Explicit and Implicit Methods in Quantitative Analyses of Sociophonetic Variation
Bibliographic Data
| ID | 19544254 |
|---|---|
| Authors | Sara Mack (0000-0002-4004-3799, University of Minnesota System, corresponding author) |
| Year | 2013 |
| Volume | 6 |
| Issue | 1 |
| Pages | 165-178 |
| Publication date | 2013-03-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Studies in Hispanic and Lusophone Linguistics (JOURNAL) |
| Journal identifiers | ISSN: 1939-0238 • E-ISSN: 2199-3386 |
| Publisher | Walter de Gruyter GmbH (PUBLISHER • DE) |
| DOI | 10.1515/shll-2013-1145 |
| OpenAlex | W2333323729 |
| Language | EN |
| Citations received | 2 |
This viewpoint paper provides an overview of explicit and implicit methods in sociophonetic perception studies, illustrates how they can be used to measure the relationship between social factors and phonetic variation, and demonstrates how they can prove useful complements to more traditional sociolinguistic methods. The first section addresses explicit measures and gives an example of an explicit measures task exploring the relationships between phonetic variation and perceptions of speaker sexual orientation, height, age, and social class in Puerto Rican Spanish. Results show that an explicit measures task can provide a window into fine-grained phonetic variation associated with social factors that is not available through traditional impressionistic methods. The second part of the paper provides an overview of implicit measures, including an example of the use of implicit measures in a response time task that quantitatively assesses the relationship between /s/ variation and perceptions of sexual orientation in Puerto Rican Spanish. The paper concludes with a summary of how the results gathered from these types of experiments can further our understanding of theoretical issues in Hispanic Linguistics
Cognitive psychology · Linguistics · Perception · Computer Science · Linguistic Variation and Morphology · Multilingual Education and Policy · Phonetics and Phonology Research · Psychology · Artificial Intelligence
| Citations per year | 1 |
|---|---|
| Citation span | 2024 - 2025 (2) |
| Highly cited | No |