Loyal and Honest a Question of Usage
Mary Sarawit
Abstract
The purpose of this study was to examine the words „loyal‟ and „honest‟,
especially in terms of how these words are used by Thais. Using contrastive
linguistics and corpus based linguistics, the two words were examined for
grammatical and semantic errors made by fifty-nine intermediate level
students. One of the objectives of this study was to suggest remediation for
the Thai users of English in order to eliminate errors using „loyal‟ and „honest‟
by presenting collocation data and resources. As James (1998: 152) states,
“Adherence to the collocational conventions of a FL contributes greatly to
one‟s idiomaticity and native likeness and not doing so announces one‟s
foreignness…”
The results of this study revealed that over sixty-five percent of the
students‟ writing had grammatical and semantic errors with „loyal‟ and thirtyone percent of their writing had grammatical and semantic errors with
„honest.‟ The grammatical errors included failure to use the verb „to be‟ with
the adjectives „loyal‟ and „honest‟ as well as failure to use the correct
prepositions following the two words.
Semantic errors with these two words involved misuse of the two
words by disregarding the core meaning of truthful and lawful for „honest‟ and
faithful for „loyal.‟ While Thai has two separate words to distinguish the
meaning of „loyal‟ from the meaning of „honest‟, it also uses ซื่อสัตย์ alone or
จงรักภักดี to mean „honest‟ and/or „loyal.‟
Students who rely on bilingual dictionaries will thus often find ซื่อสัตย์ when
in combination with
สุจริต,
or
translating „loyal‟ and „honest‟ into Thai and „honest‟ and „loyal‟ when
translating ซื่อสัตย์ into English. In addition, because „honest‟ has a higher
frequency of use in English, students are less familiar with „loyal‟ and this
might also influence their use of „honest‟ in contexts requiring „loyal.‟
The results of this study support previous work advocating the use of
collocations in teaching vocabulary ( Boonyasaquan: 2006). This paper
presents language corpora websites which give teachers and students the tools
to access collocations of words easily.
1
Loyal and Honest a Question of Usage
Mary Sarawit (2010)
Background
All languages can express ideas and concepts. We do this through
words embodied through the structure of a language. Words are basic units in
a language built by combining sounds of a language following the phonology
of the particular language. Words can be simple like „ram‟ or complex like
„encouraged‟ combining root, cour, prefix marking a verb, en-, suffix marking
a noun, –age, and another suffix marking past tense, -ed. Even a seemingly
simple word like the noun „ram‟ carries a multitude of semantic information:
animal, sheep, adult, male, and so forth.
Learning and using a foreign language requires not only knowledge of
the sound system and structure of the language along with practice in using
the listening, speaking, reading, and writing skills, but it also requires an
understanding of the often subtle differences between the native and foreign
language in using words. While some words can be translated from one
language to another with an almost 100 percent accuracy in semantic and
syntactic properties, many words have important semantic differences beyond
differences of structure in the two languages.
In my years of living and teaching in Thailand, I have often been
intrigued by the properties of words in Thai and English and the problems
these difference cause Thai users of English. In this research I would like to
examine the Thai English speakers‟ problems in using the words „loyal‟ and
„honest.‟
Research questions
1. What percent of the sentences using „loyal‟ were correct and what percent
had errors?
2. What percent of the errors using „loyal‟ were grammatical errors and what
percent were semantic errors?
3. What percent of the sentences using „honest‟ were correct and what percent
had errors?
4. What percent of the errors using „honest‟ were grammatical errors and
what percent were semantic errors?
5. Why do the Thai users of English make the identified grammatical errors?
6. Why do the Thai users of English make the identified semantic errors?
Research objectives
1. To identify the grammatical and semantic errors made by Thais when using
„loyal‟ and „honest.‟
2. To propose possible reasons for these errors.
3. To suggest remediation for the Thai users of English in order to eliminate
errors in using „loyal‟ and honest.‟
2
Significance of the study
It is expected that the results of this study will help Thai users of
English to understand the differences and correct usage of the words „loyal‟
and „honest.‟ This study will also provide an example for teachers to study
their students‟ errors, and show how collocations using concordance software
programs can facilitate the learner‟s understanding of the lexicon.
