label_dicts.py

CAP_NUM_DICT = {
    0: 1,
    1: 2,
    2: 3,
    3: 4,
    4: 5,
    5: 6,
    6: 7,
    7: 8,
    8: 9,
    9: 10,
    10: 12,
    11: 13,
    12: 14,
    13: 15,
    14: 16,
    15: 17,
    16: 18,
    17: 19,
    18: 20,
    19: 21,
    20: 23,
    21: 999,
    22: 999, # had to do this because of some language-domain models (e.g. english media)
}

CAP_MIN_NUM_DICT = {
    0: 100,
    1: 101,
    2: 103,
    3: 104,
    4: 105,
    5: 107,
    6: 108,
    7: 110,
    8: 199,
    9: 200,
    10: 201,
    11: 202,
    12: 204,
    13: 205,
    14: 206,
    15: 207,
    16: 208,
    17: 209,
    18: 299,
    19: 300,
    20: 301,
    21: 302,
    22: 321,
    23: 322,
    24: 323,
    25: 324,
    26: 325,
    27: 331,
    28: 332,
    29: 333,
    30: 334,
    31: 335,
    32: 341,
    33: 342,
    34: 398,
    35: 399,
    36: 400,
    37: 401,
    38: 402,
    39: 403,
    40: 404,
    41: 405,
    42: 408,
    43: 498,
    44: 499,
    45: 500,
    46: 501,
    47: 502,
    48: 503,
    49: 504,
    50: 505,
    51: 506,
    52: 529,
    53: 599,
    54: 600,
    55: 601,
    56: 602,
    57: 603,
    58: 604,
    59: 606,
    60: 607,
    61: 698,
    62: 699,
    63: 700,
    64: 701,
    65: 703,
    66: 704,
    67: 705,
    68: 707,
    69: 708,
    70: 709,
    71: 711,
    72: 798,
    73: 799,
    74: 800,
    75: 801,
    76: 802,
    77: 803,
    78: 805,
    79: 806,
    80: 807,
    81: 898,
    82: 899,
    83: 900,
    84: 1000,
    85: 1001,
    86: 1002,
    87: 1003,
    88: 1005,
    89: 1007,
    90: 1010,
    91: 1098,
    92: 1099,
    93: 1200,
    94: 1201,
    95: 1202,
    96: 1203,
    97: 1204,
    98: 1205,
    99: 1206,
    100: 1207,
    101: 1208,
    102: 1210,
    103: 1211,
    104: 1227,
    105: 1299,
    106: 1300,
    107: 1302,
    108: 1303,
    109: 1304,
    110: 1305,
    111: 1308,
    112: 1399,
    113: 1400,
    114: 1401,
    115: 1403,
    116: 1404,
    117: 1405,
    118: 1406,
    119: 1407,
    120: 1408,
    121: 1409,
    122: 1498,
    123: 1499,
    124: 1500,
    125: 1501,
    126: 1502,
    127: 1504,
    128: 1505,
    129: 1507,
    130: 1520,
    131: 1521,
    132: 1522,
    133: 1523,
    134: 1524,
    135: 1525,
    136: 1526,
    137: 1598,
    138: 1599,
    139: 1600,
    140: 1602,
    141: 1603,
    142: 1604,
    143: 1605,
    144: 1606,
    145: 1608,
    146: 1610,
    147: 1611,
    148: 1612,
    149: 1614,
    150: 1615,
    151: 1616,
    152: 1617,
    153: 1619,
    154: 1620,
    155: 1698,
    156: 1699,
    157: 1700,
    158: 1701,
    159: 1704,
    160: 1705,
    161: 1706,
    162: 1707,
    163: 1708,
    164: 1709,
    165: 1798,
    166: 1799,
    167: 1800,
    168: 1802,
    169: 1803,
    170: 1804,
    171: 1806,
    172: 1807,
    173: 1808,
    174: 1899,
    175: 1900,
    176: 1901,
    177: 1902,
    178: 1905,
    179: 1906,
    180: 1910,
    181: 1921,
    182: 1925,
    183: 1926,
    184: 1927,
    185: 1929,
    186: 1999,
    187: 2000,
    188: 2001,
    189: 2002,
    190: 2003,
    191: 2004,
    192: 2005,
    193: 2006,
    194: 2007,
    195: 2008,
    196: 2009,
    197: 2010,
    198: 2011,
    199: 2012,
    200: 2013,
    201: 2014,
    202: 2015,
    203: 2030,
    204: 2099,
    205: 2100,
    206: 2101,
    207: 2102,
    208: 2103,
    209: 2104
}

