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Data and Analysis scripts for the "Word Choice" experiment

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word-choice

Data and analysis scripts for the "Word Choice" experiment

Koranda, M., Zettersten, M., & MacDonald, M. (in press). Good-enough production: Selecting easier words instead of more accurate ones. Psychological Science. https://doi.org/10.1177/09567976221089603. Preprint: https://psyarxiv.com/q2h9d

Abstract

Dominant theories of language production suggest that word choice—lexical selection—is driven by alignment with the intended message: to talk about a young feline, we choose the most aligned word, kitten. Another factor that could shape lexical selection is word accessibility, or how easy it is to produce a given word (e.g., cat is more accessible than kitten). To test whether producers are also influenced by word accessibility, we designed an artificial lexicon with high- and low-frequency words with word meanings corresponding to compass directions. Participants earned points by producing compass directions, often requiring an implicit decision between a high- vs low-frequency word. A trade-off was observed across four experiments, such that high-frequency words were produced even when less aligned with messages. These results suggest that implicit decisions between words are impacted by accessibility. Of all the times that people have produced cat, sometimes they likely meant kitten.

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The repository contains the following documents

  • raw_data: raw data from Experiments 1-4
  • processed_data: processed data from Experiments 1-4 and the codebook for the resulting data
  • analysis_scripts: R scripts for processing the raw data and analyzing the processed data from Experiments 1-4
  • plots: figures generated in the analysis pipeline
  • experiment_scripts: Experimental scripts used to present the experiment (python-/ psychopy-based)

Link to OSF project

https://osf.io/3svge

Analysis Walkthrough

Here is a direct link to the html rendering of the R Markdown file in the data folder. This provides a walkthrough of the major analyses in the paper.

https://rpubs.com/zcm/good_enough_production

Questions

Feel free to contact me at [email protected] if you have any comments or questions about the data or the analyses.

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