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Eliciting Big Data From Small, Young, or Non-standard Languages: 10 Experimental Challenges
Evelina Leivada1, Roberta D'Alessandro2, Kleanthes K Grohmann3
1Department of Language and Culture, UiT The Arctic University of Norway, Tromsø, Norway.
Frontiers in Psychology
|March 7, 2019
Summary
Fieldwork in linguistic communities with small, young, or non-standard languages presents unique challenges. This study identifies and offers solutions for data collection, participant recruitment, and experimental design issues in such settings.
Area of Science:
- Linguistics
- Sociolinguistics
- Fieldwork Methodology
Background:
- Researching small, young, or non-standard languages poses distinct fieldwork challenges.
- Eliciting rich data requires addressing issues related to language characteristics and community dynamics.
Purpose of the Study:
- To identify and analyze challenges in linguistic fieldwork for under-resourced languages.
- To provide recommendations for effective data collection, participant recruitment, and experimental design.
Main Methods:
- Analysis of static and dynamic linguistic characteristics impacting fieldwork.
- Examination of interactive relations between language features and research processes.
- Case examples from diverse linguistic communities.
Main Results:
- Challenges include lack of orthography, rapid language change, absence of standardized tools, and limited participant pools.
- Issues span data handling, recruitment, experimental design, funding, and cross-border data transfer.
- Ten experimental challenges are detailed, applicable across spoken, sign, extant, and extinct languages.
Conclusions:
- Effective fieldwork in under-resourced languages requires strategic planning to overcome inherent linguistic and logistical hurdles.
- Recommendations are provided to enhance data quality and research feasibility in diverse linguistic contexts.
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