CAP_LABEL_NAMES = {
    1: "Macroeconomics",
    2: "Civil Rights",
    3: "Health",
    4: "Agriculture",
    5: "Labor",
    6: "Education",
    7: "Environment",
    8: "Energy",
    9: "Immigration",
    10: "Transportation",
    12: "Law and Crime",
    13: "Social Welfare",
    14: "Housing",
    15: "Domestic Commerce",
    16: "Defense",
    17: "Technology",
    18: "Foreign Trade",
    19: "International Affairs",
    20: "Government Operations",
    21: "Public Lands",
    23: "Culture",
    999: "No Policy Content"
}

CAP_MIN_LABEL_NAMES = {
    # 1. Macroeconomics
    100: "General",
    101: "Interest Rates",
    103: "Unemployment Rate",
    104: "Monetary Policy",
    105: "National Budget",
    107: "Tax Code",
    108: "Industrial Policy",
    110: "Price Control",
    199: "Other",
    # 2. Civil Rights
    200: "General",
    201: "Minority Discrimination",
    202: "Gender Discrimination",
    204: "Age Discrimination",
    205: "Handicap Discrimination",
    206: "Voting Rights",
    207: "Freedom of Speech",
    208: "Right to Privacy",
    209: "Anti-Government",
    299: "Other",
    # 3. Health
    300: "General",
    301: "Health Care Reform",
    302: "Insurance",
    321: "Drug Industry",
    322: "Medical Facilities",
    323: "Insurance Providers",
    324: "Medical Liability",
    325: "Manpower",
    331: "Disease Prevention",
    332: "Infants and Children",
    333: "Mental Health",
    334: "Long-term Care",
    335: "Drug Coverage and Cost",
    341: "Tobacco Abuse",
    342: "Drug and Alcohol Abuse",
    398: "R&D",
    399: "Other",
    # 4. Agriculture
    400: "General",
    401: "Trade",
    402: "Subsidies to Farmers",
    403: "Food Inspection & Safety",
    404: "Food Marketing & Promotion",
    405: "Animal and Crop Disease",
    408: "Fisheries & Fishing",
    498: "R&D",
    499: "Other",
    # 5. Labor
    500: "General",
    501: "Worker Safety",
    502: "Employment Training",
    503: "Employee Benefits",
    504: "Labor Unions",
    505: "Fair Labor Standards",
    506: "Youth Employment",
    529: "Migrant and Seasonal",
    599: "Other",
    # 6. Education
    600: "General",
    601: "Higher",
    602: "Elementary & Secondary",
    603: "Underprivileged",
    604: "Vocational",
    606: "Special",
    607: "Excellence",
    698: "R&D",
    699: "Other",
    # 7. Environment
    700: "General",
    701: "Drinking Water",
    703: "Waste Disposal",
    704: "Hazardous Waste",
    705: "Air Pollution",
    707: "Recycling",
    708: "Indoor Hazards",
    709: "Species & Forest",
    711: "Land and Water Conservation",
    798: "R&D",
    799: "Other",
    # 8. Energy
    800: "General",
    801: "Nuclear",
    802: "Electricity",
    803: "Natural Gas & Oil",
    805: "Coal",
    806: "Alternative & Renewable",
    807: "Conservation",
    898: "R&D",
    899: "Other",
    # 9. Immigration
    900: "Immigration",
    # 10. Transportation
    1000: "General",
    1001: "Mass",
    1002: "Highways",
    1003: "Air Travel",
    1005: "Railroad Travel",
    1007: "Maritime",
    1010: "Infrastructure",
    1098: "R&D",
    1099: "Other",
    # 12. Law and Crime
    1200: "General",
    1201: "Agencies",
    1202: "White Collar Crime",
    1203: "Illegal Drugs",
    1204: "Court Administration",
    1205: "Prisons",
    1206: "Juvenile Crime",
