CONGRUENT AND METAPHORICAL CODING IN MOOD AND SPEECH FUNCTION OF DONALD TRUMP’S UTTERANCES IN FACE THE NATION TALK PROGRAM
A THESIS
By
LILIAN 177052012/MBE
ENGLISH POSTGRADUATE STUDY PROGRAM FACULTY OF CULTURAL SCIENCES UNIVERSITY OF SUMATERA UTARA MEDAN 2019
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CONGRUENT AND METAPHORICAL CODIN IN MOOD AND SPEECH FUNCTION OF DONALD TRUMP’S UTTERANCES IN FACE THE NATION TALK PROGRAM
A THESIS
Submitted as the Partial Fulfillment of Requirement for the Degree of Master of Arts (M.A.) in English Postgraduate Study Faculty of Cultural Sciences, University of Sumatera Utara
By
LILIAN 177052012/ MBE
FACULTY OF CULTURAL SCIENCES UNIVERSITY OF SUMATERA UTARA MEDAN 2019
Universitas Sumatera Utara
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ABSTRACT
This research is entitled Congruent and Metaphorical Coding in Mood and Speech Function of Donald Trump’s Utterances in Face the Nation Talk Program. It aims to find out the types of Mood and Speech Function and to describe Congruent and Metaphorical Coding based on Mood and Speech Function realized in Donald Trump’s utterances, the president of the United States of America. The data source are all of the question from the presenter, Margaret Brennan in the video which take place in a studio on Sunday, February 3rd 2019 and the duration is 28 minutes 37 second. The video and the script are downloaded from internet. The data are Trump’s utterances transcribed into the data namely 607 clauses. Then, they are analyzed based on Halliday’s theory about Mood Types, Speech Function and Congruent or Metaphorical Coding of them. This research is conducted by applying descriptive qualitative research. The researcher wants to describe and to categorize the types of Mood and Speech Function realized in Trump’s utterances. Then, they are analyzed into Congruent and Metaphorical coding in Mood and Speech Function realization. The findings are there are 4 Mood Types founded in Trump’s utterances namely Descriptive Mood, Interrogative Mood, Imperative Mood and Modulated Interrogative Mood and there are 30 Metaphorical Coding consisted of 5 Metaphorical coding of Mood and Speech Function realization. They are Declarative Mood realized in Command 6 clauses (20 %), Interrogative Mood realized in Statement 4 (13.33 %), Declarative Mood realized in Question 13 clauses (43.33 %), Imperative Mood realized in Statement 4 clauses (13.33 %) and Declarative Mood realized in Offer 1 clause (3.33 %). The most frequency of Metaphorical coding in Trump’s utterances is Declarative Mood realized in Question. It means that Trumps uses Declarative Mood but it is actually to express Question in Speech Function.
Keywords: congruent, metaphorical coding, mood, speech function
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ABSTRAK
Penelitian ini berjudul Pengkodean Kongruen dan Metafora (tidak Kongruen) berdasarkan Modus dan Fungsi Kalimat dari ungkapan Donald Trump dalam Face the Nation Talk Program. Tesis ini bertujuan untuk mengetahui jenis-jenis Modus dan Fungsi Kalimat serta untuk menggambarkan Pengkodean Kongruen dan Metafora berdasarkan Modus dan Fungsi Kalimat yang direalisasikan dalam ungkapan Donald Trump yang merupakan seorang presiden Amerika Serikat. Sumber data adalah semua pertanyaan dari pembawa acara yaitu Margaret Brennan dalam sebuah video yang berlangsung di studio pada hari Minggu, 3 Februari 2019 dan durasinya 28 menit 37 detik. Video dan skrip diunduh dari internet. Data penelitian ini adalah ungkapan Donald Trump yang disalin dan menjadi 607 klausa. Kemudian, klausa tersebut dianalisis berdasarkan teori Halliday tentang Pengkodean Kongruen dan Metafora berdasarkan Modus dan Fungsi Kalimat. Penelitian ini dilakukan dengan menggunakan penelitian deskriptif kualitatif. Peneliti ingin menggambarkan dan mengkategorikan jenis Modus and Fungsi Kalimat yang terealisasi dalam ungkapan Trump. Kemudian, klausa-klausa tersebut dianalisis ke dalam pengkodean Kongruen dan Metafora dalam realisasi Modus and Fungsi Kalimat. Penemuannya ada 4 jenis Modus yang ditemukan yaitu Modus Deskriptif, Modus Interrogatif, Modus Imperatif dan Modus Modulasi Interogatif serta ada 30 klausa yang merujuk pada pengkodean Metafora yaitu terdiri dari 5 pengkodean Metafora berdasarkan perwujudan Modus dan Fungsi Kalimat. 6 Modus merupakan Modus Deklaratif yang diwujudkan dalam kalimat perintah(20%), 4 Modus Interogatif yang diwujudkan dalam kalimat pernyataan (13.33%), 13 Modus Deklaratif yang di wujudkan dalam pertanyaan (43.33%), 4 Modus Imperatif yang diwujudkan dalam kalimat pernyataan, dan 1 Modus Deklaratif yang diwujudkan dalam kalimat penawaran. Pengkodean yang paling dominan di dalam ungkapan Trump adalah Modus Deklaratif yang di wujudkan dalam pertanyaan. Hal ini berarti bahwa Trump menggunakan Modus Deklaratif dalam tetapi mengekspresikannya dengan kalimat pertanyaan dalam Fungsi kalimat.
