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Variation in the input: a case study of manner class frequencies
1UCLA Department of Linguistics.
Journal of Child Language
|October 11, 2012
Summary
Language input frequency varies significantly, not uniformly, impacting language acquisition. Discourse topic influences these variations, not just language differences.
Area of Science:
- Linguistics
- Psycholinguistics
- Speech Science
Background:
- Understanding input variation is crucial for language acquisition theories.
- Segmental frequency distributions are key to analyzing language structure.
- Previous assumptions suggested uniform (unigram) and unitary language models.
Purpose of the Study:
- To investigate sources of frequency variation in manner-of-articulation classes in child and adult language input.
- To determine the significance of this variation for language acquisition.
- To test the hypotheses that language varieties are unigram and unitary.
Main Methods:
- Analysis of segmental frequency distributions in English child and adult input.
- Statistical examination of 'bursty' distributions versus chance variation.
- Comparison of segmental frequency variation within and across language varieties.
Main Results:
- English segmental frequencies are not unigram but exhibit 'bursty' distributions.
- Natural variation within a single language (English) is substantial, making it approximately unitary.
- Discourse topic variation is a primary driver of local segmental frequency fluctuations.
Conclusions:
- Input frequency variation is significant and non-uniform, with implications for language acquisition models.
- Discourse context, not just language differences, drives segmental frequency variation.
- Methodological recommendations are provided for comparing language samples effectively.
Related Concept Videos
01:15Construction of Frequency Distribution
A frequency distribution table can be constructed using the steps given below.
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is best to...
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is best to...
01:07What is a Mode?
The mode is one of the commonly used measures of a central tendency. It is defined as the most frequent value in a data set.
There can be more than one mode in a data set if multiple values have the same highest frequency. For instance, suppose that the Statistics exam scores of 20 students are: 50; 53; 59; 59; 63; 63; 72; 72; 72; 72; 72; 76; 78; 81; 83; 84; 84; 84; 90; 93. Here, the mode is 72, as it occurs most frequently, five times.
A data set with two modes is called bimodal. For example,...
There can be more than one mode in a data set if multiple values have the same highest frequency. For instance, suppose that the Statistics exam scores of 20 students are: 50; 53; 59; 59; 63; 63; 72; 72; 72; 72; 72; 76; 78; 81; 83; 84; 84; 84; 90; 93. Here, the mode is 72, as it occurs most frequently, five times.
A data set with two modes is called bimodal. For example,...
01:19Expected Frequencies in Goodness-of-Fit Tests
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n) to the number of categories (k).
00:51What is a Frequency Distribution
A frequency is the number of times a value of the data occurs. The sum of all the frequency values represents the total number of students included in the sample. It is commonly used to group data of quantitative types. Frequency distributions can be displayed in a table, histogram, line graph, dot plot, or pie chart, just to name a few. A histogram is a graphical representation of tabulated frequencies, shown as adjacent rectangles, erected over discrete intervals (bins), with an area equal to...
01:11Mean From a Frequency Distribution
Sometimes, data gathered from an experiment on a large sample or population are organized into concise tables. In such cases, the frequency of the quantitative data set is plotted in the form of a table. Or else, the data values are grouped into the quantity’s intervals, which form classes, and their respective frequencies are known. That is, the data values are distributed over different categories or classes. This is known as frequency distribution.
When such a data set is encountered, the...
When such a data set is encountered, the...
01:21Frequency-dependent Selection
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.