Classification Algorithm for Skin Color (CASCo): A new tool to measure skin color in social science research.

Objective: A growing body of literature reveals that skin color has significant effects on people's income, health, education, and employment. However, the ways in which skin color has been measured in empirical research have been criticized for being inaccurate, if not subjective and biased. Object...

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Publicado en:Social Science Quarterly (Wiley-Blackwell) Vol. 104; no. 2; pp. 168 - 180
Autores principales: Rejón Piña, René Alejandro, Ma, Chenglong
Formato: Artículo
Publicado: Wiley-Blackwell Mar2023
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Acceso en línea:Ver este registro en EBSCOhost
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        atl: Classification Algorithm for Skin Color (CASCo): A new tool to measure skin color in social science research.
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        au:
          Rejón Piña, René Alejandro
          Ma, Chenglong
        affil:
          The University of Melbourne, Melbourne Victoria,, Australia
          School of Computer Science and Information Technology, RMIT University, Melbourne Victoria,, Australia
      su:
        Social science research
        Paradigms (Social sciences)
        Human skin color
        Classification algorithms
        Measuring instruments
        K-means clustering
        Content-based image retrieval
      sug:
        subj:
          Social science research
          Paradigms (Social sciences)
          Other Electronic and Precision Equipment Repair and Maintenance
          Other Measuring and Controlling Device Manufacturing
          Instruments and Related Products Manufacturing for Measuring, Displaying, and Controlling Industrial Process Variables
          Research and Development in the Social Sciences and Humanities
          Human skin color
          Classification algorithms
          Measuring instruments
          K-means clustering
          Content-based image retrieval
      keyword:
        colorism
        measurement
        photo elicitation
        racism
        skin color
        spectrometers
        colorism
        measurement
        photo elicitation
        racism
        skin color
        spectrometers
      ab: Objective: A growing body of literature reveals that skin color has significant effects on people's income, health, education, and employment. However, the ways in which skin color has been measured in empirical research have been criticized for being inaccurate, if not subjective and biased. Objective: Introduce an objective, automatic, accessible and customizable Classification Algorithm for Skin Color (CASCo). Methods: We review the methods traditionally used to measure skin color (verbal scales, visual aids or color palettes, photo elicitation, spectrometers and image‐based algorithms), noting their shortcomings. We highlight the need for a different tool to measure skin color Results: We present CASCo, a (social researcher‐friendly) Python library that uses face detection, skin segmentation and k‐means clustering algorithms to determine the skin tone category of portraits. Conclusion: After assessing the merits and shortcomings of all the methods available, we argue CASCo is well equipped to overcome most challenges and objections posed against its alternatives. While acknowledging its limitations, we contend that CASCo should complement researchers. toolkit in this area.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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