Ch. 19 | Exercise 1

# Chapter 19 | Exercise 1

### Case study 1 ‘Women and metonymy in Ancient Chinese’

Table 19.1 contains some important metonymic patterns that were used to refer to women in texts of the Ming dynasty in China (1368 – 1644). The frequencies are a somewhat modified version of the data in Zhang (2013). The rows show different types of female referents, namely, imperial woman (queen or emperor's concubine), servant girl, beautiful woman, mother or grandmother, unchaste woman (prostitute or mistress), young girl, wife (or concubine). The columns are six metonymic patterns, which need some explanation:

• Action for agent or patient, e.g. “to ruin state” for “beautiful woman”

• Bodypart for whole, e.g. “powder-heads” for “prostitutes”

• Location for located, e.g. “the middle palace” for “queen”

• A piece of clothing for person, e.g. “red dress” for “beautiful woman”

• Characteristic for person, e.g. “respectable-kind” for “mother”

• Possessed for possessor, e.g. “blusher and powder” for “beautiful woman”

Table 19.1. Distribution of metonymic patterns that refer to females in Ming dynasty texts
Action Bodypart Location Clothes Characteristic Possessed
Imperial 10 1 204 5 2 0
Beautiful 9 99 5 71 112 120
Mother 8 4 32 1 2 3
Unchaste 2 67 27 3 5 2
Young 1 2 16 14 7 3
Wife 24 3 763 37 1 2
1.

Create a table in R with counts from Table 19.1.

2.

Perform Simple Correspondence Analysis to see which targets (rows) are similar with regard to the metonymical patterns. Explore two-dimensional and three-dimensional plots and interpret them.

First, create vectors that represent the rows in the table:

```> Imperial <- c(10, 1, 204, 5, 2, 0) > Beautiful <- c(9, 99, 5, 71, 112, 120) > Mother <- c(8, 4, 32, 1, 2, 3) > Unchaste <- c(2, 67, 27, 3, 5, 2) > Young <- c(1, 2, 16, 14, 7, 3) > Wife <- c(24, 3, 763, 37, 1, 2) ```

Next, combine the vectors as rows.

```> Ming_woman <- rbind(Imperial, Beautiful, Mother, Unchaste, Young, Wife) ```

Finally, provide the columns with names:

`> colnames(Ming_woman) <- c('Action', 'Bodypart', 'Location', 'Clothes', 'Characteristic', 'Possessed')````> library(ca) > Ming_woman.ca <- ca(Ming_woman) > summary(Ming_woman.ca) ```

First, create a two-dimensional map, which explains almost 96.4% of the total variance (inertia):

```> plot(Ming_woman.ca) ```

Next, create a 3D plot, to account for additional 2.2% of variance, which is explained by the third dimension:

```> library(rgl) > plot3d(Ming_woman.ca, labels = c(1,1)) ```

The plots will show that most metonymic patterns tend to designate a particular referent, although there is some variation. For example, a beautiful woman is associated with Possessed for possessor and Characteristic for person, whereas Imperial women and simple Wives and concubines are associated with Location for located (typically, a room or palace), and so on. Young girls are mostly associated with Piece of clothing for person, whereas Unchaste women are associated with Bodypart for whole. Adding the third dimension allows one to see that Mothers are less similar to Wives and Imperial women than it would seem on a two-dimensional plot.