---
# System prepended metadata

title: Executive Order

---

# Executive Order - Legal Analysis: Biological Basis for Sex Classification

## Executive Order Framework

The executive order establishes several key principles:

1. Quote (a): "'Sex' shall refer to an individual's immutable biological classification as either male or female."
   - Establishes sex as a biological classification
   - Makes this classification immutable
   - Creates a binary framework (male/female)

2. Quote (d): "'Female' means a person belonging, at conception, to the sex that produces the large reproductive cell."
   Quote (e): "'Male' means a person belonging, at conception, to the sex that produces the small reproductive cell."
   - Provides specific sufficient conditions for classification
   - Uses reproductive cell type as a determinant
   - References biological characteristics present at conception

## Key Legal Arguments for Broader Biological Classification

### 1. Biological Basis Requirement

The order's fundamental requirement (Quote a) establishes sex as a "biological classification." This creates the governing framework: any valid classification must be based on biological evidence. This is the primary constraint on all classifications.

### 2. Sufficient but Not Necessary Conditions

Quotes (d) and (e) provide specific sufficient conditions for classification based on reproductive cells. Critical legal analysis reveals:

a) These quotes establish that:
   - Producing large reproductive cells is sufficient for female classification
   - Producing small reproductive cells is sufficient for male classification

b) However, the text does not:
   - Claim these are the only valid criteria
   - Use language of exclusivity (e.g., "only," "solely," "exclusively")
   - Prohibit other biological criteria from being sufficient

### 3. Negative Space in the Order

The order's structure creates meaningful negative space:

1. It establishes sex as biological (Quote a)
2. It provides specific examples of sufficient biological criteria (Quotes d, e)
3. It explicitly rejects non-biological criteria (Quote f: rejecting "self-assessed gender identity")
4. It remains silent on other biological criteria

This structure suggests:
- Intentional focus on biological basis
- Deliberate provision of examples rather than exhaustive criteria
- Clear rejection of non-biological factors
- Implicit acceptance of other valid biological evidence

### 4. Legal Principle of Classification

The order establishes a key principle: when sufficient biological evidence exists for a sex classification, that classification must be recognized. This is demonstrated by:

1. The requirement that sex be a "biological classification" (Quote a)
2. The provision of specific examples where biological evidence requires classification (Quotes d, e)
3. The rejection of non-biological bases for classification (Quote f)

### 5. Implementation in Classification System

Therefore, a legally valid classification system must:

1. Accept reproductive cell production as sufficient evidence (per Quotes d, e)
2. Allow other biological evidence to be sufficient when:
   - It is truly biological in nature (per Quote a)
   - It provides conclusive evidence of sex classification
   - It maintains the immutable nature of the classification (per Quote a)
3. Reject any classification based on:
   - "self-assessed gender identity" (per Quote f)
   - non-biological criteria
   - mutable characteristics

### 6. Abstract Representation of Biological Evidence

The concept of "has_biological_evidence_of_sex" is legally valid because:

1. It strictly adheres to the biological requirement (Quote a)
2. It follows the order's pattern of recognizing sufficient biological conditions (Quotes d, e)
3. It maintains the immutability requirement (Quote a)
4. It excludes non-biological factors (consistent with Quote f)
5. It operates within the negative space intentionally left by the order



## Addressing Biological Complexity

### 1. Implied Recognition of Edge Cases

The executive order's framework implicitly acknowledges biological complexity through:

a) Its careful construction of sufficient conditions:
   - Quote (d) and (e) provide clear cases where classification is required
   - These establish when classification is mandatory, not when it's possible

b) Its focus on conclusive biological evidence:
   - The order requires classifications to be based on biological evidence
   - This implies the evidence must be conclusive to mandate classification

### 2. Dealing with Inconclusive Evidence

The order's structure creates a framework for handling cases where biological evidence is inconclusive:

1. When Evidence is Conclusive:
   - Reproductive cell production mandates classification (Quotes d, e)
   - Other conclusive biological evidence mandates classification (derived from Quote a)

