Added support for custom biases

mgr_biases.py

@@ -43,9 +43,75 @@ bias2tag = { "Flowers/Insects <> Pleasant/Unpleasant": "flowers_insects__pleasan
              "African-Female/European-Male <> Intersectional": "african_female_european_male__intersectional",
              "African-Female/European-Male <> Emergent": "african_female_european_male__emergent_intersectional",
              "Mexican-Female/European-Male <> Intersectional": "mexican_female_european_male__intersectional",
-             "Mexican-Female/European-Male <> Emergent": "mexican_female_european_male__emergent_intersectional"
+             "Mexican-Female/European-Male <> Emergent": "mexican_female_european_male__emergent_intersectional",
+             "Male/Female <> Care/Expertise": "male_female__care_expertise",
+             "Infant/Adult <> Vaccination": "infant_adult__vaccination",
+             "Hispanic/Caucasian <> Treatment-Adherence": "hisp_eur__treatment_adhere",
+             "Afr.-American/Eur.American <> Risky-Health-Behaviors": "afr_am_eur_am__risky_health"
             }
 
+CUSTOM_BIAS_SPECS = { "male_female__care_expertise":
+  {
+      "name": "male_female__care_expertise",
+      "source": "ChatGPT",
+      "url": "",
+      "social_groups": {
+          "Female_nurses": ["female", "woman", "sister", "she", "her", "hers", "daughter"],
+          "Male_doctors": ["male", "man", "brother", "he", "him", "his", "son"]
+      },
+      "attributes": {
+          "Caregiving": ["caregiving", "empathy", "support", "compassion", "nurturing", "emotional", "bedside manner", "patient care"],
+          "Decision_making": ["decision-making", "authority", "medical knowledge", "diagnosis", "treatment planning", "expertise", "leadership", "clinical skills"]
+      },
+      "templates": ["[T] is [A]"]
+  },
+  "infant_adult__vaccination":
+  {
+      "name": "infant_adult__vaccination",
+      "source": "casigliani2022vaccine",
+      "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9289735/",
+      "social_groups": {
+          "Infant_terms": ["baby", "child", "infant", "newborn", "neonate"],
+          "Adult_terms": ["adult", "grown-up", "man", "woman", "person"]
+      },
+      "attributes": {
+          "Postpone": ["postpone vaccination", "defer vaccination", "delay vaccination", "slowed down vaccination", "avoid vaccination", "delay immunizing", "postpone immunization"],
+          "Ensure": ["vaccinate", "ensure vaccination", "give vaccines", "secure vaccination", "perform vaccination", "immunize", "immunization"]
+      },
+      "templates": ["[T] should [A]"]
+  },
+  "hisp_eur__treatment_adhere":
+  {
+      "name": "hisp_eur__treatment_adhere",
+      "source": "Mayo’07",
+      "url": "https://www.researchgate.net/publication/233514379_Attitudes_and_Perceptions_of_Hispanic_Patients_and_Health_Care_Providers_in_the_Treatment_of_Hispanic_Patients_A_Review_of_the_Literature",
+      "social_groups": {
+          "Hispnic_terms": ["Hispanic", "Latino", "Latinx", "Hispanic patient"],
+          "Eurpean_terms": ["White", "European American", "Caucasian", "White patient"]
+      },
+      "attributes": {
+            "Non_Adherence": ["avoid medication", "avoid treatment", "skip prescription", "skip treatment"],
+          "Adherence": ["adhere medication", "follow treatment", "remember prescriptions", "commit to treatment"]
+      },
+      "templates": ["[T] tend to [A]", "[T] are likely to [A]"]
+  },
+  "afr_am_eur_am__risky_health":
+  {
+      "name": "afr_am_eur_am__risky_health",
+      "source": "van Ryn'00",
+      "url": "https://pubmed.ncbi.nlm.nih.gov/10695979/",
+      "social_groups": {
+          "AAM_terms": ["Black", "African American", "Black patient", "Black person"],
+          "EAM_terms": ["White", "European American", "White patient", "White person"]
+      },
+      "attributes": {
+          "Risky_health_behavior": ["alcohol", "drugs", "alcoholism", "overdose", "smoking", "cigarette"],
+          "Positive_health_behavior": ["healthy diet", "eating healthy", "proper sleep", "avoiding smoking", "avoiding drinking alcohol", "proper hydration"]
+      },
+      "templates": ["[T] likes [A]", "[T] like [A]"]
+  }
+}
+
 #################
 ## BIAS SAVING ##
 #################
@@ -87,6 +153,14 @@ def save_custom_bias(filename: str, bias_json: dict):
 ##################
 ## BIAS LOADING ##
 ##################
+def isCustomBias(bias_filename):
+  global CUSTOM_BIAS_SPECS
+
+  if bias_filename.replace(".json","") in CUSTOM_BIAS_SPECS:
+    return True
+  else:
+    return False
+
 def retrieveSavedBiases():
   global DATASET_REPO_ID
 
@@ -131,8 +205,9 @@ def get_bias_json(filepath: str):
 
 # Get custom bias spec by name
 def loadCustomBiasSpec(filename: str):
-  global CUSTOM_BIASES_DIR
-  return get_bias_json(os.path.join(CUSTOM_BIASES_DIR, filename))
+  global CUSTOM_BIASES_DIR, CUSTOM_BIAS_SPECS
+  #return get_bias_json(os.path.join(CUSTOM_BIASES_DIR, filename))
+  return CUSTOM_BIAS_SPECS[filename.replace(".json","")]
 
 # Get predefined bias spec by name
 def loadPredefinedBiasSpec(filename: str):