Kata Kunci: kongruen, pengkodean metafora, modus, fungsi kalimat
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ACKNOWLEDGEMENT
Praised be to Allah, Lord of the world, who has given the writer His love and compassion to finish the last assignment in his study. Peace and salutation be upon to the prophet Muhammad SAW, his family, his companion and his adherence. It is a pleasure to acknowledge the help and contribution to all of lecturers, family, and friends who have contributed in different ways hence this thesis is processed until it becomes a complete writing which will be presented to the Postgraduate Program of English in the University of Sumatera Utara in partial fulfillment of the requirements for the degree of Master of Art in English. She would like to express her great honor and deepest gratitude to:
1. The Dean of Faculty of Cultural Studies, University of Sumatera Utara, Dr. Drs. Budi Agustono, M.S. 2. The Head of Department of English, Dr. Ridwan Hanafiah, S.H., M.A. and The Secretary of Department of English, Dr. Drs. Umar Mono, Dipl. Trans., M.Hum. 3. Her supervisors, Prof. Dr. Syahron Lubis, M.A. and Dr. Nurlela, M.Hum. who have patiently guided the researcher and provided input and suggestion in completing her thesis. 4. Her reviewers, Dr. Ridwan Hanafiah,S.H., M.A., Dr. Eddy Setia M.Ed TESP, Dr. Muhizar Muchtar, M.S. who have provided valuable knowledge in supporting her thesis, as well as all lecturers and staffs for helps during her academic year. 5. Her father and mother, Muchtar and Syamsiar who have given a lot of loves, cares, prayers, supports, and advice. 6. Her lovely husband and daughters Hakiki Mahedi Hasibuan, S.Sos., Mughny Shaliha Hasibuan and Aisha Inara Hasibuan who have motivated in other adorable ways. 7. Her leaders and partners in Yayasan Adzkia International, SMA Islam Plus ADZKIA, Bimbel ADZKIA STAN, Muhammad Ramli S.T., M.Si., Wahyudi, M.M., Dr. Dicky Nofriansyah, M. Kom. 8. Her brothers and sister, Rahmadany, Budy Harry, Almh. Wiwik Andriani who never stopped motivating her in accomplishing this thesis. 9. Her postgraduate Darlyngs friends and best friends, Dwi Mahartika, M.A., Siti Hajar, M.A., Yetty Wirasini, S.S, Rudang Mayang Sari, S.Pd, Syayu Mutiara, S.S, Tri Indah Widya Pratiwi, Tomi
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Wahendra, Amin Rosyidi and Maam Adri who have shared the valuable knowledge, times, touches of laughter and smiles. 10. Her everlasting mates, Rizky Hidayani, M.A., Della Fransiska Ginting, M.A., Rina Mariati, S. Pd, Faisal Asdani, S.Pd., Annisa Risma Khairani Lubis, S.Pd., Anni Alvionita Simanjuntak S.Pd, M. Eryca Ronauli, S. Pd., Budi Awan Marpaung, S.S., Agus Salim, S.S., who have given supports and prays.
