting Christian Profile

Output unit: Intensity score (each foundation independent, sums to 4.45)

Sanctity
0.95
Authority
0.90
Care
0.80
Loyalty
0.75
Fairness
0.60
Liberty
0.45
Why do these sum to 4.45, not 1.0? Because intensity is measured per-foundation, independently. A tradition can command care at 0.80 intensity and authority at 0.90 intensity simultaneously -- these are not competing for a fixed budget. The profile is a vector of independent intensities, not a probability distribution.

Critical Distinction Why the Numbers Don't Compare Directly

The most common mistake when reading these profiles is to compare numbers across parameterizations and conclude that one tradition "cares more" or "values fairness less." This is a category error. The two profiles measure fundamentally different quantities.

Secular: Care = 0.47
47%

47% of the total moral signal in contemporary American social norms is about care. This means that when Americans reason about right and wrong, nearly half of their moral vocabulary and attention is devoted to care/harm concerns. It says nothing about how intensely care is felt -- only that care dominates the conversation.

Christian: Care = 0.80
80%

Care is commanded at 80% intensity in the Protestant tradition. This means that care obligations are strong, emphatic, and scripturally grounded (the second greatest commandment). It says nothing about care's share relative to other foundations -- sanctity (0.95) and authority (0.90) are both commanded at even higher intensity.

The analogy: Secular weights are like a pie chart -- slices must sum to 100%. If care gets a bigger slice, fairness necessarily gets a smaller one. Christian weights are like a mixing board -- each fader is independent. Turning up authority does not turn down care.

Side-by-Side: The Numbers in Context

Foundation Secular Meaning Christian Meaning
Care 0.4697 47% of moral attention 0.80 80% command intensity
Fairness 0.1762 18% of moral attention 0.60 60% command intensity
Loyalty 0.1893 19% of moral attention 0.75 75% command intensity
Authority 0.0905 9% of moral attention 0.90 90% command intensity
Sanctity 0.0743 7% of moral attention 0.95 95% command intensity
Liberty 0.0000 unmeasured in corpus 0.45 45% command intensity
Sum 1.0000 probability distribution 4.45 intensity vector

What Valid Comparisons Look Like

Christian Parameterization The 12 Root Constraints

The Christian profile is grounded in 12 root constraints plus 3 TLR meta-gates. Each constraint is sourced from specific scripture passages, assigned an obligation type and strength, and mapped to all six Haidt foundations. The constraints are ordered by strength.

TLR Meta-Gates (Must All Pass)

MUST Truth Gate -- Does this correspond to reality? Is there deception?
John 17:17, Exodus 20:16 · strength: 0.95
0.95
MUST Love Gate -- Does this honor human dignity and do no harm?
Romans 13:10, Matthew 7:12 · strength: 0.95
0.95
MUST Role Gate -- Is this within proper authority and necessity?
Matthew 22:21 · strength: 0.90
0.90

Root Constraints (Ordered by Strength)

