Determining the presence and number of the nine features

2. Determining the presence and number of the nine features

After the clauses of all of participants’ drafts were numbered consecutively, (following the pattern in Berman & Ravid 2008: 4), each of the nine features of global text quality was quantified in the order presented above. Before the features could be counted, however, the number of each type of information unit had to be determined and marked with their respective abbreviations (CoP, CoEv, and INT). This was done carefully and consistently across all drafts. Descriptives (DES) were unmarked. Core- propositions (CoP) were taken to be any speech act verbs. The clause complementing the speech act verbs were taken to be descriptives, following Berman & Ravid (2008). Core- propositions were also taken to be signal-statements that were repeated throughout the argument and/or around which descriptive element clauses clustered around them. Any commentary that seemed to be deontic in force or abrupt shifts to the second person in order to prescribe advice—especially those which appeared at the end of drafts—were taken to be interpretives (INT). Core-eventives were not as difficult to determine as the other information units, as use of past tense dynamic action verbs usually signaled the After the clauses of all of participants’ drafts were numbered consecutively, (following the pattern in Berman & Ravid 2008: 4), each of the nine features of global text quality was quantified in the order presented above. Before the features could be counted, however, the number of each type of information unit had to be determined and marked with their respective abbreviations (CoP, CoEv, and INT). This was done carefully and consistently across all drafts. Descriptives (DES) were unmarked. Core- propositions (CoP) were taken to be any speech act verbs. The clause complementing the speech act verbs were taken to be descriptives, following Berman & Ravid (2008). Core- propositions were also taken to be signal-statements that were repeated throughout the argument and/or around which descriptive element clauses clustered around them. Any commentary that seemed to be deontic in force or abrupt shifts to the second person in order to prescribe advice—especially those which appeared at the end of drafts—were taken to be interpretives (INT). Core-eventives were not as difficult to determine as the other information units, as use of past tense dynamic action verbs usually signaled the

Table I. Information units in draft 1

Clause and infu count in draft 1

Types of Infus Michelle Jackie

Helen Average

Draft 1-INT# 2 0 4 1 2 2 2 Draft 1-CoEv#

0 1 5 0 10 4 3 Draft 1-CoP#

5 3 3 8 0 7 4 Draft 1-DES#

Draft 1 Total clauses

Proportion of types of information units to total clause number in draft 1 Types of Infus

Helen Average Draft 1-INT%

Michelle Jackie

Draft 1-CoEv%

Draft 1-CoP%

Draft 1-DES%

Table I shows that descriptives made up most of the information unit types in draft 1, followed by Core-propositions/eventives and least of all interpretives. The low number of core elements is consistent with Ravid & Berman (2006: 132) with respect to the written expository discourse of older speaker-writers. In table II, there was a small increase in each of the types of information units, and overall clause number for almost all participants. An increase in clause number, however, is in no way linked to an increase in global text quality. Though more information units were found in draft 2 overall, the number of descriptives in draft 2 dropped slightly, evident of a higher proportion of other types of information units in drafts.

Table II. Information units in draft 2

Clause and infu count in draft 2

Types of Infus Michelle Jackie

Helen Average

Draft 2-INT# 3 0 4 1 2 3 2 Draft 2-CoEv#

5 1 5 0 10 4 4 Draft 2-CoP#

6 5 5 10 1 7 6 Draft 2-DES.#

Draft 2 Total clauses

Proportion of types of information units to total clause number in draft 2 Types of Infus

Helen Average 2-INT%

Michelle Jackie

With reference to Fraser (1996, 2005), determining the number and type of discourse markers present in the drafts was met with little difficulty (DM#, MetaDM#). Any instance of meta-commentary in general was consistently taken to be one count of meta- discourse marker usage. With respect to determining the number of shifts between personal/impersonal discourse stances (Alt-IMP#), pronoun usage was taken to be the

key signal with 1 rd and 2 person usage regarded as “personal” and 3 person usage regarded “impersonal.” Passive voice usage, noun abstractness, and other linguistic

st

nd

devices encoding discourse stance (See section 2.7.3) were not consistent enough across drafts to be a reliable enough index of personal/impersonal shifts. With respect to the number of statements framed as replies to text-external exigencies (Reply#), the canonical “Some say/ but I say” signals were counted, along with some variants. Any time a discourse marker or thematic content signaled a shift in type of information unit, a count was made (Alt-Infu#). The following change in information unit, for example, was signaled with a subsequent shift in discourse stance:

