class_docstr: Filter samples based on gender bias
  
  for example in mode 'man'::
  
      sample 1: "There is a boy.", score: 1
      sample 2: "There is a girl.", score: 1
      sample 3: "There are boys and girls.", score: 0
docstr: 1 or 0 indicate whether sample fields match mode and prejudice words
  
  :param sample: data sample
  :param list fields: list of field str
  :param kwargs:
  :return int: score for sample
docstr_tok: ["1","or","0","indicate","whether","sample","fields","match","mode","and","prejudice","words",":","param","sample",":","data","sample",":","param","list","fields",":","list","of","field","str",":","param","kwargs",":",":","return","int",":","score","for","sample"]
code: def _score(self, sample, fields, **kwargs):
      r"""
      1 or 0 indicate whether sample fields match mode and prejudice words
  
      :param sample: data sample
      :param list fields: list of field str
      :param kwargs:
      :return int: score for sample
      """
  
      texts = [sample.get_text(field) for field in fields]
      man_match = self.word_match(texts, type="man")
      woman_match = self.word_match(texts, type="woman")
  
      if self.mode == "man":
          return man_match and not woman_match
      elif self.mode == "woman":
          return woman_match and not man_match
      elif self.mode == "both":
          return woman_match and man_match
      else:
          return not woman_match and not man_match
  
file_path: textflint/textflint/generation/subpopulation/UTCN/prejudice.py
imports: from flashtext import KeywordProcessor
  from ..subpopulation import SubPopulation
  from ....common.settings import PREJUDICE_PATH
  from ....common.utils.install import download_if_needed
  from ....common.utils.file_io import read_json
label_desc: Use image node_id 6 for calling the PrejudiceSubPopulation obj's underlying member method code with example usage: obj._score(sample, fields) and returns: unknown, unknown, unknown, unknown