MUST Love God First -- Love the Lord your God with all your heart, soul, mind, and strength
Matthew 22:37, Deuteronomy 6:5, Mark 12:30
1.00
MUST NOT Do Not Murder -- Extends to anger and contempt (Matthew 5:21-22)
Exodus 20:13, Matthew 5:21-22, Romans 13:9, 1 John 3:15
0.98
MUST Love Neighbor as Self -- The second greatest commandment
Matthew 22:39, Leviticus 19:18, Romans 13:9, Galatians 5:14
0.95
MUST NOT Do Not Commit Adultery -- Extends to lustful intent (Matthew 5:27-28)
Exodus 20:14, Matthew 5:27-28, Hebrews 13:4, 1 Cor 6:18-20
0.90
MUST NOT Do Not Bear False Witness -- Exception: protecting innocent life
Exodus 20:16, Proverbs 12:22, Ephesians 4:25, Colossians 3:9
0.90
MUST Protect the Vulnerable -- Defend the fatherless, plead the case of the widow
Isaiah 1:17, James 1:27, Psalm 82:3-4, Proverbs 31:8-9, Matthew 25:35-40
0.88
MUST Truth and Honesty -- Speak the truth in love
John 8:32, Ephesians 4:15, Ephesians 4:25, Zechariah 8:16
0.88
MUST NOT Do Not Steal -- Includes intellectual property; necessity exception
Exodus 20:15, Ephesians 4:28, Romans 13:9
0.85
MUST Honor Father and Mother -- First commandment with a promise
Exodus 20:12, Deuteronomy 5:16, Ephesians 6:1-3, Colossians 3:20
0.85
MUST Forgive as Forgiven -- Not optional; does not mean no consequences
Matthew 6:14-15, Colossians 3:13, Ephesians 4:32, Matthew 18:21-35
0.85
SHOULD Stewardship -- Body, gifts, resources, time, creation
Matthew 25:14-30, 1 Cor 6:19-20, Genesis 1:28, 1 Peter 4:10
0.75
SHOULD Submit to Legitimate Authority -- Exception: "We must obey God rather than men" (Acts 5:29)
Romans 13:1-7, 1 Peter 2:13-17, Titus 3:1, Hebrews 13:17
0.70
Obligation type maps to intensity signal: MUST_DO and MUST_NOT_DO constraints use "shall"/"must" language and carry base signals of 0.85-1.00. SHOULD_DO constraints use "ought"/"should" language and carry base signals of 0.70-0.75. This three-tier system (must/should/may at 0.9/0.7/0.5) is how biblical deontic language is translated into the numerical intensity scale.

Relational Models Theory Rai/Fiske Analysis

The Moral Hierarchy Framework does not treat moral foundations as context-free constants. Moral obligations shift based on the relationship between actors. This insight comes from Rai and Fiske's relational models theory of moral judgment, which argues that the same action can be moral or immoral depending on the relational context in which it occurs.

The Four Relational Models (Fiske 1991)

Communal Sharing (CS)
obligation: care, unity, sacrifice
Members of the group are equivalent and interchangeable with respect to the shared resource or identity. The paradigmatic relationship: family, close kin, romantic partners. Morality centers on care, loyalty, and sanctity -- protecting the in-group, sharing freely, maintaining purity of the shared bond.
Authority Ranking (AR)
obligation: obey, honor, protect
People are linearly ordered along a hierarchical dimension. The paradigmatic relationships: parent-child, boss-employee, God-person. Morality centers on authority and care -- superiors protect and provide, subordinates defer and respect. Obligations flow asymmetrically.
Equality Matching (EM)
obligation: reciprocate, balance, take turns
People are distinct but equal, tracking balance and reciprocity. The paradigmatic relationships: friends, peers, colleagues. Morality centers on fairness -- tit-for-tat, equal treatment, distributive justice, turn-taking.
Market Pricing (MP)
obligation: proportional exchange, contract, merit
Relationships are organized by ratios, rates, and proportional exchange. The paradigmatic relationships: buyer-seller, employer-employee (transactional dimension). Morality centers on fairness and liberty -- proportional reward, contractual obligation, freedom to enter or exit exchanges.

How obligation_type Captures Relational Context

In the MHF data model, every relationship edge carries an obligation_type that determines which relational model applies. This changes the moral calculus for the same foundation. Consider the concrete difference:

Boss Edge
relationship: employer-employee obligation_type: comply relational_model: AR + MP // Authority Ranking (hierarchy) // + Market Pricing (contract) care: 0.2 // low -- transactional fairness: 0.8 // high -- contractual authority: 0.7 // high -- hierarchy

The boss-employee relationship is primarily governed by Authority Ranking (obey directives) and Market Pricing (fair compensation). Care is present but attenuated -- the boss has some duty to employee wellbeing, but it is bounded by the contractual frame.

Father Edge
relationship: parent-child obligation_type: honor relational_model: AR + CS // Authority Ranking (hierarchy) // + Communal Sharing (family) care: 0.8 // high -- family bond fairness: 0.4 // lower -- not transactional authority: 0.85 // high -- parental authority

The father-child relationship is governed by Authority Ranking (the child honors the parent) and Communal Sharing (the family is a unity). Care dominates because the Communal Sharing model demands sacrifice, care, and unconditional regard. The same "authority" foundation activates differently because the relational model has changed.

Key insight: It is not that bosses don't care or that fathers aren't fair. It is that the weight of each foundation shifts with the relational model. The same person can be a boss (AR+MP) and a father (AR+CS) simultaneously, and the moral obligations differ in each role -- not because the foundations change, but because the relationship activates different foundations at different strengths.