Scope of the study
This study is limited to an examination of an intact group of
intermediate level Thai users of English. The study focuses on their use of the
English words „loyal‟ and „honest‟ in writing sentences. Analysis of the data
uses theories of language analysis and error analysis to identify grammatical
and semantic errors and possible causes for such errors. Remediation of
errors is proposed using concordancers.
Definition of terms
Grammatical errors are errors in word structure and sentence structure.
Example: the use of „loyal‟ in subject position which requires the noun form
„loyalty‟ or the use of „loyal‟ as a verb instead of using the verb to be plus the
adjective „loyal.‟
Semantic errors are errors which involve the meanings of the two words.
Example: „honest‟ includes not cheating; knowing right from wrong. It is not
normally used with animals.
Related literature
This research is basically a qualitative study that relates to „Contrastive
Lexis‟ and „Corpus-based‟ analysis. As Michael Lewis (2002, 89) states in his
book advocating a „Lexical Approach‟ to foreign language teaching ,“Lexis is
the core or heart of language but in language teaching has always been the
Cinderella.” After decades in which vocabulary or lexis played a secondary
role with grammar taking the spotlight, “…the lexicon now features high on
the agenda, in both theoretical and applied linguistics” (Altenberg and
Granger, 2002, 3).
Along with focus on the lexicon, there has been renewed use of
contrastive analysis (CA) or CL, contrastive linguistics, to study words across
languages. Bentivogli and Pianta (2002, 1) point out in their study of English
to Italian gaps “…contrastive analysis is rich in classifications and
exemplifications of the lexical divergences that can occur between pairs of
languages.” While a cursory look at a bilingual dictionary may lead one to
think that there is a one-to-one translation, for most lexical items due to
historical, cultural, geographical and social developments words do not equate
one hundred percent across languages. As Altenberg and Granger (2002, 21)
note “…complete equivalence between words and expressions in different
languages is rather unusual.” Bentivogli and Pianta (2002, 2) list four types of
discrepancies between lexical items in words and phrases of two languages:
1. Syntactic divergences: This is where the translation equivalent has
different ordering properties. An example would be „green house‟ = „บ้ าน
หลังสีเขียว‟ (house green).
I would also add when the word class is different:
„free‟ is an adjective in English, but the borrowed word in Thai is used
3
mainly as an adverb.
2. Lexicalization differences: This is where the two languages use a different
kind of lexical unit (word compound or phrase) or one of the two languages
has no lexicalization for a concept: aquarium= ทีเก็บสัตว์น ้า, a place for
aquatic animals.
3. Divergence in connotation: This is where one language fails to reproduce
all the nuances expressed by the other language: eat= „กิน/รับประทาน/เสวย.‟
„Eat‟ is a general word in English and can be used in all registers while in
Thai „กิน/รับประทาน/เสวย‟ are used in different registers: everyday, polite or
formal and for royalty, respectively.
4. Divergence in denotation. This is where one language only partially
overlaps the denotation of the other language. Both „prevent‟ and „ protect‟
translate as ป้องกัน: การแปรงฟั น ป้องกันฟั นผุ‟=Brushing prevents tooth decay
and „ทหารมีน้าที่
ป้องกันประเทศ‟-Soldiers have a duty to protect the country.
(See Sarawit 2008 and 1978 for an analysis of „protect‟ and „prevent.‟)
Linguistic analysis in general and lexical analysis in particular was
given an enormous boost with advances in computing which allowed for the
input of large amounts of language data. In the 1960s Henry Kucera and W.
