Chinese written characters exist in two varieties, one type of characters has a
name the other does not. Zhang and Simon asked some Chinese speakers to
remember eight sets of the two sorts of characters. The sub jects could immedi-
ately recall about six characters with names, but short term memory capacity
for Chinese radicals not possessing common pronounceable names is about two
or three items. Thus short term memory appears, on occasion, to adopt a name
strategy similar to the name strategy of the two proceeding sections; however
the new name referred to by Miller might not always be a specific word, it might
be some other label. To see this consider short term memory in musical perfor-
mance, where what is remembered may be specific notes, or a specific scale etc.,
chunking strategy is still involved but it is not now a name strategy. Therefore
the term stereotyping is used to cover all three phenomena.
5 The Implications for Traffic Accidents
5.1 Colour Perception and Traffic Accidents
Table: Rate of Involvement in Traffic Accidents of Cars by Colour.
Number of Accidents per 10,000 Cars.
Adapted from Table 7C.HMSO91.
Black White Red Blue Grey Gold Silver Other Beige Green Yellow Brown
176 160 157 149 147 145 142 139 137 134 133 133
Two-colour cars are classified by their main colour.
Other = Bronze,Pink,Orange,Purple,
Maroon,Turquoise,Multi-coloured,&Unknown.
The ab ove table shows the rate, per 10,000 licensed cars, of accidents classified
by colour. There is a striking resemblance of the three most accident prone
colours namely black, white, and red to the Berlin-Kay diagram; and some
resemblance among other colours, however accidents of blue cars seem to be
anomalously high compared to green, yellow, and brown cars. Munster and
Strait (1992) [33] note:
”The data probably say more about differences in the types of car
and driver represented in the colour groups than differences in the
inherent safety of the car colours. It is possible that certain colours
are more popular among groups of drivers with a higher risk of acci-
dent such as young drivers or company car users. Some colours may
tend to be associated with particular makes and models of car. No
doubt factors such as visibility also affect accident risk, but it would
be difficult to distinguish their effects from those of the driver and
vehicle, using the available data.”
11