2. When Evidence is Inconclusive:
   - The order doesn't mandate forced classification into male/female
   - No provision requires classification without conclusive evidence
   - The biological basis requirement (Quote a) actually suggests avoiding classification without conclusive biological evidence

### 3. Legal Necessity of "Sexless" Classification

The inclusion of a "sexless" classification is legally necessary because:

1. Real-World Biological Complexity:
   - Some individuals may have ambiguous or inconclusive biological characteristics
   - Medical conditions can result in unclear or mixed biological indicators
   - Historical records or evidence may be incomplete

2. Order's Requirements:
   - Classifications must be based on biological evidence (Quote a)
   - Classifications must be immutable once made (Quote a)
   - Non-biological factors cannot be considered (Quote f)

3. Legal Coherence:
   - Forcing binary classification without conclusive evidence would contradict the order's biological basis requirement
   - Creating a "sexless" category maintains the integrity of male/female classifications
   - This approach preserves the immutability requirement while acknowledging biological reality

### 4. Implementation Principles

A legally sound classification system should:

1. Mandate Classification When Evidence is Conclusive:
   - Based on reproductive cells (Quotes d, e)
   - Based on other conclusive biological evidence (Quote a)

2. Assign "Sexless" Classification When:
   - Biological evidence is inconclusive
   - Multiple biological indicators conflict
   - Insufficient evidence exists for definitive classification

3. Maintain Core Requirements:
   - All classifications remain based on biological evidence
   - Classifications remain immutable
   - Non-biological factors remain excluded

## Conclusion

The executive order's framework supports a three-category classification system (male/female/sexless) because:

1. It requires biological basis for classification
2. It provides examples of sufficient conditions
3. It rejects non-biological criteria
4. It implies the need for conclusive evidence
5. It acknowledges biological reality through its construction

This framework necessitates a "sexless" classification to:
- Maintain fidelity to the biological evidence requirement
- Handle cases where evidence is inconclusive
- Preserve the integrity of male/female classifications
- Provide a complete and logically consistent system

The resulting system:
- Classifies as male/female when biological evidence is conclusive
- Classifies as sexless when biological evidence is inconclusive
- Maintains immutability of all classifications
- Excludes non-biological factors
- Acknowledges real-world biological complexity

This interpretation provides a legally coherent framework that:
1. Fulfills the order's requirements
2. Maintains its core principles
3. Addresses real-world biological complexity
4. Avoids forced classification without conclusive evidence

The order's framework:
1. Requires biological basis for classification
2. Provides examples of sufficient conditions
3. Rejects non-biological criteria
4. Creates space for other valid biological evidence

This framework supports a classification system that:
- Recognizes reproductive cells as sufficient evidence
- Allows other conclusive biological evidence to be sufficient
- Maintains immutability of classification
- Excludes non-biological factors

This interpretation maintains fidelity to the order's text while providing a complete and logically consistent framework for sex classification based on biological evidence.