Nelson Francis (1967), both of whom were at Brown University, compiled a
corpus of American English of around a million words. It is widely known
today simply as the Brown Corpus. In the 1980s the English Department at
Birmingham University and Collins Publishing initiated the Collins
Birmingham University International Language Database known as the
COBUILD Corpus or the Bank of English. Starting with around seven million
words, as of 2005 the corpus totaled 525 million words. Renouf (1987, 1)
defines corpus as “…a collection of texts of written or spoken word, which is
stored and processed on computer for the purposes of linguistic research.”
Because the corpus is actual text and not randomly recorded individual words,
it offers lexicographers words in a situational context. Rosamund Moon
(1987) another of the COBUILD team compares older dictionaries that simply
listed words and their meaning to “…flies caught in amber” (Moon: 1987, 87).
Meaning, she maintains, should never be devoid of context. Another large
corpus of English is the Corpus of Contemporary American English known as
COCA (Davis, 2009). It has over 400 million words from over 150,000 texts.
It, like the COBUILD corpus, continues to expand.
Other languages are also building language corpora. In Thailand the
National Electronics and Computer Technology Center (NECTEC) completed
the ORCHID (Open Linguistic Resources Channeled toward Inter Disciplinary
Research) project in 1997. It is the basis of the LEXITRON on-line ThaiEnglish dictionary. The Linguistics Department at Chulalongkorn University
maintains the website for the Thai concordancer, using the Thai National
Corpus.
Originally these corpora were designed to provide real world language
for lexicographers, linguists, and others conducting language research. Later
the value of lexical collocations using concordancers became apparent to
4
language teachers, especially foreign language teachers. Concordance
programs allow the users to see words in context bringing a multitude of
examples of a word and its collocations or as Firth (1957, 187) said, “…the
company that words keep.” A concordance program provides an example of a
selected word from authentic language texts displayed in the center
of a line showing the context in which the word occurs (Lamy et al.: 4). The
following is an example from the Collins COBUILD Dictionary CD ROM
(2006) for which the selected word is highlighted in the sentence. This is a
sample of the 202 occurrences provided for the word „honest.‟
So, all in all the odds are heavily against the honest buyer and heavily
in favour of the crook.
Mostly, I‟m honest because special gifts aren‟t for monkeying about
with.
She said quietly, “I told you he was honest, even if he is stupid.”
Suddenly I was the only honest crook on the campus.
In our country nothing can happen to an honest man.
In an article discussing the Collins COBUILD English Collocations
software, Carolyn Samuel (2003, 5) points out that the concordancer..”…has
the potential to foster autonomous learning and to stimulate students‟
problem-solving skills.” As previously noted words rarely have perfect
equivalents across languages, so it is important that language learners realize
the importance of seeing words in context and not in isolation. Guyneth Fox
(1987, 137) points out in her article “The Case for Examples” that “Most
learners of a foreign language have had the experience of looking up a word in
the target language and finding 3 or 4 words given which seem to be
synonyms but which all have limitations the unwary user is not conscious of.”
As Jens Bahns (1993, 59) tells us, it is for these „lexically non-congruent‟ forms
that collocations need to be learned. He notes that most collocation errors
made by foreign language learners are a result of L1 influence (Bahns:1993,
61). It is for this reason that he advocates a contrastive analysis of lexical
collocations and the teaching of collocations which present specific problems
to students with a particular L1 background.
It is with this in mind that the researcher decided to conduct a study of
„loyal‟ and „honest‟ as used by Thai users of English and through the use of
concordancers point out the semantic restrictions of each word in English and
resulting Thai/English translation problems.
Research methodology
The population was a group of doctoral students at Naresuan
University who were studying the third course in English to fulfill the
language requirements for their doctoral programs. I asked their teacher to
collect the data. At the end of class one week the students wrote two sentences
using „loyal‟; there were fifty-nine students. The next week they wrote two
sentences using „honest.‟ That day three students were absent, so there were
only fifty-six respondents.
I read the sentences for errors in using „loyal‟ and „honest.‟ Other
errors in the sentences were not considered. Errors in using „loyal‟ and
„honest‟ were then categorized as grammatical or semantic. Percentage was
used to quantify the errors.
