-
Notifications
You must be signed in to change notification settings - Fork 0
/
exemplar.txt
103 lines (87 loc) · 4.29 KB
/
exemplar.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
# Import necessary libraries
import numpy as np
import decision_tree
import bayesian_model
import uplift_metrics
import ethical_decision_making
import cultural_analysis as ca
import emotional_intelligence as ei
import trend_analysis as ta
import cross_cultural_impact as cci
import historical_validation as hv
import social_graph_analysis as sga
import ensemble_modeling as ensemble
import empirical_validation as ev
import temporal_wisdom_model as twm
# Define Functions for Ethical Score Calculation
def calculate_utilitarian_score(actions, cultural_factors):
# Utilitarian calculation logic
def calculate_utilitarian_score(actions, cultural_factors):
# Utilitarian calculation logic
total_utility = 0
for action in actions:
utility = action.impact_on_wellbeing # Hypothetical attribute
cultural_influence = cultural_factors.get(action.context, 1)
beneficence_factor = action.beneficence_score # From evaluate_beneficence
total_utility += utility * cultural_influence * beneficence_factor
return total_utility
def calculate_deontological_score(actions, context, cultural_factors):
# Deontological calculation logic
def calculate_deontological_score(actions, context, cultural_factors):
# Deontological calculation logic
rule_adherence_score = 0
for action in actions:
adherence = action.adherence_to_rules # Hypothetical attribute
cultural_relevance = cultural_factors.get(action.context, 1)
beneficence_factor = action.beneficence_score # From evaluate_beneficence
rule_adherence_score += adherence * cultural_relevance * beneficence_factor
return rule_adherence_score
def calculate_virtue_ethics_score(actions, context, cultural_factors):
# Virtue ethics calculation logic
def calculate_virtue_ethics_score(actions, context, cultural_factors):
# Virtue ethics calculation logic
virtue_score = 0
for action in actions:
virtues = action.expressed_virtues # Hypothetical attribute, a dict of virtue scores
cultural_context_factor = cultural_factors.get(action.context, 1)
beneficence_factor = action.beneficence_score # From evaluate_beneficence
for virtue, score in virtues.items():
virtue_score += score * cultural_context_factor * beneficence_factor
return virtue_score
# Main Function for Analyzing Moral Exemplar
def analyze_moral_exemplar(exemplar, actions, context, cultures, communities, historical_data, time_points):
# Incorporate cultural context in ethical evaluations
cultural_factors = ca.analyze_cultural_context(cultures, actions, context)
# Calculate ethical scores using the three ethical frameworks
utilitarian_score = calculate_utilitarian_score(actions, cultural_factors)
deontological_score = calculate_deontological_score(actions, context, cultural_factors)
virtue_ethics_score = calculate_virtue_ethics_score(actions, context, cultural_factors)
# Ensemble Ethical Score with Cultural Context
ethical_score = ensemble.integrate_scores(utilitarian_score, deontological_score, virtue_ethics_score)
# Emotional Intelligence Metrics
ei_score = ei.evaluate_emotional_intelligence(exemplar)
# Wisdom Trajectory Analysis
wisdom_scores, trend_inflections = ta.analyze_wisdom_trends(exemplar, time_points)
# Social Graph Impact Analysis
cross_cultural_social_impacts = cci.compare_social_graphs(exemplar, communities)
# Empirical Validation with Historical Data
empirical_validation_score = hv.validate_with_expanded_historical_data(exemplar, historical_data)
return {
"EthicalScore": ethical_score,
"EmotionalIntelligenceScore": ei_score,
"WisdomTrajectory": wisdom_scores,
"TrendInflections": trend_inflections,
"CrossCulturalSocialImpacts": cross_cultural_social_impacts,
"EmpiricalValidationScore": empirical_validation_score
}
# Example Usage
exemplar_analysis = analyze_moral_exemplar(
exemplar=example_person,
actions=example_actions,
context=example_context,
cultures=example_cultures,
communities=example_communities,
historical_data=example_historical_data,
time_points=example_time_points
)
print(exemplar_analysis)