## Basic Version
```datalog=
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% DATALOG PRIMER:
% 1. Datalog is a logical programming language based on facts and rules
% 2. Facts are simple statements like: human(john). meaning "john is a human"
% 3. Rules have a head and body separated by :- 
%    Example: woman(X) :- sex(X, female), age(X, adult).
%    Reads as: "X is a woman IF X's sex is female AND X's age is adult"
% 4. Capital letters like X represent variables that can match any value
% 5. :- by itself starts an integrity constraint (a rule that must never be violated)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%% SECTION 1: BASIC FACTS %%%

% These are simple facts stating what types of reproductive cells exist
reproductive_cell(large).    % Means: "large is a type of reproductive cell"
reproductive_cell(small).    % Means: "small is a type of reproductive cell"

% Define age categories we'll need
age_category(adult).         % Means: "adult is an age category"
age_category(juvenile).      % Means: "juvenile is an age category"

%%% SECTION 2: CLASSIFICATION RULES %%%

% Quote (a): "'Sex' shall refer to an individual's immutable biological 
% classification as either male or female."

% Rule 1: If someone produces large reproductive cells, they are female
% Read as: "X's sex is female IF X produces large reproductive cells"
sex(X, female) :- produces_cell(X, large).

% Rule 2: If someone produces small reproductive cells, they are male
% Read as: "X's sex is male IF X produces small reproductive cells"
sex(X, male) :- produces_cell(X, small).

% Rule 3: Other biological evidence can also determine sex
% Read as: "X's sex is female IF X has biological evidence of being female"
sex(X, female) :- has_biological_evidence_of_sex(X, female).
% Read as: "X's sex is male IF X has biological evidence of being male"
sex(X, male) :- has_biological_evidence_of_sex(X, male).

% Rules for implementing quotes (b) and (c) about women, men, girls, and boys
% Read as: "X is a woman IF X's sex is female AND X's age is adult"
woman(X) :- sex(X, female), age(X, adult).

% Read as: "X is a man IF X's sex is male AND X's age is adult"
man(X) :- sex(X, male), age(X, adult).

% Read as: "X is a girl IF X's sex is female AND X's age is juvenile"
girl(X) :- sex(X, female), age(X, juvenile).

% Read as: "X is a boy IF X's sex is male AND X's age is juvenile"
boy(X) :- sex(X, male), age(X, juvenile).

%%% SECTION 3: INTEGRITY CONSTRAINTS %%%
% Constraints are rules that must never be violated
% They start with :- and represent things that are NOT allowed

% Constraint 1: No person can have two different sexes
% Read as: "It is NOT allowed for X to have sex S1 and also sex S2 if S1 and S2 are different"
:- sex(X, S1), sex(X, S2), S1 != S2.

% Constraint 2: Sex cannot change over time
% Read as: "It is NOT allowed for X to have sex S1 at time T1 and sex S2 at time T2 if S1 and S2 are different"
:- sex(X, S1, T1), sex(X, S2, T2), S1 != S2.

% Constraint 3: No person can have two different age categories
% Read as: "It is NOT allowed for X to have age A1 and also age A2 if A1 and A2 are different"
:- age(X, A1), age(X, A2), A1 != A2.

% Constraint 4: Categories (woman/man/girl/boy) must be mutually exclusive
% Read as: "It is NOT allowed for X to be both a woman and a man"
:- woman(X), man(X).
:- woman(X), girl(X).
:- woman(X), boy(X).
:- man(X), girl(X).
:- man(X), boy(X).
:- girl(X), boy(X).

% Rule to check if someone's classification is incomplete
% Read as: "X has an incomplete classification IF X is human AND X is not a woman 
% AND X is not a man AND X is not a girl AND X is not a boy"
incomplete_classification(X) :- 
    human(X),
    not woman(X),
    not man(X),
    not girl(X),
    not boy(X).

% Constraint 5: No person can have an incomplete classification
% Read as: "It is NOT allowed for any human X to have an incomplete classification"
:- human(X), incomplete_classification(X).

%%% SECTION 4: EXAMPLE DATA %%%
% These are concrete examples showing how the rules work

% Example 1: A human who produces large reproductive cells
human(person1).                    % Means: "person1 is a human"
produces_cell(person1, large).     % Means: "person1 produces large reproductive cells"
age(person1, adult).              % Means: "person1 is an adult"
% Based on these facts and our rules:
% - person1 will be classified as female (because they produce large reproductive cells)
% - person1 will be classified as a woman (because they are female and adult)

% Example 2: A human classified by other biological evidence
human(person2).                                      % Means: "person2 is a human"
has_biological_evidence_of_sex(person2, male).       % Means: "person2 has biological evidence of being male"
age(person2, juvenile).                              % Means: "person2 is juvenile"
% Based on these facts and our rules:
% - person2 will be classified as male (because of biological evidence)
% - person2 will be classified as a boy (because they are male and juvenile)

%%% SECTION 5: VERIFICATION QUERIES %%%
% Queries are questions we can ask the system to verify it works correctly

% Find all women in the system
?- woman(X).

% Find all men in the system
?- man(X).

% Find all girls in the system
?- girl(X).

% Find all boys in the system
?- boy(X).

% Check if anyone has multiple classifications (should find nothing)
?- woman(X), (man(X); girl(X); boy(X)).

% Check if anyone is missing a classification (should find nothing)
?- human(X), incomplete_classification(X).

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% KEY POINTS ABOUT THIS PROGRAM:
%
% 1. It implements the executive order's requirement that sex is biological and
%    immutable by:
%    - Basing classification only on biological characteristics
%    - Using constraints to prevent sex from changing
%
% 2. It shows that producing specific reproductive cells is sufficient but not
%    necessary for classification because:
%    - If someone produces large/small reproductive cells, they are
%      automatically classified as female/male
%    - But there are other valid biological ways to be classified (captured
%      by has_biological_evidence_of_sex)
%
% 3. It maintains clear, distinct categories:
%    - Every person must be exactly one of: woman, man, girl, or boy
%    - No person can be in multiple categories
%    - Categories are based on both sex and age
%
% 4. It contrasts with gender ideology (quote f) by:
%    - Using only biological criteria
%    - Making classifications immutable
%    - Not including self-identification
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
```



