ArticlePloS one2023
Is time an embodied property of concepts?
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Specificity effect in concrete/abstract semantic categorization task.Cognitive processing · 2026Article
- Specificity ratings for English data.Cognitive processing · 2025Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A haircut usually lasts under an hour. But how long does it take to recognize that something is an instance of a haircut? And is this "time-to-perceive" a part of the representation of concepts like haircut? Across three experiments testing lexical decision, word recognition, and semantic decision, we show that the amount of time people say it takes to perceive a concept in the world (e.g., haircut, dandelion, or merit) predicts how long it takes for them to respond to a word referring to that thing, over and above the effects of other lexical-semantic variables (e.g., word frequency, concreteness) and other variables related to conceptual complexity (e.g., how confusable a concept is with other, similar concepts, or the diversity of the contexts in which a concept appears). These results suggest that our experience of how long it takes to recognize an instance of a concept can become a part of its representation, and that we simulate this information when reading words. Consequently, we suggest that time may be an embodied property of concepts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.