<p>Conceptual engineering is the practice of revising concepts to improve how people talk and think. Its ability to improve talk and thought ultimately hinges on the successful dissemination of desired conceptual changes. Unfortunately, the field has been slow to develop methods to directly test what barriers stand in the way of propagation and what methods will most effectively propagate desired conceptual change. In order to test such questions, this paper introduces the masked time-lagged method. The masked time-lagged method tests people’s concepts at a later time than the intervention without participant’s knowledge, allowing us to measure conceptual revision in action. Using a masked time-lagged design on a content internalist framework, we attempted to revise <span>planet</span> and <span>dinosaur</span> in online participants to match experts’ concepts. We successfully revised <span>planet</span> but not <span>dinosaur</span>, demonstrating some of the difficulties conceptual engineers face. Nonetheless, this paper provides conceptual engineers, regardless of framework, with the tools to tackle questions related to implementation empirically and head-on.</p>

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Conceptual Revision in Action

  • Ethan Landes,
  • Kevin Reuter

摘要

Conceptual engineering is the practice of revising concepts to improve how people talk and think. Its ability to improve talk and thought ultimately hinges on the successful dissemination of desired conceptual changes. Unfortunately, the field has been slow to develop methods to directly test what barriers stand in the way of propagation and what methods will most effectively propagate desired conceptual change. In order to test such questions, this paper introduces the masked time-lagged method. The masked time-lagged method tests people’s concepts at a later time than the intervention without participant’s knowledge, allowing us to measure conceptual revision in action. Using a masked time-lagged design on a content internalist framework, we attempted to revise planet and dinosaur in online participants to match experts’ concepts. We successfully revised planet but not dinosaur, demonstrating some of the difficulties conceptual engineers face. Nonetheless, this paper provides conceptual engineers, regardless of framework, with the tools to tackle questions related to implementation empirically and head-on.