1. The fundamental classification system implements quotes (a), (d), and (e) while maintaining sex as an immutable biological property

2. The age-based categories implement quotes (b) and (c), creating distinct classifications for adults and juveniles

3. The integrity constraints ensure that:
   - Sex remains immutable (quote a)
   - Categories remain mutually exclusive (quotes b, c)
   - Classifications are based solely on biological characteristics

4. The abstraction `has_biological_evidence_of_sex` is valid because:
   - The order establishes sex as biological (quote a)
   - It provides reproductive cells as sufficient criteria (quotes d, e)
   - It doesn't claim these are the only biological criteria
   - The program maintains all required properties

5. The system directly contrasts with quote (f) about gender ideology by:
   - Maintaining sex as purely biological
   - Making classifications immutable
   - Not including self-assessment or identity concepts


## Sexless version

```datalog 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% DATALOG PRIMER:
% 1. Facts are simple statements like: human(john). meaning "john is a human"
% 2. Rules use :- to mean "IF"
% 3. Capital letters are variables that can match any value
% 4. Constraints show what's not allowed
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%% SECTION 1: BASIC FACTS %%%

% Define types of reproductive cells
reproductive_cell(large).    % Means: "large is a type of reproductive cell"
reproductive_cell(small).    % Means: "small is a type of reproductive cell"

% Define all possible sex classifications
sex_category(female).
sex_category(male).
sex_category(sexless).       % New: Allow for sexless classification

% Define age categories
age_category(adult).
age_category(juvenile).

%%% SECTION 2: CLASSIFICATION RULES %%%

% Rule 1: If someone produces large reproductive cells, they are female
sex(X, female) :- produces_cell(X, large).

% Rule 2: If someone produces small reproductive cells, they are male
sex(X, male) :- produces_cell(X, small).

% Rule 3: Other biological evidence can determine sex
sex(X, female) :- has_biological_evidence_of_sex(X, female).
sex(X, male) :- has_biological_evidence_of_sex(X, male).

% Rule 4: NEW - If someone is human but has no conclusive biological evidence, they are sexless
sex(X, sexless) :- 
    human(X),
    not produces_cell(X, large),
    not produces_cell(X, small),
    not has_biological_evidence_of_sex(X, female),
    not has_biological_evidence_of_sex(X, male).

% Rules for age-based categories
woman(X) :- sex(X, female), age(X, adult).
man(X) :- sex(X, male), age(X, adult).
girl(X) :- sex(X, female), age(X, juvenile).
boy(X) :- sex(X, male), age(X, juvenile).

% New categories for sexless individuals
sexless_adult(X) :- sex(X, sexless), age(X, adult).
sexless_juvenile(X) :- sex(X, sexless), age(X, juvenile).

%%% SECTION 3: INTEGRITY CONSTRAINTS %%%

% Constraint 1: No person can have two different sexes
:- sex(X, S1), sex(X, S2), S1 != S2.

% Constraint 2: Sex classification cannot change over time
:- sex(X, S1, T1), sex(X, S2, T2), S1 != S2.

% Constraint 3: One age category per person
:- age(X, A1), age(X, A2), A1 != A2.

% Constraint 4: Categories must be mutually exclusive
:- woman(X), man(X).
:- woman(X), girl(X).
:- woman(X), boy(X).
:- woman(X), sexless_adult(X).
:- woman(X), sexless_juvenile(X).
:- man(X), girl(X).
:- man(X), boy(X).
