PARTICIPANTS
We will put a HIT on Amazon Mechanical Turk for 1000 workers.
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MATERIALS - OVERVIEW
Materials will be presented and answers will be collected using Qualtrics web platform. The exact wording of all used materials can be found in Materials node. The materials were constructed to be as close as possible to the materials used in Study 3 by Song and Schwarz (2009) based on their description in the paper.
Six out of the 206 names we will use in the study are from Study 3 by Song and Schwarz (2009), the rest is obtained and constructed using a Python script that can be found in the Files section of this node. Since Song and Schwarz used Native American names, we downloaded all Native American names in the database: http://www.babynameguide.com/categorynativeamerican.asp?strGender=&strCat=Native-American&strOrder=Name and we selected names that were of the same range of word lengths as used in Song and Schwarz (2009), i.e., 6-13 letters. For each of these lengths, we selected 25 names randomly. Because there was not enough names of lengths 11-13, we constructed the remaining names (to the total of 25) randomly by combining names 3-5 letters long. We thus obtained 200 names. Adding the original 6 names from Song and Schwarz (2009) resulted in the final 206 names used in the study. Lists of names obtained from running the script can be found in the Files section of the Materials node.
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DESIGN
Participants will be asked to imagine that they are visiting an amusement park and reading a brochure with names of amusement-park rides. In one scenario, they are looking for the most adventurous ride and they are supposed to judge all presented rides on a scale ranging from 1 – very dull to 7 – very adventurous. In the other scenario, they are told that they are not feeling well that day and they want to avoid too adventurous rides, which could make them sick. In this scenario, participants are supposed to judge all presented rides on a scale ranging from 1 – very safe to 7 – very risky.
They will be judging 11 different rides (out of 206) in each scenario.
After the end of the data collection, we will obtain pronounceability ratings for all 206 used names from a different sample of mTurk workers using a 7-point scale ranging from 1-easily pronounceable to 7-hard pronounceable.
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Song, H., & Schwarz, N. (2009). If It's Difficult to Pronounce, It Must Be Risky Fluency, Familiarity, and Risk Perception. *Psychological Science, 20*, 135-138.
