While university professors are given high social status in the United States, their salaries cause them to actually have low socioeconomic statuses. Despite their lower SES, professors typically use highly “standard” language, as many consider themselves gatekeepers of both language and knowledge.
Simiarly, low-paid white collar and pink-collar workers, such as administrative assistants, nurses, etc., will likely use speech similar to the standard language of their superiors, despite lower salaries than them. -- or some may perform a more vernacular dialect when dealing with the public or vernacular speaking clients.
On the contrary, contractors and plumbers have high SES, despite having lower social prestige due to their being labelled blue-collar. It is likely that, despite their high SES, they will use more working class patterned language due to their social networks.
Finally, a lawyer or car salesman in the South may have both high prestige and high SES, but may choose to speak with a heavily accented dialect in order to sound more “believable” or “genuine.”
Chapter 6 | Exercises
Exercise 6.1
Most people can think of individuals who are exceptions to the rule when it comes to the link between language variation and quantitative measures of socioeconomic status. That is, a person assigned a low SES rating may speak like one typically associated with a high SES rating, or the converse.
What kinds of factors may account for such discrepancies?
Do you think that such discrepancies invalidate the general correlation of language variation with SES scores based on objective measures? Why or why not?
What kinds of factors may account for such discrepancies?
Do you think that such discrepancies invalidate the general correlation of language variation with SES scores based on objective measures? Why or why not?
6.1 Answers
Exercise 6.2
In the following passage, tabulate the incidence of cluster reduction for all the underlined word‐final clusters. Observe whether the cluster is reduced or not, as indicated by the phonetic content in the brackets following the underlined cluster. For example, guest[s] would indicate a reduced item since the final [t] has been omitted, and guest[st] would not. For the sake of the exercise, ignore consonant clusters that are not underlined. Tabulate the items by setting up two columns, one for clusters followed by consonants and one for clusters followed by non‐consonants. Items at the end of a sentence should be considered to be followed by non‐consonants. For each cluster, first identify whether it is followed by a consonant or non‐consonant and then enter it under the relevant category and identify in some way whether it is reduced or non‐reduced. After extracting the first couple of items, your tabulation sheet might look like the following:
Clusters followed by
a consonant 0 e.g. best[st] movie 1 e.g. last[s] year . . . |
Clusters followed by
a non‐consonant 0 e.g. most[st] of 1 e.g. coast[s]. It . . . |
1 = reduced cluster
0 = unreduced cluster
After you have finished entering all the items under the appropriate category, calculate the percentage of cluster reduction for each category by dividing the number of clusters in each category that are reduced by the total number of clusters in that category, and multiply by 100. This will give you a percentage of cluster reduction for clusters followed by consonants and clusters followed by non‐consonants. What can you say about the influence of the following context on cluster reduction based on this calculation?
Passage for word‐final cluster reduction tabulation
Last[s] year I saw the best[st] movie. It seemed silly but it was serious too. It was about this detective who lived in California, but he traveled up and down most[st] of the coast[s]. It seemed like he was always one step ahead of the cops and one step behind[n] the bad guys at the same time. Nobody really liked him, and it seemed like he was almost[s] killed every time he left the house. Most[s] of the time, he was running from both the criminals and the police. In fact[kt] both sides were totally confused by him.
One time, the police set up a scam bust[s] by pretending to smuggle in some drugs off the coast[st]. When they smuggled the stuff inland[n] they wanted to sell it to the dealers. But the detective wasn’t told so he thought it was a chance for a real bust[st] on the dealers. Just[s] as he jumped in to make an arrest[s] a couple of dealers showed up, and he had to act[k] like he was one of them. So the police thought he was part of the dealers and the dealers thought he was part of the police. Both sides jumped in and he was trying to act[k] as if he was with the other side. He told a policeman to go along with him ’cause he was making a bust[st] and he told a drug dealer to go along with him and he would get the drugs. Both sides were so confused by him they just[s] went along with the act[kt] and followed his lead. As it turned out, some of the police had gone underground[n] and some of the dealers had turned evidence to the police. He was so confused himself he didn’t know who to arrest[st]. Finally, he just[s] left both groups shooting at each other. He just[s] couldn’t figure out who was bad and who was good.
