Beyond heteronormativity: counternarratives of love, kinship, and belonging in youth literature

Purpose This paper aims to investigate the evolution of family representations in children’s literature, focusing on the rise of queer narratives and the critical role of chosen families in shaping children’s understanding of familial relationships. Design/methodology/approach Via counter-storytelling, the authors of this work critique limitations embedded throughout traditional family portrayals as well as the implications of these narratives for queer children’s socialization and identity formation. This critique argues that traditional family structures often reinforce heteronormative ideals, whereas, in contrast, an inclusion of queer counter-narratives and chosen families in children’s literature serves to validate diverse experiences and promote inclusivity among young readers. Throughout this piece, the authors use counter-storytelling – as both a method and as an analytic lens, while drawing from critical race theory (Ladson-Billings and Tate, 1995) and queer of color critique (Ferguson, 2004) to center marginalized familial narratives. Together, these critical frameworks function as pedagogical tools for illuminating the lived realities of various individuals outside of dominant norms. Findings The findings showcase how the traditional, nuclear family model depictions often marginalize those who fail to adhere to or fit its limiting structures, thereby leading to feelings of exclusion. In contrast, the inclusion of queer narratives and chosen families in literature fosters acceptance and understanding, providing essential validation for queer youth. This work contributes to existing literature by highlighting chosen families and queer representation in children’s literature as essential in advocating for greater understanding of family dynamics that transcends traditional nuclear model to include chosen families. Originality/value The work presented in this paper is our own. Neither artificial intelligence nor large language models) were used to produce any of the research, findings or writing.