:- man(X), sexless_adult(X).
:- man(X), sexless_juvenile(X).
:- girl(X), boy(X).
:- girl(X), sexless_adult(X).
:- girl(X), sexless_juvenile(X).
:- boy(X), sexless_adult(X).
:- boy(X), sexless_juvenile(X).
:- sexless_adult(X), sexless_juvenile(X).

% Rule to check if someone's classification is incomplete
incomplete_classification(X) :- 
    human(X),
    not woman(X),
    not man(X),
    not girl(X),
    not boy(X),
    not sexless_adult(X),
    not sexless_juvenile(X).

% Constraint 5: Every person must have a complete classification
:- human(X), incomplete_classification(X).

%%% SECTION 4: EXAMPLE DATA %%%

% Example 1: Person with clear female classification
human(person1).
produces_cell(person1, large).
age(person1, adult).
% Will be classified as female and thus a woman

% Example 2: Person with biological evidence of being male
human(person2).
has_biological_evidence_of_sex(person2, male).
age(person2, juvenile).
% Will be classified as male and thus a boy

% Example 3: NEW - Person without conclusive biological evidence
human(person3).
age(person3, adult).
% Will be classified as sexless_adult due to lack of conclusive evidence

%%% SECTION 5: VERIFICATION QUERIES %%%

% Find all classifications
?- woman(X).
?- man(X).
?- girl(X).
?- boy(X).
?- sexless_adult(X).
?- sexless_juvenile(X).

% Verify no multiple classifications
?- woman(X), (man(X); girl(X); boy(X); sexless_adult(X); sexless_juvenile(X)).

% Verify no incomplete classifications
?- human(X), incomplete_classification(X).

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% KEY DIFFERENCES IN THIS VERSION:
%
% 1. Added 'sexless' as a valid sex category for cases without conclusive
%    biological evidence
%
% 2. Created new categories sexless_adult and sexless_juvenile for
%    age-appropriate classification of sexless individuals
%
% 3. Modified the classification system to:
%    - Still classify as male/female when there is conclusive evidence
%    - Classify as sexless when evidence is inconclusive
%    - Maintain immutability of classification
%
% 4. Extended mutual exclusivity constraints to include sexless categories
%
% 5. Maintains core principles:
%    - Classifications remain immutable once made
%    - Everyone must have exactly one classification
%    - All classifications are based on biological evidence
%    - No self-identification involved
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

```





## Addressing Common Criticisms

### 1. Claims of Circular Reasoning

The criticism that the order uses circular reasoning to define sex as binary and immutable misunderstands the logical structure. The order:
- Establishes sex as a biological classification (definitional premise)
- States this classification is binary and immutable (characteristics of the classification)
- Provides specific sufficient conditions for classification

This is not circular - it's a standard logical structure of establishing a category and then describing its properties.

### 2. False Dichotomy Claims

Critics argue the order presents a false dichotomy between binary sex classification and current biological understanding. However, this conflates two distinct domains:
- Logical framework: The order establishes a logically consistent classification system
- Biological reality: The empirical facts about biological sex variation

The order's logical consistency is independent of whether it fully captures biological complexity.