    1207: "Child Abuse",
    1208: "Family Issues",
    1210: "Criminal & Civil Code",
    1211: "Crime Control",
    1227: "Police",
    1299: "Other",
    # 13. Social Welfare
    1300: "General",
    1302: "Low-Income Assistance",
    1303: "Elderly Assistance",
    1304: "Disabled Assistance",
    1305: "Volunteer Associations",
    1308: "Child Care",
    1399: "Other",
    # 14. Housing
    1400: "General",
    1401: "Community Development",
    1403: "Urban Development",
    1404: "Rural Housing",
    1405: "Rural Development",
    1406: "Low-Income Assistance",
    1407: "Veterans",
    1408: "Elderly",
    1409: "Homeless",
    1498: "R&D",
    1499: "Other",
    # 15. Domestic Commerce
    1500: "General",
    1501: "Banking",
    1502: "Securities & Commodities",
    1504: "Consumer Finance",
    1505: "Insurance Regulation",
    1507: "Bankruptcy",
    1520: "Corporate Management",
    1521: "Small Businesses",
    1522: "Copyrights and Patents",
    1523: "Disaster Relief",
    1524: "Tourism",
    1525: "Consumer Safety",
    1526: "Sports Regulation",
    1598: "R&D",
    1599: "Other",
    # 16. Defense
    1600: "General",
    1602: "Alliances",
    1603: "Intelligence",
    1604: "Readiness",
    1605: "Nuclear Arms",
    1606: "Military Aid",
    1608: "Personnel Issues",
    1610: "Procurement",
    1611: "Installations & Land",
    1612: "Reserve Forces",
    1614: "Hazardous Waste",
    1615: "Civil",
    1616: "Civilian Personnel",
    1617: "Contractors",
    1619: "Foreign Operations",
    1620: "Claims against Military",
    1698: "R&D",
    1699: "Other",
    # 17. Technology
    1700: "General",
    1701: "Space",
    1704: "Commercial Use of Space",
    1705: "Science Transfer",
    1706: "Telecommunications",
    1707: "Broadcast",
    1708: "Weather Forecasting",
    1709: "Computers",
    1798: "R&D",
    1799: "Other",
    # 18. Foreign Trade
    1800: "General",
    1802: "Trade Agreements",
    1803: "Exports",
    1804: "Private Investments",
    1806: "Competitiveness",
    1807: "Tariff & Imports",
    1808: "Exchange Rates",
    1899: "Other",
    # 19. International Affairs
    1900: "General",
    1901: "Foreign Aid",
    1902: "Resources Exploitation",
    1905: "Developing Countries",
    1906: "International Finance",
    1910: "Western Europe",
    1921: "Specific Country",
    1925: "Human Rights",
    1926: "Organizations",
    1927: "Terrorism",
    1929: "Diplomats",
    1999: "Other",
    # 20. Government Operations
    2000: "General",
    2001: "Intergovernmental Relations",
    2002: "Bureaucracy",
    2003: "Postal Service",
    2004: "Employees",
    2005: "Appointments",
    2006: "Currency",
    2007: "Procurement & Contractors",
    2008: "Property Management",
    2009: "Tax Administration",
    2010: "Scandals",
    2011: "Branch Relations",
    2012: "Political Campaigns",
    2013: "Census & Statistics",
    2014: "Capital City",
    2015: "Claims against the government",
    2030: "National Holidays",
    2099: "Other",
    # 21. Public Lands
    2100: "General",
    2101: "National Parks",
    2102: "Indigenous Affairs",
    2103: "Public Lands",
    2104: "Water Resources",
    2105: "Dependencies & Territories",
    2199: "Other",
    # 23. Culture
    2300: "General",
    # NPC
    9999: "No Policy Content",
}

