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Specificity ratings for English data | Cognitive Processing | Springer Nature Link

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A dataset of specificity ratings for English words is hereby presented, analyzed and discussed in relation with other collections of speaker-generated ratings, including concreteness. Both, specificity and concreteness are analyzed in their ability to explain decision latencies in lexical and semantic tasks, showing important individual contributions. Specificity ratings are collected through best–worst scaling method on the words included in the ANEW dataset (Bradley and Lang in Affective norms for English words (ANEW): instruction manual and affective ratings (Tech. Rep.). Technical report C-1, the center for research in psychophysiology, 1999), chosen for its compatibility with many other collections of rating resources, and for its comparability with Italian specificity data (Bolognesi and Caselli in Behav Res Methods 55(7):3531–3548, 2023), allowing for cross-linguistic comparisons. Results suggest that specificity plays an important role in word processing and the importance of taking specificity into consideration when investigating concreteness effects.

Introduction Abstraction, a hallmark of human cognition, remains a rather vague phenomenon that possesses intuitive comprehensibility, yet eludes precise delineation. A recent definition offers a potential explication of Abstraction as “The process of forming general ideas or concepts by extracting similarities and general tendencies from direct experience, language, or other concepts” (Reilly et al. 2024). Upon a closer examination of this overarching definition, identifying the fundamental mechanisms involved in this process proves to be challenging. One of the difficulties arises from…

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