5
Thai and English concordancers and dictionaries were examined to
study the lexical context for „loyal‟, „honest‟, and their Thai translations.
Results
The results of this study will be presented in two parts. Part one will
present the analysis of the data in answer to research questions one through
four relating to the error analysis of the respondents‟ use of „loyal‟ and
„honest.‟ Part two will present an analysis of the words „loyal‟ and „honest‟ and
the Thai translations in terms of dictionary meanings, frequency in corpora,
and collocations to answer research questions five and six.
Part 1
Doctoral students who had received lower than 500 on a TOEFL or
TOEFL-like examination had enrolled in English for Post-graduate Students
III. Upon request they wrote two sentences using „loyal‟ and the following
week wrote two sentences using „honest.‟ The results of the error analysis can
be seen in Table 1.
Table 1. Errors in Using Loyal and Honest
Errors
Loyal
Honest
Semantic
#
%
4 3.390
10 8.929
Grammatical
#
%
55 46.660
32 28.571
Other
#
%
7 5.932
0 0.000
Totals
#
%
67 65.932
42 37.500
Fifty-nine students provided two sentences each using „loyal‟ for a total
of 118 sentences of which 52 sentences or 44.068% had no errors related to
the semantic or grammatical use of „loyal.‟ There were few semantic errors
with „loyal‟, (3.390%). All the errors were where „honest‟ was required:
incorrect
correct
*I want a loyal government.
I want an honest government.
incorrect
correct
*I will be loyal with myself and other people.
I will be honest with myself and other people.
There were numerous grammatical errors with „loyal‟ (46.610%). Errors
involved using the adjective „loyal‟ where the position in the sentence required
a noun or a verb, or errors in preposition usage with „loyal.‟
incorrect
correct
*I have loyal.
I am loyal.
incorrect
correct
*I loyal to the King.
I am loyal to the King.
incorrect
correct
*I am loyal the Queen.
I am loyal to the Queen.
6
incorrect
correct
*My friends are loyal for me.
My friends are loyal to me.
In addition, there were errors (5.932%) in using „loyal‟ related to
phonology. „Loyal‟ was used where the writer obviously had confused r and l.
incorrect
correct
*Thai people respect our Loyal Majesty.
Thai people respect our Royal Majesty.
Fifty-four students provided two sentences each using „honest‟ for a
total of 108 sentences of which 58 sentences or 62.50% had no errors related
to the semantic or grammatical use of „honest‟. Here again, there were more
grammatical errors (28.571%) than semantic errors (8.929%). The semantic
errors involved conditions where „loyal‟ was required.
incorrect
correct
incorrect
correct
incorrect
correct
*My sister has an honest dog.
My sister has a loyal dog.
*My dog is honest to me.
My dog is loyal to me.
*I am honest to my boss.
I am loyal to my boss.
The grammatical errors involved using the adjective „honest‟ where the
position required a noun or the verb be with the adjective „honest‟.
incorrect
correct
incorrect
correct
incorrect
correct
*Honest means not copying from another student.
Honesty means not copying from another student.
“I honest myself.
I am honest myself.
*My director has honest.
My director has honesty.
My director is honest.
Part 2
Questions five and six related to the reasons for the students‟
grammatical and semantic errors in using „loyal‟ and „honest.” Though
grammatical errors were more numerous than semantic errors for both words:
„loyal‟ 46.66% vs 3.39% and „honest‟ 28.57% vs 8.93%, they are easily
explained in terms of a lack of control of basic English structure. For the most
part students had trouble with the two following patterns:
have + Noun (loyalty/honesty)
be + Adjective (loyal/honest)
In addition, the students did not use the preposition „to‟ with „loyal.‟ Words in
English often require specific prepositions such as, interested in and annoyed
with. In this study the students either used „for‟ instead of the required „to‟ or
had no preposition following the adjective „loyal‟ as in „He is loyal me.” When
students look up a word in a dictionary, they do not usually see the
preposition that accompanies the word so when they are required to produce a
sentence with the word they often do not know the required preposition.
