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Table 1.
Relative Activity of String Families in Four Genres of Letters.
String-Famiy/Genre Apologize Collect Fielding a Making a
Money Complaint Complaint
First Person
+2
-2
-2
+2
Self Disclosure
+1
-2
+1
Autobio
+2
-1
-1
Immediacy
-1
+3
-1
-1
Contingency
-1
+1
Apology
+3
-1
-1
-1
Positive
+1
-1
Negative
+1
-2
+2
-1
Retrospective
+1
-1
Reasoning
-1
+1
Inclusiveness
+1
+1
+1
-3
Reassuring
+1
-1
Acknowledging
+2
-1
-1
Imperative
-1
+3
-1
-1
Interactivity
+3
-3
Requesting
-1
+2
-1
Follow-Up
-1
-1
+2
ogizing, positive, reassuring, and acknowledging language. Compared to other
genres, letters that seek to collect on delinquent accounts rely on language that
conveys a sense of immediacy (now is the time), interactivity (you), and im-
perative command (should pay). Compared to other genres, letters that field
complaints focus on following-up with the complainer (“in response to your let-
ter of...”). They also acknowledgeand seek to redress the negativity associated
with the complaint. One surprise, which should be less surprising in the con-
text of the second letter of complaint above (Fig. 2) is that letters that make
complaints tend to be less negative overall than letters that field complaints or
that collect on delinquent accounts. Writers who make complaints apparently
find that they can be more effective by describing the problem narratively and
letting the reader infer the negative implications.
The point of this illustration is to show how the surface text, coded as string
families of reader experience, can aggregate to form statistically interpretable
and meaningful traces of genre distinctiveness. As readers we can sense the col-
lective impact of these surface manifestations. However, because of their distribu-
tion across multiple categories and because of the variety of ways that categories
can combine, these regularities are not easy, or even possible, to register con-
sciously, much less articulate, as an outcome of serial reading. Nevertheless, as
the above illustration suggests, it is feasible, through coding, string-matching,
and statistics, to isolate and articulate the deep relationship that in fact exists
between patterns in the textual surface and cultural functions of text.
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