A Robust Approach to Variation in Carpathian Rusyn: Resampling-Based Methods for Small Data Sets

M. Z. Lahjouji-Seppälä, Achim Rabus
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Abstract

Abstract Quantitative, corpus based research on spontaneous spoken Carpathian Rusyn language can cause several data-related problems: Speakers are using ambivalent forms in different quantities, resulting in a biased data set – while a stricter data-cleaning process would lead to a large scale data loss. On top of that, polytomous categorical dependent variables are hard to analyze due to methodological limitations. This paper provides several approaches to face unbalanced and biased data sets containing variation of conjugational forms of the verb maty ‘to have’ and (po-)znaty ‘to know’ in Carpathian Rusyn language. Using resampling based methods like Cross-Validation, Bootstrapping and Random Forests, we provide a strategy for circumventing possible methodological pitfalls and gaining the most information from our precious data, without trying to p-hack the results. Calculating the predictive power of several sociolinguistic factors on linguistic variation, we can make valid statements about the (sociolinguistic) status of Rusyn and the stability of the old dialect continuum of Rusyn varieties.
喀尔巴阡山脉变化的鲁棒方法:基于小数据集的重采样方法
基于语料库的定量研究喀尔巴阡Rusyn自发口语可能会导致几个与数据相关的问题:说话者使用不同数量的矛盾形式,导致数据集有偏差,而更严格的数据清理过程会导致大规模的数据丢失。最重要的是,由于方法的限制,多分类因变量难以分析。本文提供了几种方法来面对不平衡和有偏差的数据集,这些数据集包含喀尔巴阡山脉俄语中动词maty (to have)和(po-)znaty (to know)的变化。使用基于重采样的方法,如交叉验证、引导和随机森林,我们提供了一种策略,可以规避可能的方法陷阱,并从宝贵的数据中获得最多的信息,而无需尝试p-hack结果。计算几种社会语言学因素对语言变异的预测能力,我们可以对Rusyn的(社会语言学)地位和Rusyn变体的旧方言连续体的稳定性做出有效的陈述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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