7
Semantic errors are more difficult to account for. A three pronged
analysis of the two words was carried out: dictionary definitions, word
frequency, and word collocations.
Dictionary definitions
For the English definitions of „loyal‟ and „honest‟, three dictionaries
were consulted: the Collins COBUILD Dictionary (2006), the Oxford Student‟s
Dictionary of Current English (Ruse: 1978), and Webster‟s New Collegiate
Dictionary (1973). For all three „loyal‟ is defined in terms of faithful while
„honest‟ is defined as truthful.
Four bilingual dictionaries were also consulted. The Thai-English
Student‟s Dictionary (Haas: 1964), the SE-ED‟s Modern English-Thai
Dictionary (Thiengburanathum: 1998), the New Model English-Thai and
Thai-English Dictionaries (Sethaputra: 1974), and the on-line Lexitron ThaiEnglish Dictionary (2009). „Loyal‟ was defined in Thai as ซื่อสัตย์, and
จงรักภักดี.
‘Honest‟ was defined in Thai as ซื่อสัตย์,
สุจริต, and ยุตธิ รรม.
Taking the Thai word ซื่อสัตย์ which was listed for both „loyal‟ and „honest‟ we
find the English definitions „honest‟, „faithful‟, and „loyal‟.
Frequency
A survey was made of five corpora sites to study the word frequency of
„loyal‟ and „honest‟. The corpora sites used are as follows:
Brown Corpus: Brown University‟s Professors Kucera and Francis‟s written
corpora of approximately 1 million words was first made available in 1964. It
is available at http://conc/extutot.ca/concordancers/wwwassocwords.pl
Corpus of Contemporary American English (COCA): this four million plus
corpus is maintained by Mark Davies, Professor of Corpus Linguistics, at
Brigham Young University. It includes both spoken (20%) and written (80%)
corpora. It is available at www.americancorpus.org
British National Corpus (BNC): The British National Corpus of one hundred
million words uses both written (90%) and spoken (10%) 20th century English.
It was compiled between 1991-1994. It is available at
www.natcorp.ox.ac.uk/index.xml
COBUILD Collins: Originally known at the Bank of English, this is the largest
collection of English in the world (approximately five hundred and twenty-five
million words). The corpora project was led by Sinclair at the University of
Birmingham in the 1980s. It is available at
www.collins.co.uk/Corpus/CorpusSearch.aspx
VLC Corpus: This user friendly corpora includes the Brown corpus, student
writing, Hong Kong government reports and a wide range of newspapers and
texts from the Bible and Sherlock Holmes stories to sports. Excluding the
Brown corpus and student writing it has over twelve million words. The
website is maintained by the Hong Kong Polytechnic University. It is
available at http://vlc.poly.edu.hk/Concordance/
8
The relative frequency of the two words in the five corpora can be seen
in Table 2.
Table 2. Frequency of Loyal and Honest
Corpora
Brown
COCA
BNC
COBUILD
VLC
(-Brown
-student essays)
Loyal
Instances
Honest
Instances
per million
18
5,070
1,330
64
164
48
12,969
2,855
205
241
1 million
400+ million
100 million
525 million
12 million
While the corpora differ in composition and size, Table 2 shows clearly
that „honest‟ is found without exception far more frequently in the corpora
than „loyal‟. With the exception of the VLC data, „honest‟ occurs more than
twice as frequently as „loyal.‟ Leech et al. (2001) in their book on word
frequencies in the BNC list „honest‟ as 30 instances per million and „loyal‟ as
14 per million which is well in-line with the data presented in Table 2.
Collocations
Collocations tell us the words a word goes with and in doing so gives us
insights into the grammatical and semantic relationships a word has. Today‟s
concordancers offer us a window into how a word works with other words by
allowing us to type in our word and then from the thousands of texts stored in
the corpora site our word will be displayed with the surrounding text. To
carry out this analysis I used the same five corpora and their concordancers
with the exception of the COBUILD corpora for which I used the Collins
COBUILD Advanced Learner‟s Dictionary‟s CD which includes a
concordancer.