Medan, 15th August 2019
The writer,
Lilian 177052012
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CURRICULUM VITAE
Personal Data Name : Lilian Place, Date of Birth : Medan, August 8th 1986 Gender : Female Religion : Moeslim Nationality : Indonesia Address : Jl Pancing Gg. Mesjid Istiqomah No. 03 Medan Phone Number : 082365008766 Email : [email protected] Academic Background 1992 – 1998 SDN 067689 Medan 1998 – 2001 SLTPN 3 Percut Sei Tuan 2001 – 2004 MAN 1 Medan 2004 – 2008 State University of Medan (UNIMED) 2017 – 2019 University of Sumatra Utara (USU) Working Experience Years Officers/ Companies Positions 2007 – 2008 BT/BS BIMA English Tutor 2008 – 2009 Sony Sugema College English Tutor 2010 – 2011 TELKOMSEL, Tbk Caroline Officer 2011 – 2012 NCC English Coordinator 2012 – 2014 Yayasan Pendidikan English Teacher Shafiyyatul Amaliyah 2014 – 2016 CARNEGIE NATIONAL English Teacher PLUS SCHOOL 2016 – 2018 EDU GLOBAL SCHOOL Vice Principle 2018 – 2019 SMA PLUS SEDAYU English Teacher NUSANTARA 2009 – 2019 ADZKIA STAN English Tutor 2019 – now SMA Islam Plus Adzkia Vice Principle
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TABLE OF CONTENT
Page
ABSTRACT ...... i ABSTRAK ...... ii ACKNOWLEDGEMENT ...... iii CURRICULUM VITAE ...... v TABLE OF CONTENT ...... vi LIST OF TABLE ...... viii LIST OF FIGURE ...... ix LIST OF APPENDICES ...... x CHAPTER I INTRODUCTION ...... 1 1.1 The Background of the Study ...... 1 1.2 The Focus of the Research ...... 7 1.3 The Research Questions ...... 7 1.4 The Objective of the Research ...... 8 1.5 The Significance of the Research ...... 8 CHAPTER II REVIEW OF LITERATURE ...... 9 2.1 Language ...... 10 2.2 Spoken and Written Language ...... 12 2.3 Systemic Functional Grammar ...... 10 2.4 Metafunction ...... 13 2.4.1 Ideational Function ...... 13 2.4.2 Textual Function ...... 13 2.4.3 Interpersonal Function ...... 14 2.4.3.1 Mood ...... 15 2.4.3.2 Mood Elements ...... 15 2.4.3.3 Finite Elements ...... 16 2.4.3.4 Mood Types ...... 23 2.4.3.4.1. Indicative Mood ...... 25 2.4.3.4.1.1 Declarative Mood ...... 25 2.4.3.4.1.2 Interrogative Mood ...... 26 2.4.3.4.1.3 Imperative Mood ...... 28 2.4.3.4.1.4 Exclamative Mood ...... 28 2.5 Speech Function ...... 29 2.6 Congruent and Metaphorical Coding ...... 35 2.7 Donald John Trump ...... 41 2.8 Face the Nation Talk Program ...... 42 2.9 Relevant Studies...... 43 2.10 Conceptual Framework ...... 45 CHAPTER III RESEARCH METHODOLOGY ...... 47 3.1 Research Design...... 47 3.2 The Data and Data Source ...... 47 3.3 Techniques of Data Collection...... 48 3.4 Techniques of Data Analysis ...... 49 3.5 Trustworthiness of The Study ...... 50 CHAPTER IV FINDINGS AND DISCUSSIONS ...... 53 4.1 Findings………...... 53 4.2 Mood Types in Trump’s Utterances ...... 54
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4.2.1 Declarative Mood...... 54 4.2.2 Interrogative Mood ...... 57 4.2.3 Imperative Mood ...... 59 4.2.4 Modulated Interrogative Mood ...... 61 4.3 Speech Function in Trump’s Utterances ...... 62 4.3.1 Statement...... 65 4.3.2 Question ...... 65 4.3.3 Command ...... 65 4.3.4 Offer ...... 65 4.4 Coding in Trump’s Dialogue ...... 66 4.4.1 Congruent Coding in Mood and Speech Function Realization ...... 78 4.4.2 Metaphorical Coding in Mood and Speech Function Realization ...... 79 4.4.2.1 Declarative Mood Realized in Command ...... 79 4.4.2.2 Interrogative Mood Realized in Statement ...... 80 4.4.2.3 Declarative Mood Realized in Question ...... 81 4.4.2.4 Imperative Mood Realized in Statement...... 81 4.4.2.5 Declarative Mood Realized in Offer ...... 82 4.5 Discussion ...... 82 CHAPTER V CONCLUSION AND SUGGESTION ...... 84 5.1 Conclusions ...... 84 5.2 Suggestions ...... 86 REFERENCES ...... 87 APPENDIX 1 ...... 91 APPENDIX 2 ...... 102 APPENDIX 3 ...... 114 APPENDIX 4 ...... 171