MANIFESTO_LABEL_NAMES = {
    0: "No Policy Goal",
    999: "No Policy Goal",
    101: "Foreign Special Relationships: Positive",
    102: "Foreign Special Relationships: Negative",
    103: "Anti-Imperialism",
    104: "Military: Positive",
    105: "Military: Negative",
    106: "Peace",
    107: "Internationalism: Positive",
    108: "European Community/Union: Positive",
    109: "Internationalism: Negative",
    110: "European Community/Union: Negative",
    201: "Freedom and Human Rights",
    202: "Democracy",
    203: "Constitutionalism: Positive",
    204: "Constitutionalism: Negative",
    301: "Federalism",
    302: "Centralisation",
    303: "Governmental and Administrative Efficiency",
    304: "Political Corruption",
    305: "Political Authority",
    401: "Free Market Economy",
    402: "Incentives",
    403: "Market Regulation",
    404: "Economic Planning",
    405: "Corporatism/Mixed Economy",
    406: "Protectionism: Positive",
    407: "Protectionism: Negative",
    408: "Economic Goals",
    409: "Keynesian Demand Management",
    410: "Economic Growth: Positive",
    411: "Technology and Infrastructure",
    412: "Controlled Economy",
    413: "Nationalisation",
    414: "Economic Orthodoxy",
    415: "Marxist Analysis: Positive",
    416: "Anti-Growth Economy: Positive",
    501: "Environmental Protection: Positive",
    502: "Culture: Positive",
    503: "Equality: Positive",
    504: "Welfare State Expansion",
    505: "Welfare State Limitation",
    506: "Education Expansion",
    507: "Education Limitation",
    601: "National Way of Life: Positive",
    602: "National Way of Life: Negative",
    603: "Traditional Morality: Positive",
    604: "Traditional Morality: Negative",
    605: "Law and Order: Positive",
    606: "Civic Mindedness: Positive",
    607: "Multiculturalism: Positive",
    608: "Multiculturalism: Negative",
    701: "Labour Groups: Positive",
    702: "Labour Groups: Negative",
    703: "Agriculture and Farmers: Positive",
    704: "Middle Class and Professional Groups",
    705: "Underprivileged Minority Groups",
    706: "Non-economic Demographic Groups"
}

ILLFRAMES_MIGRATION_LABEL_NAMES = {
    901: "Culture Under Attack",
    902: "Economic Burden",
    903: "Illegals and Fraudsters",
    904: "Extradition Necessity",
    905: "Nation tate Should Decide",
    906: "Administrative Burden",
    907: "General System Failure",
    908: "Security Threat",
    909: "Criminals",
    910: "Welfare State Overload",
    999: "None of Them",
}

ILLFRAMES_COVID_LABEL_NAMES = {
    310: "Skepticism",
    311: "Great Reset and Elite Control",
    312: "Undermining the Economy",
    313: "Medical Choice",
    314: "Media Fabrication",
    315: "Threatening Way of Life",
    399: "None of Them",
}

ILLFRAMES_WAR_LABEL_NAMES = {
    101: 'Identity and Cultural Threat',
    102: 'Economic Fallout/Domestic Welfare Neglected',
    103: 'Violation of Russian Sovereignty/Western geopolitical meddling',
    104: 'Illegitimate and corrupt Ukraine leadership',
    105: 'Ukrainians and Ukraine are a military threat and agressive war-mongerer that threaten EU stability and security',
    107: 'Western Propaganda and Civilian Suffering',
    108: 'Historical Betrayal of Russia',
    109: 'Ukraine/Nazi Allegation',
    110: "None of Them"
}

ONTOLISST_LABEL_NAMES = {
    0: 'Demographics',
    1: 'Housing and local environment (Housing and environment)',
    2: 'Physical health',
    3: 'Mental health and mental processes',
    4: 'Healthcare',
    5: 'Health behaviour (Health and lifestyle)',
    6: 'Family and social networks',
    7: 'Education',
    8: 'Employment and income (Employment and pensions)',
    9: 'Expectation, attitudes and beliefs (Attitudes and beliefs)',
    10: 'Child development',
    11: 'Life events',
    12: 'Omics',
    13: 'Pregnancy',
    14: 'Administration',
    15: 'COVID19'
}
EMOTION9_LABEL_NAMES = {
    0: "Anger",
    1: "Fear",
    2: "Disgust",
    3: "Sadness",
    4: "Joy",
    5: "Enthusiasm",
    6: "Hope",
    7: "Pride",
    8: "None of Them",
}