A sampling of the collocations for both words indicated which categories to
study. The results of the collocations analysis can be seen in Tables 3 and 4.
Table 3 Collocations for Loyal
Concordancer
Brown
COCA
BNC
COBUILD
VLC
Totals
People
#
18
95
45
95
150
403
Product of
Human Endeavor
%
# %
100.000
0 0.000
94.060
3 2.970
90.000
4 8.000
96.939
2 2.041
91.463
13 7.927
93.504
22 5.104
Animal
Totals
#
0
3
1
1
1
6
#
18
101
50
98
164
431
%
0.000
2.970
2.000
1.020
0.610
1.392
%
100
100
100
100
100
100
As can be seen in Table 3, „loyal‟ is overwhelmingly used with people
(93.505%) as in the „loyal servant‟, followed by a product of human endeavor
9
(5.104%) such as „loyal support‟, „loyal silence‟, „loyal service‟, and „loyal
welcome‟, and with animals (1.392%) such as „dog‟, „pet‟, and „werewolf‟.‟
In addition to the five corpora sites, google.com was also searched for
collocations with „loyal‟. The search produced „loyal dogs‟, „loyal companions‟,
„as loyal as cats‟, and „which breed of dogs is most loyal?‟
Table 4 Collocations for Honest
Concordancer
#
Brown
34
COCA
44
BNC
21
COBUILD 108
VLC
133
Totals
340
People
%
70.833
42.564
42.000
45.958
55.187
50.370
Product of
to be
Human Endeavor honest
# %
# %
11 22.917
0 0.000
36 35.644
18 17.822
12 24.000 13 26.000
42 17.872
70 29.787
69 28.630 32 13.278
170 25.185 133 19.704
Other
#
3
3
4
15
7
32
Totals
%
# %
6.250 38 100
2.970 101 100
8.000 50 100
6.383 235 100
2 .905 241 100
4.741 675 100
As can be seen from Table 4, as with „loyal,‟ most instances of „honest‟
occur with people (50.370%). „Honest‟ also occurs with products of human
endeavor (25.185%) such as „honest dialog‟, „honest mistake‟, „honest day‟s
work‟, „honest service‟, „honest opinion‟, and „honest debate.‟ It was found that
19.704% of the instances of „honest‟ were in the expression „to be honest‟
meaning „really.‟ In addition, „honest‟ was found in the context of „honest
indicator‟ „honest atmosphere‟, „honest sign‟, and one instance (0.148%) of an
animal with „honest‟: “This honest and genuine young stallion is being
produced for the Cranswick stud.” (COUBILD corpus)
A check of google.com for collocations for „honest‟ turned up three
examples of „honest‟ with dogs the first two of which are personifications and
the second means „genuine‟:
1. „Honest Dogs‟ the name of a book by Brian Patrick Donoghue where he
writes of “…furry athletes rested upon the straw…” (Donoghue: 1999, 15).
2. “Honest Dog Gets Reward” an article about a dog that brings a woman‟s
purse home (NYTimes, 1916).
3. „Pit Bulls are a Nice Honest Dog Breed‟ (Writer Gal, 2007).
Before leaving the analysis of data on collocations with „loyal‟ and
„honest‟, I would like to include data from West‟s General Service List of
American Words (West: 1953, 273 and 280). Both „honest‟ and „loyal‟ are
listed in his 2,000 words. Of interest here is West‟s semantic frequencies for
the two words as can be seen in Table 5.