### 3. Definition Consistency

The claim that the order inconsistently shifts between different meanings of biological reality fails because:
- The order maintains consistent usage of "biological classification"
- References to different biological characteristics (chromosomes, reproductive cells) are examples of evidence, not shifts in definition
- The framework consistently requires biological basis while allowing multiple types of biological evidence

### 4. Completeness of Definitions

Critics argue the definitions are both over- and under-inclusive, citing cases like:
- Infertile individuals
- Post-menopausal women
- Post-vasectomy men

This criticism misunderstands the temporal aspect of the definitions:
- Classification is determined "at conception"
- Later changes in reproductive capacity don't affect classification
- The immutability requirement ensures consistency across time

### 5. Legal vs Biological Reality

The argument that legal definitions shouldn't be needed if biological reality is "fundamental" misunderstands the purpose of legal frameworks:
- Legal definitions formalize how biological reality will be recognized in law
- This doesn't legislate biological reality itself
- The definitions create a consistent framework for legal recognition of biological facts

### 6. Scientific Arguments

While critics cite current biological research showing sex complexity, these arguments don't affect the logical coherence of the framework:
- The order creates a logically valid classification system
- Whether this system fully captures biological complexity is a separate question
- Logical validity doesn't require complete biological accuracy

### 7. "Means" vs Exhaustive Definition

Critics might argue that the use of "means" in definitions (d) and (e) makes them exhaustive. However:
- "Means" establishes sufficient conditions without necessarily being exhaustive
- Nothing in the text explicitly excludes other biological criteria
- The framework remains logically consistent while allowing for additional biological evidence

### Key Points

1. The framework is logically consistent:
   - Clear definitions
   - No internal contradictions
   - Maintains temporal consistency
   - Handles edge cases systematically

2. Common criticisms often:
   - Conflate logical and biological arguments
   - Misunderstand the temporal aspect of classification
   - Confuse sufficient with necessary conditions
   - Mix empirical and logical claims

3. The framework:
   - Creates a valid logical system
   - Maintains internal consistency
   - Allows for biological complexity
   - Provides clear classification criteria

This analysis demonstrates that while there may be biological or policy arguments about the framework, it maintains logical coherence and internal consistency.


I'll rewrite this section to incorporate both "unknown" and "sexless" as distinct categories:

## The Necessity of Multiple Classification States

### 1. Three Distinct Categories

1. Sex Classification (Binary)
   * Male or female, determined at conception
   * Based on biological evidence
   * Immutable once determined

2. Sexless Status
   * Distinct from sex classification
   * Based on biological evidence
   * Independent category, not a third sex
   * Immutable once determined

3. Unknown Status
   * Epistemic state about our knowledge
   * Temporary until evidence allows classification
   * Can resolve to either sex classification or sexless status

### 2. Logical Relations

1. Sex and Sexless
   * Mutually exclusive states
   * Both based on biological evidence
   * Both immutable once determined
   * Cannot transition between these states

2. Unknown Classification
   * Reflects insufficient evidence
   * Can resolve to either sex or sexless
   * Temporary by nature
   * Based on absence of conclusive evidence

3. Examples of Classification
   * Sex: Clear evidence of male/female characteristics
   * Sexless: Clear evidence of sexless status
   * Unknown: Incomplete records, inconclusive evidence

### 3. Implementation Framework

1. Evidence Standards
   * Sex Classification: Requires biological evidence of male/female
   * Sexless Status: Requires biological evidence of sexless condition
   * Unknown: Applied when evidence is insufficient

2. Temporal Aspects
   * Initial classification may be unknown
   * Evidence may later establish sex or sexless status
   * Once established, classification is immutable
   * Cannot transition between sex and sexless

3. Practical Applications
   * Default to unknown when evidence is insufficient
   * Require clear standards for each classification
   * Maintain documentation requirements
   * Establish appeals process

### 4. Logical Properties

1. Framework Requirements
   * Sex remains strictly binary
   * Sexless is a distinct status
   * Unknown reflects knowledge limitations
   * All states based on biological evidence

2. Classification Integrity
   * No overlap between categories
   * Clear criteria for each state
   * Immutability once determined
   * Evidence-based transitions from unknown

