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Modeling Uncertainty around Free-List Cultural Salience Scores

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Title: Modeling Uncertainty around Free-List Cultural Salience Scores
Language: English
Authors: Daniel Major-Smith (ORCID 0000-0001-6467-2023), Benjamin Grant Purzycki (ORCID 0000-0002-9595-7360)
Source: Field Methods. 2026 38(1):62-75.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 14
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Research Methodology, Scores, Ambiguity (Context), Sampling, Bayesian Statistics, Regression (Statistics), Computation, Data Use, Data Collection, Computer Software, Foreign Countries
Geographic Terms: Russia
DOI: 10.1177/1525822X251379224
ISSN: 1525-822X
1552-3969
Abstract: The free-list method has enjoyed a remarkably productive history, yet most free-list research is limited to informal comparisons that are heavily reliant on point estimates such as item or cultural salience. Here, we demonstrate a range of methods to incorporate uncertainty into such group-level estimates. This approach involves: (1) resampling individual-level data (via bootstrapping or Bayesian regression) to create a range of hypothetical alternative samples; (2) generating group-level estimates (e.g., Smith's S) in each sample; and (3) using the variation in these estimates as uncertainty intervals. While we focus predominantly on cultural salience, this approach can be applied to other free-list metrics. We also present some extensions to this approach, such as comparing estimates between items and between groups. We provide open data and code to help readers gain familiarity with these methods. Ultimately, we encourage researchers using free-list data to move beyond simply reporting point estimates.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1496503
Database: ERIC
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  Data: Modeling Uncertainty around Free-List Cultural Salience Scores
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  Data: <searchLink fieldCode="AR" term="%22Daniel+Major-Smith%22">Daniel Major-Smith</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6467-2023">0000-0001-6467-2023</externalLink>)<br /><searchLink fieldCode="AR" term="%22Benjamin+Grant+Purzycki%22">Benjamin Grant Purzycki</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9595-7360">0000-0002-9595-7360</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Field+Methods%22"><i>Field Methods</i></searchLink>. 2026 38(1):62-75.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: The free-list method has enjoyed a remarkably productive history, yet most free-list research is limited to informal comparisons that are heavily reliant on point estimates such as item or cultural salience. Here, we demonstrate a range of methods to incorporate uncertainty into such group-level estimates. This approach involves: (1) resampling individual-level data (via bootstrapping or Bayesian regression) to create a range of hypothetical alternative samples; (2) generating group-level estimates (e.g., Smith's S) in each sample; and (3) using the variation in these estimates as uncertainty intervals. While we focus predominantly on cultural salience, this approach can be applied to other free-list metrics. We also present some extensions to this approach, such as comparing estimates between items and between groups. We provide open data and code to help readers gain familiarity with these methods. Ultimately, we encourage researchers using free-list data to move beyond simply reporting point estimates.
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      – SubjectFull: Scores
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      – TitleFull: Modeling Uncertainty around Free-List Cultural Salience Scores
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