0 = unreduced cluster
After you have finished entering all the items under the appropriate category, calculate the percentage of cluster reduction for each category by dividing the number of clusters in each category that are reduced by the total number of clusters in that category, and multiply by 100. This will give you a percentage of cluster reduction for clusters followed by consonants and clusters followed by non‐consonants. What can you say about the influence of the following context on cluster reduction based on this calculation?
Passage for word‐final cluster reduction tabulation
Last[s] year I saw the best[st] movie. It seemed silly but it was serious too. It was about this detective who lived in California, but he traveled up and down most[st] of the coast[s]. It seemed like he was always one step ahead of the cops and one step behind[n] the bad guys at the same time. Nobody really liked him, and it seemed like he was almost[s] killed every time he left the house. Most[s] of the time, he was running from both the criminals and the police. In fact[kt] both sides were totally confused by him.
One time, the police set up a scam bust[s] by pretending to smuggle in some drugs off the coast[st]. When they smuggled the stuff inland[n] they wanted to sell it to the dealers. But the detective wasn’t told so he thought it was a chance for a real bust[st] on the dealers. Just[s] as he jumped in to make an arrest[s] a couple of dealers showed up, and he had to act[k] like he was one of them. So the police thought he was part of the dealers and the dealers thought he was part of the police. Both sides jumped in and he was trying to act[k] as if he was with the other side. He told a policeman to go along with him ’cause he was making a bust[st] and he told a drug dealer to go along with him and he would get the drugs. Both sides were so confused by him they just[s] went along with the act[kt] and followed his lead. As it turned out, some of the police had gone underground[n] and some of the dealers had turned evidence to the police. He was so confused himself he didn’t know who to arrest[st]. Finally, he just[s] left both groups shooting at each other. He just[s] couldn’t figure out who was bad and who was good.
6.2 Answers
1 Last[s] year
0 best[st] movie
1 behind[n] the
1 almost[s] killed
0 fact[kt] both
1 bust[s] by
1 act[k] like
0 coast[st]. When
1 inland[n] they
1 just[s] went
0 arrest[st]. Finally
1 just[s] couldn’t
8 reduced cluster
4 unreduced cluster
=66.6% reduced
0 most[st] of
1 coast[s]. It
1 most[s] of
0 bust[st] on
1 arrest[s] a
1 act[k] as
0 act[kt] and
1 underground[n] and
5 reduced cluster
3 unreduced cluster
=62.5% reduced
It doesn’t look like there appears to be a huge effect of following environment upon CCR, although more clusters tend to be reduced before consonants than before non-consonants.
Clusters followed by a consonant
1 Last[s] year
0 best[st] movie
1 behind[n] the
1 almost[s] killed
0 fact[kt] both
1 bust[s] by
1 act[k] like
0 coast[st]. When
1 inland[n] they
1 just[s] went
0 arrest[st]. Finally
1 just[s] couldn’t
8 reduced cluster
4 unreduced cluster
=66.6% reduced
Clusters followed by a non-consonant
0 most[st] of
1 coast[s]. It
1 most[s] of
0 bust[st] on
1 arrest[s] a
1 act[k] as
0 act[kt] and
1 underground[n] and
5 reduced cluster
3 unreduced cluster
=62.5% reduced
It doesn’t look like there appears to be a huge effect of following environment upon CCR, although more clusters tend to be reduced before consonants than before non-consonants.
Exercise 6.3
In referring to the rodent mouse, the plural form mouses rather than mice is highly stigmatized. At the same time, when referring to computers, the plural of mouse is often the regularized form mouses, as in We bought new mouses for all of the computers in the lab.
How might you explain the differential social valuation of these forms?
What does this say about language innovation and social valuation?
How might you explain the differential social valuation of these forms?
What does this say about language innovation and social valuation?
6.3 Answers
This shows the linguistic arbitrariness but social/contextual influence on language “norms.” That is, the word mouses is not inherently “ungrammatical”, but rather depends on the situation.