3. System Coherence
   * Maintains logical consistency
   * Preserves binary nature of sex
   * Accommodates biological reality
   * Handles epistemic limitations

### Key Points

1. Distinct Categories
   * Sex (male/female) as binary classification
   * Sexless as separate biological status
   * Unknown as epistemic state

2. Logical Structure
   * Categories are mutually exclusive
   * Each has clear evidence requirements
   * Unknown can resolve to either sex or sexless
   * All classifications immutable once determined

3. Implementation
   * Clear standards for each category
   * Evidence-based classification
   * Documentation requirements
   * Appeals process

This framework maintains logical consistency while accurately reflecting both biological reality and epistemological limitations. It preserves the binary nature of sex while acknowledging both sexless status and unknown classifications as distinct concepts.


### Unknown Proof

```datalog=
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% DATALOG PRIMER:
% 1. Facts are simple statements like: human(john). meaning "john is a human"
% 2. Rules use :- to mean "IF"
% 3. Capital letters are variables that can match any value
% 4. Constraints show what's not allowed
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%% SECTION 1: BASIC FACTS %%%

% Define types of reproductive cells
reproductive_cell(large).    % Means: "large is a type of reproductive cell"
reproductive_cell(small).    % Means: "small is a type of reproductive cell"

% Define sex categories (binary)
sex_category(female).
sex_category(male).

% Define age categories
age_category(adult).
age_category(juvenile).

% Define classification status types
classification_status(known).
classification_status(unknown).

% Define sexless status (separate from sex)
has_sexless_status(X) :- has_biological_evidence_of_sexless(X).

%%% SECTION 2: CLASSIFICATION RULES %%%

% Rule 1: If someone produces large reproductive cells, they are female
sex(X, female) :- produces_cell(X, large).
classification_known(X) :- produces_cell(X, large).

% Rule 2: If someone produces small reproductive cells, they are male
sex(X, male) :- produces_cell(X, small).
classification_known(X) :- produces_cell(X, small).

% Rule 3: Other biological evidence can determine sex
sex(X, female) :- has_biological_evidence_of_sex(X, female).
classification_known(X) :- has_biological_evidence_of_sex(X, female).
sex(X, male) :- has_biological_evidence_of_sex(X, male).
classification_known(X) :- has_biological_evidence_of_sex(X, male).

% Rule 4: Classification is unknown if no conclusive biological evidence exists
classification_unknown(X) :- 
    human(X),
    not classification_known(X),
    not has_sexless_status(X).

% Rules for age-based categories when sex is known
woman(X) :- sex(X, female), age(X, adult), classification_known(X).
man(X) :- sex(X, male), age(X, adult), classification_known(X).
girl(X) :- sex(X, female), age(X, juvenile), classification_known(X).
boy(X) :- sex(X, male), age(X, juvenile), classification_known(X).

% Rules for sexless categories
sexless_adult(X) :- has_sexless_status(X), age(X, adult).
sexless_juvenile(X) :- has_sexless_status(X), age(X, juvenile).

% Rules for unknown classifications
unknown_adult(X) :- classification_unknown(X), age(X, adult).
unknown_juvenile(X) :- classification_unknown(X), age(X, juvenile).

%%% SECTION 3: INTEGRITY CONSTRAINTS %%%

% Constraint 1: No person can have two different sexes
:- sex(X, S1), sex(X, S2), S1 != S2.

% Constraint 2: Sex classification cannot change over time
:- sex(X, S1, T1), sex(X, S2, T2), S1 != S2.

% Constraint 3: Sexless status cannot change over time
:- has_sexless_status(X, T1), not has_sexless_status(X, T2), T1 != T2.

% Constraint 4: One age category per person
:- age(X, A1), age(X, A2), A1 != A2.

% Constraint 5: Cannot be both sexed and sexless
