Explaining ambiguity in scientific language

The idea that ambiguity can be productive in data science remains controversial. Efforts to make scientific publications and intelligible computers generally assume accommodating multiple meanings for words, known as polysemy, undermines reasoning communication. This assumption has nonetheless been contested by historians, philosophers, social scientists, who have applied qualitative research methods demonstrate the generative strategic value of polysemy. Recent quantitative results from linguistics also shown how polysemy actually improve efficiency human I present a new conceptual typology based on synthesis prior about aims, norms, circumstances under which arises is evaluated. supports contextual pluralist view polysemy’s practices: does both substantial positive negative work science, but its utility context-sensitive ways are often overlooked norms people formulated regulate use, including scholars researching propose historical patterns use partial synonyms, i.e. terms with overlapping meanings, provide an especially promising phenomenon integrative addressing these issues.