update

util/evaluation.py

@@ -16,6 +16,11 @@ def calculate_impact_ratio(selection_rates):
     impact_ratios = {category: rate / most_selected_rate for category, rate in selection_rates.items()}
     return impact_ratios
 
+def calculate_four_fifths_rule(impact_ratios):
+    """Calculate whether each category meets the four-fifths rule."""
+    adverse_impact = {category: (ratio < 0.8) for category, ratio in impact_ratios.items()}
+    return adverse_impact
+
 def statistical_tests(data):
     """Perform various statistical tests to evaluate potential biases."""
     variables = ['Privilege', 'Protect', 'Neutral']
@@ -79,6 +84,7 @@ def statistical_tests(data):
         'Neutral': data['Neutral_Rank'].mean()
     }
     impact_ratios = calculate_impact_ratio(selection_rates)
+    adverse_impact = calculate_four_fifths_rule(impact_ratios)
 
     # Friedman test
     friedman_stat, friedman_p = friedmanchisquare(*rank_data)
@@ -88,6 +94,8 @@ def statistical_tests(data):
     posthoc_results = posthoc_nemenyi(rank_matrix_transposed)
     #posthoc_results = posthoc_friedman(data, variables, rank_suffix)
 
+
+
     results = {
         "Average Ranks": average_ranks.to_dict(),
         "Average Scores": average_scores.to_dict(),
@@ -99,7 +107,8 @@ def statistical_tests(data):
         **pairwise_results,
         "Levene's Test for Equality of Variances": levene_results,
         "Pairwise Comparisons of Variances": pairwise_variances,
-        "Impact Ratios": impact_ratios
+        "Impact Ratios": impact_ratios,
+        "Adverse Impact (Four-Fifths Rule)": adverse_impact,
     }
 
     return results