:- sex(X, _), has_sexless_status(X).

% Constraint 6: Cannot be both known and unknown
:- classification_known(X), classification_unknown(X).

% Constraint 7: Cannot be both unknown and sexless
:- classification_unknown(X), has_sexless_status(X).

% Constraint 8: Categories must be mutually exclusive
:- woman(X), man(X).
:- woman(X), girl(X).
:- woman(X), boy(X).
:- woman(X), sexless_adult(X).
:- woman(X), sexless_juvenile(X).
:- woman(X), unknown_adult(X).
:- woman(X), unknown_juvenile(X).
:- man(X), girl(X).
:- man(X), boy(X).
:- man(X), sexless_adult(X).
:- man(X), sexless_juvenile(X).
:- man(X), unknown_adult(X).
:- man(X), unknown_juvenile(X).
:- girl(X), boy(X).
:- girl(X), sexless_adult(X).
:- girl(X), sexless_juvenile(X).
:- girl(X), unknown_adult(X).
:- girl(X), unknown_juvenile(X).
:- boy(X), sexless_adult(X).
:- boy(X), sexless_juvenile(X).
:- boy(X), unknown_adult(X).
:- boy(X), unknown_juvenile(X).
:- sexless_adult(X), sexless_juvenile(X).
:- sexless_adult(X), unknown_adult(X).
:- sexless_adult(X), unknown_juvenile(X).
:- sexless_juvenile(X), unknown_adult(X).
:- sexless_juvenile(X), unknown_juvenile(X).
:- unknown_adult(X), unknown_juvenile(X).

% Rule to check if someone's classification is incomplete
incomplete_classification(X) :- 
    human(X),
    not woman(X),
    not man(X),
    not girl(X),
    not boy(X),
    not sexless_adult(X),
    not sexless_juvenile(X),
    not unknown_adult(X),
    not unknown_juvenile(X).

% Constraint 9: Every person must have a complete classification
:- human(X), incomplete_classification(X).

%%% SECTION 4: EXAMPLE DATA %%%

% Example 1: Person with clear female classification
human(person1).
produces_cell(person1, large).
age(person1, adult).
% Will be classified as female and thus a woman

% Example 2: Person with biological evidence of being male
human(person2).
has_biological_evidence_of_sex(person2, male).
age(person2, juvenile).
% Will be classified as male and thus a boy

% Example 3: Person with evidence of being sexless
human(person3).
has_biological_evidence_of_sexless(person3).
age(person3, adult).
% Will be classified as sexless_adult

% Example 4: Person with unknown classification
human(person4).
age(person4, adult).
% Will be classified as unknown_adult due to lack of evidence

%%% SECTION 5: VERIFICATION QUERIES %%%

% Find all classifications
?- woman(X).
?- man(X).
?- girl(X).
?- boy(X).
?- sexless_adult(X).
?- sexless_juvenile(X).
?- unknown_adult(X).
?- unknown_juvenile(X).

% Verify no multiple classifications
?- woman(X), (man(X); girl(X); boy(X); sexless_adult(X); sexless_juvenile(X); unknown_adult(X); unknown_juvenile(X)).

% Verify no incomplete classifications
?- human(X), incomplete_classification(X).

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% KEY DIFFERENCES IN THIS VERSION:
%
% 1. Sex is strictly binary:
%    - Only male and female are sex categories
%    - Sexless is a separate biological status
%
% 2. Three distinct concepts:
%    - Sex (male/female) - biological sex classification
%    - Sexless - biological status outside sex classification
%    - Unknown - epistemic state about classification
%
% 3. Classification system:
%    - Sex classification when evidence of male/female exists
%    - Sexless status when evidence of sexless exists
%    - Unknown status when evidence is insufficient
%
% 4. Integrity maintained through:
%    - Cannot be both sexed and sexless
%    - Cannot be both known and unknown
%    - Cannot be both unknown and sexless
%    - All classifications remain immutable
%
% 5. Key conceptual points:
%    - Sex remains binary (male/female only)
%    - Sexless is not a sex category
%    - Unknown reflects lack of knowledge
%    - All states based on biological evidence
%    - No self-identification involved
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


```