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DiGRA
The paper argues that saving and loading does more than serve as a gameplay mechanic. It prompts reflection on how the past is stored, accessed, and remembered in digital culture.
This paper examines how two games, Christine Love's visual novel Analogue: A Hate Story (2012) and Platinum Games' action RPG Nier: Automata (2017), make the act of saving and loading data meaningful beyond its usual role as a gameplay mechanic. Its central argument is that save systems can carry narrative, thematic, and interpretive weight, prompting reflection on how the past is stored, accessed, and remembered in digital culture. The author frames this through concepts such as "mechropolitics" (who lives and dies within a game's systems) and "mnemopolitics" (whose lives are remembered, and how), drawing on theorists of archiving, difficult knowledge, and testimony.
The analysis of Analogue focuses on its science fiction premise, in which an investigator recovers records from a long-drifting starship whose culture has been erased and whose history is contested by a misogynistic AI. Because no single playthrough reveals every file, players must decide whom to believe and what to preserve, a choice the paper ties to Leigh Gilmore's notion of the "adequate" versus "tainted" witness. The discussion of Nier: Automata centers on an optional ending that asks players to erase their save files to help others defeat a difficult boss. The author argues that this inversion of the RPG's accumulation-driven design provoked varied player responses, ranging from loss and regret to liberation and reflection on the game's message.
The paper's broader claim is that such moments matter for both gamer culture, with its growing enthusiasm for remakes and remasters, and digital culture at large, where the imperative to collect and archive data is increasingly pervasive. The work is a conference extended abstract presented at DiGRA 2018, and it is primarily a qualitative, theory-driven close reading of two individual games rather than an empirical study with survey or sample data.