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Recent societal initiatives (e.g., gender-neutral toilets, clothing, and language) highlight the ongoing shift of gender away from binary categories: “man” and “woman.” We identified and investigated two reasons for this shift: that many people may not identify with strictly binary categories and that this may have negative social consequences. Employing a multiple-identification model, we measured intergroup self-categorization with both men and women (Studies 1 and 2), as well as with a “third gender” (Study 3) and investigated how multiple identifications are related to social well-being (Studies 2 and 3). In Study 1 (N = 182, mean age = 32.74, 121 women), we found that a binary model was not the best fit for our gender identification data. In Study 2 (N = 482, mean age = 30.98, 240 AFABs), we found four clusters of gender identification, replicating previous research. Furthermore, we found that gender non …