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Table 5. Michael West‟s Semantic Frequencies for Loyal and Honest
Honest
Loyal
330 instances/5 million words
120 instances/5 million words
%
%
1. honest man (of an act)
52
1. loyal friendship;
33
loyal to his friends
2. honest labour; earn an
22
honest living
3. honest opinion; be honest 36
2. loyal to the King; loyal 65
about it with me (frank
subject
truthful)
As seen previously, „honest‟ has a higher frequency than „loyal.‟
West‟s findings also agree with the corpus data findings in that „honest‟
collocates greatest with people as does „loyal.‟
Thailand is also developing a national corpus. The Thai National
Corpus (TNC) will eventually include an 80,000,000 word bank based
exclusively on the standard Thai written language. At present, there are
14,000,000 words (Aroonmanakun: 2000, 154). The Faculty of Arts at
Chulalongkorn University manages the concordance website at
http:www.arts.chula.ac.th/ling/tnc2. A search for ซื่อสัตย์ resulted in a total of
345 instances of the word covering six categories: fiction (72), newspapers
(24), non-academic (77), academic (87), law (39), and miscellaneous (46). A
Thai native speaker who is a law lecturer was asked to examine the 345
occurrences of the word ซื่อสัตย์ and their collocations, and mark whether the
meaning was สุจริ ต (honest -truthful), จงรักภักดี (loyal-friendship), or a
combination of both. The results are shown in Table 6.
Table 6 The Meaning of
Meanings
Corpus
Category
#
Fiction
32
Newspaper
22
Non-academic 54
Academic
75
Law
38
Misc.
39
Totals
260
ซื่อสัตย์ in the Thai National Corpus
สุจริต
จงรักภักดี
„honest‟
%
„loyal‟
# %
#
34
2
19
12
0
6
73
4
0
2
0
0
0
6
44.444
91.667
70.130
86.207
97.436
84.783
75.362
47.222
8.333
24.675
13.793
0.000
13.043
21.159
Combination
%
Unclear
Totals
#
#
%
%
5.556
2 2.778 72 20.870
0.000 0 0.000 24 6.957
2.597
2 2.597 77 22.319
0.000 0 0.000 87 25.174
0.000
1 2.564 39 11.304
0.000 1 2.174 46 13.333
1.739
6 1.739 345 100.000
ซื่อสัตย์ were judged to mean
สุจริ ต (honest) and 26.159% were judged to mean จงรักภักดี (loyal) with 1.739% of
Overall, 75.362% of the examples of
11
the examples judged to include both meanings, and 1.739% not providing a
clear enough context to allow for a judgment. When considered by the
category of the text, it was found that the meaning of „honest‟ was highest in
Law (97.436%) followed by Newspapers (91.667%), Academic (86.207%),
Miscellaneous (84.783%), and Non-academic (70.130%), respectively. The
meaning of „honest‟ was lowest for Fiction (44.444%). The meaning of „loyal‟
for สุจริ ต was highest for Fiction (47.222%) followed by Non-academic
(24.675%), Academic (13.043%), Miscellaneous (13.043%), and Newspapers
(8.333%), respectively. None of the examples of ซื่อสัตย์ in the context of Law
were judged to mean „loyal.‟ Six examples of
ซื่อสัตย์ were judged to combine
the meaning of „loyal‟ and „honest‟: four for Fiction and two for Nonacademic. Six examples were judged not to provide a clear enough context:
one for Law and one for Miscellaneous.