“CoEv 43) Now Korea has become one of the economically developed countries in the world 44) and it is ranked around top 10. INT 45) I think it’s a jaw- dropping evidence 46) we could ever find in the world history” (Natalie, Draft 2)

With respect to determining the number of instances that generalized propositions was anchored with narrative or culturally shared knowledge (Nar-Gen#), the presence of CoEv elements were taken to be the predominant index, and sometimes statements that seemed to be instances of culturally shared knowledge elaborating upon or supporting a generalized proposition. Interestingly, the number of themes—defined as the sub-topics or statements used to discuss/argue the main essay topics—never changed (Theme#). When all of the above features had been quantified consistently, it was then that a score of global text quality level (GTO) was assigned—only with careful reference to Berman & Nir-Sagiv (2007: 97-99). All of these features quantified in drafts 1 and 2 are shown in table III.

Table III. Discourse features in drafts 1-2

Number of features in draft 1

Helen Average Draft 1 Reply#

Features Michelle Jackie

Draft 1 Nar-Gen#

Draft 1 Theme#

Draft 1 MetaDM#

Draft 1 Alt-Infu#

Draft 1 Alt-IMP#

Draft 1 DM#

Total 18 25 33 37 40 51

Number of features in draft 2

Helen Average Draft 2 Reply#

Features Michelle Jackie

Draft 2 Theme#

Draft 2 Nar-Gen#

Draft 2 MetaDM#

Draft 2 Alt-IMP#

Draft 2 Alt-Infu#

Draft 2 DM#

Total

Each participant demonstrated an increase in certain features from draft 1 to draft 2, yet overall the greatest increase across drafts was in the use of meta-discourse markers. One can observe, for example, that Helen used more using meta-discourse marking in draft 2 as compared with draft 1:

Helen, Draft 1:

56) I don't want 57) to judge 58) what is the most important in our life.

59) But it is true . CoP 60) that each standard of society affects human's characteristic and behavior. CoP 61) If people can have a chance 62) to change somethings, 63) people also can be changed. CoEv 64) A man 65) <who I met in the US>

Helen, Draft 2:

61) I don't want 62) to judge 63) what is the most important in our life.

64) But it is true CoP 65) that each standard of society affects choosing criteria of human's characteristic and behavior.

66) I would argue 67) that Change of Human being depends on his Society. 68) If society show him a variety of sides, 69) Human can accept and 70) develop it actively. 71) In another example, I remember CoEv

72) that on several occasions I met A man

It appears that Helen’s use of the manner-of-speaking meta-discourse marker “I would argue” in draft 2, clause 66, is motivated by an increased awareness of communicative context; she is speaking to an audience that may or may not want to accept her lines of argumentation. Natalie also demonstrates increased awareness of the presence of an audience by her hedging move, “allegedly,” between clause 12 in draft 1 and clause 15 in draft 2.

Natalie, Draft 1:

11) I’m from South Korea 12) which is very well known as one of the Asian Dragons for its amazing economic development along with Hong Kong, Taiwan, and Singapore.

Natalie, Draft 2:

14) I’m from South Korea 15) which is allegedly very well known as one of the four Asian Dragons for its amazing economic development along with Hong Kong, Taiwan, and Singapore.

Another instance of increased meta-discourse marking between Natalie’s drafts is demonstrated by the increase in assessment marking between clause 26 in draft 1 and clause 29 in draft 2.

Natalie, Draft 1:

24) Due to the imperialist aggression and the fratricidal war between North and South, Korea has had a very hard time 25) surviving until late 1970’s. CoP 26) However, Korean people always have been believers and doers. 27) We have a quite strong confidence for the bright future 28) and we work hard 29) to make it 30) come true.

Natalie, Draft 2:

27) Due to the imperialist aggression and the fratricidal war between North and South, Korea has had a very hard time 28) surviving until late 1970’s. CoP 29) Nonetheless, strikingly, Korean people always have been believers and doers. 30) We have a quite strong confidence for the bright future 31) and we work hard 32) to make it come true.

Again, this assessment meta-discourse marking, “strikingly,” seems to be functionally motivated by Natalie’s desire to communicate to her audience that she is framing the statement as being historically unique and laden with extraordinary value.

A measure was taken of the percentage of change with respect to each of the features, either positively or negatively, between draft 1 and 2 (table IV) in order that the pattern of increase of discourse features could be seen more clearly.

Table IV. Percentage of increase of discourse features from draft 1 to draft 2

Percentage of increase of features between drafts 1 and 2 Features