Dyad-Swap Validation: 5/5 Tests Pass

To validate that the relational model encoding produces correct moral intuitions, we run five dyad-swap tests. Each test holds the action constant and swaps the relationship, checking that the model's moral judgment flips in the direction predicted by Rai and Fiske.

Test Action Dyad A Dyad B Expected Shift Result
1 Give direct order Parent → child Stranger → stranger Permissible → impermissible (authority drops) PASS
2 Share personal secret Spouse → spouse Employee → boss Expected → inappropriate (loyalty context shifts) PASS
3 Demand equal split Friend → friend Parent → child Fair → selfish (EM → CS model swap) PASS
4 Negotiate compensation Employer → employee Parent → child Appropriate → disturbing (MP → CS model swap) PASS
5 Refuse to forgive Stranger → stranger Spouse → spouse Understandable → damaging (low → high care/loyalty) PASS

Earp's Empirical Evidence

Brian D. Earp and colleagues have provided empirical support for the claim that moral judgments are relationship-dependent in ways that standard Moral Foundations Theory does not capture. Their work demonstrates several findings that validate the MHF relational approach:

Practical Impact What This Means for Users

The choice of parameterization is not cosmetic. It changes how the system evaluates moral dilemmas, ranks competing obligations, and generates guidance. Here is what each parameterization means in practice.

Under Secular Parameterization

The system reflects the empirical moral priorities of contemporary American society. It will tend to:

  • Prioritize harm prevention above all else. With care at 0.47, nearly half of moral reasoning weight goes to "does this cause harm?" This matches the dominant moral frame in secular liberal democracies.
  • Treat authority and sanctity as secondary. At 0.09 and 0.07 respectively, these foundations carry minimal weight. Arguments from tradition, hierarchy, or purity will be deprioritized relative to care and fairness.
  • Balance fairness and loyalty roughly equally. At 0.18 and 0.19, these foundations compete on nearly equal footing, producing genuine tension in dilemmas where group loyalty conflicts with impartial fairness.
  • Ignore liberty claims. With liberty at 0.00 (unmeasured), the system has no weight for autonomy-based arguments. This is a known limitation, not a feature.
  • Modulate by relationship. A stranger's harm matters, but a spouse's or child's harm matters more -- relationship weights adjust the base profile contextually.

Under Christian Parameterization

The system reflects Protestant theological ethics. It will tend to:

  • Weigh all foundations heavily. No foundation drops below 0.45. The moral field is broad -- care, fairness, loyalty, authority, sanctity, and liberty all carry significant weight. This means more dilemmas will register as genuinely difficult.
  • Elevate sanctity and authority. At 0.95 and 0.90, these are the most intense foundations. Holiness, reverence, proper order, and divine command carry enormous weight in moral reasoning. Purity violations and authority violations are treated as serious.
  • Apply the TLR gates as hard constraints. Before foundation weights even apply, every action must pass Truth (no deception), Love (no harm to dignity), and Role (within proper authority). These gates can veto actions that foundation weights alone would permit.
  • Recognize the god-self relationship as primary. With base weight 1.0, the relationship to God outweighs all human relationships. Obligations to God can override obligations to human authorities (Acts 5:29).
  • Constrain liberty with love. Liberty exists (0.45) but is explicitly bounded: "Do not use your freedom as a cover-up for evil" (1 Peter 2:16), "through love serve one another" (Galatians 5:13). Freedom is real but not ultimate.
  • Include enemy and stranger edges. Unlike the secular profile, the Christian profile explicitly models obligations toward enemies (care=0.60) and strangers (care=0.75). "Love your enemies" is not merely aspirational -- it carries measurable weight.

When Parameterizations Agree

Despite their different measurement types and dramatically different shapes, the two parameterizations produce convergent judgments on many common moral questions:

When Parameterizations Diverge

The most interesting cases are where the two profiles produce different moral emphasis:

The framework does not claim one parameterization is correct. It provides transparent, auditable moral reasoning under the user's chosen ethical framework. The methodology page exists so that every number can be traced back to its source -- whether that source is 175,465 crowdsourced norms or 122 validated scripture citations.