Image Databases for Facial Analysis Coded for Race and Gender Features

<p>&nbsp;</p> <p>This document consists of the corpus of image databases examined for race and gender information as published in:</p> <p><em>Morgan Klaus Scheuerman, Kandrea Wade, Caitlin Lustig, and Jed R. Brubaker. 2020. How We&rsquo;ve Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis. Proc. ACM Hum.-Comput. CSCW. </em></p> <p>This code book includes:</p> <p>1. Whether race/gender is present implicitly (as descriptive, but not annotated) or explicitly (annotated/labeled).&nbsp;</p> <p>2. What categories or descriptions of race/gender are used.</p> <p>3. Whether those categories/descriptions use underlying source material to justify or motivate their descriptions of race/gender.</p> <p>4. Whether explicitly annotated databases describe the process of annotating race/gender.</p>