The following is an example of ซื่อสัตย์ in a context judged to mean
„honest‟:
กาหนดคุณธรรมพื ้นฐานที่ควรปลูกฝั งในเด็กไทย คือ ขยัน ประหยัด ซื่อสัตย์
มีวินยั สุภาพ สะอาด สามัคคี มีน ้าใจ
The following are examples of ซื่อสัตย์ in a context judged to mean
Newspapers 8:
„loyal‟:
Fiction 19: ช่างเป็ นคูผ
่ วั ตัวเมียที่จงรักภักดีตอ่ กันนี่เสียกระไร แต่ในชีวิตจริงมีใครบ้ างที่มีเวลาอัน
ซื่อสัตย์ เป็ นของกันและกันอย่างแท้ จริง
Miscellaneous 28: เป็ นต้ นว่า หมาเป็ นมิตรที่ซ่ ือสัตย์ ที่สด
ุ หรื อเป็ นผู้ที่ร้ ูจกั ภักดีมากที่สดุ
The following is an example of ซื่อสัตย์ in a context judged to
combine the meaning of „honest‟ and „loyal‟:
Fiction 9: หล่อนไม่แน่ใจว่าสองคนนี ้รักกัน ซื่อสัตย์ ตอ
่ กันเพียงใด ยิ่งไปกว่านันงิ
้ ้มคิดแล้ วว่าถึง
ตนจะนาตารายาไปให้ บดิ าได้ ทกุ อย่างในร้ านก็ต้องตกเป็ นของน้ องชายอยู่ดี
Conclusions
The purpose of this study was to examine how Thais use „loyal‟ and
„honest‟ in written English. This study is an example of how teachers can
analyze and provide remediation for student errors. The words „loyal‟ and
„honest‟ occur in West‟s General Service List of 2000 words (West: 1953). As
such, one would expect that intermediate level students of English would have
full control of the syntax and semantics of these words. However, as this
study points out, this is not the case. Students‟ writing revealed that over sixty
five percent of the sentences with „loyal‟ and thirty one percent of the
sentences with „honest‟ had grammatical and semantic errors.
Students learn words in isolation and as such fail to realize the context
in which these words occur. The results of this study strongly support the use
of collocations in the teaching of English for acquiring both the syntax and
semantics of lexical items. The majority of the students‟ errors were
grammatical. Students need to see and use the words in context to correctly
12
use the adjectives with the verb „to be‟ (She is honest/loyal) and the nouns
„honesty‟ and „loyalty‟ or adjective and noun patterns with the verb „to have‟ (I
am honest/loyal, I have honesty/loyalty, and I have an honest/ a loyal friend).
This need to examine collocations is especially true to correct errors involving
choice of prepositions following „loyal‟ which is followed by „to‟ (He is loyal to
his boss) and „honest‟ which is followed by „with‟ and „about‟ (honest with
everyone, honest about his faults).
Semantic errors with these two words involve misuse of the two words
by disregarding the core meaning of truthful and lawful for „honest‟ and
faithful for „loyal.‟ While Thai has two separate words to distinguish the
meaning of „loyal‟ from the meaning of „honest‟, it also uses ซื่อสัตย์ alone or
จงรักภักดี to mean „honest‟ and/or „loyal.‟
Students who rely on bilingual dictionaries will thus often find ซื่อสัตย์ when
in combination with
ซื่อสัตย์
or
translating „loyal‟ and „honest‟ into Thai and „honest‟ and „loyal‟ when
translating ซื่อสัตย์ into English. In addition, because „honest‟ has a higher
frequency of use in English, students are less familiar with „loyal‟ and this
might also influence their use of „honest‟ in contexts requiring „loyal.‟
Words need a context. I can think of no better context for
understanding the semantics of the words „loyal‟ and „honest‟ than Rev.
Buehrens‟ sermon (Buehrens: 2005) on „Loyalty Versus Honesty‟ in which
he discusses the moral dilemma when the two come into conflict by using the
example of the whistle blower. If students can recall the whistle blower as
someone in an organization who sees dishonesty and finally chooses to be
honesty but disloyal to the organization he works in, it should help them to
choose correctly between the words „loyal‟ and „honest.‟
The results of this study support previous work advocating the use of
collocations in teaching vocabulary (James:1998 and Boonyasaquan: 2006).
As James (1998, 152) states, “Adherence to the collocational conventions of a
FL contributes greatly to one‟s idiomaticity and native likeness and not doing
so announces one‟s foreignness...”
As I have tried to show in this paper language corpora websites give
teachers and students the tools to access collocations of words easily. Web
concordancers need not be tools used exclusively by wordsmiths. Everyone
can benefit from studying the collocations of words. We would all do well to
learn words with the company they keep (Firth: 1957, 187).
13
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