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LIST OF TABLE
Table 2.1 The Oral-Written Dichotomy ...... 11 Table 2.2 Finite Verbal Operators ...... 17 Table 2.3 List of Mood Adjunct Types ...... 22 Table 2.4 Mood Types and Their Speech Functions ...... 24 Table 2.5 Giving or Demanding, Goods & Services or Information ...... 30 Table 2.6 Speech Functions and Responses ...... 30 Table 2.7 Speech Functions and Typical Mood in Clause ...... 34 Table 2.8 Congruent and Metaphorical Realization of Mood ...... 35 Table 2.9 Congruent and Metaphorical Realization of Speech Function ...... 39 Table 2.10 Congruent and Metaphorical Coding in Trump’s Utterances ...... 40 Table 4.1 Frequency of Mood Types in Trump’s Utterances ...... 62 Table 4.2 Frequency of Speech Function in Trump’s Utterances ...... 66 Table 4.3 Congruent and Metaphorical Coding in Trump’s Utterances ...... 67 Table 4.4 Frequency of Congruent and Metaphorical Coding in Trump’s Utterances ...... 78 Table 4.5 Declarative Clause Realized in Command ...... 80 Table 4.6 Interrogative Clause Realized in Statement ...... 80 Table 4.7 Declarative Clause Realized in Question ...... 81 Table 4.8 Imperative Clause Realized in Statement ...... 82 Table 4.9 Declarative Clause Realized in Offer ...... 82
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LIST OF FIGURES
Figure 2.1 Mood Types ...... 24
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LIST OF APPENDICES
No Title Page
1 Transcription of Interview between Donald Trump 91 and Margaret Brennan in Face the Nation Talk Program 2 Donald Trump’s Utterances in Face the Nation Talk Program 102 3 Mood Types in Donald Trump’s Utterances 114 in Face the Nation Talk Program 4 Congruent and Metaphorical Coding of Trump’s 171 Utterances in Face the Nation Talk Program
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CHAPTER I
INTRODUCTION
1.1 The Background of the Research
Language is a tool of communication among human beings. Communication is one of the most important skills in our life. By good and smooth communication, we can reach our purpose and convey our message to others. Human beings as a social creature communicate one another to run their life.
In the application, language consists of two different ways that is spoken and written language. Gerot and Wignell (1994) state that spoken and written languages are both complex but in different ways.
Spoken language tends to be complex lexically. Spoken language tends to be grammatically intricate whereas written language tends to be lexically dense.
In Linguistic Functional Systemic, language is meaning system and other system (form and expression) to realize the meaning (Saragih: 2016). There are two concept differentiating Linguistic
Functional Systemic from other linguistic systemics, that is: (a) language is social phenomenon as social semiotic and (b) language is construal text with social context so that all language research released from social context.
The first concept has meaning that as a semiotic, language consists of two elements: meaning and expression. The relationship is meaning realized in expression. Nevertheless, it is different from the semiotic, social semiotic of language has other semiotic that is form/grammar. To conclude, language in social interaction consists of three elements such as: meaning, grammar and expression.
These three elements can be called as: meaning (semantic or discourse semantics) realized in form
(lexico grammar) and this form also coded by expression (phonology/graphology).
Both spoken and written form deliver the meaning in a sentence. A sentence consists of words which has meaning systematically. In using language, people need a pattern to make the messages understandable. So that it is delivered clearly. The pattern is called grammar. According to traditional grammar a sentence consists minimally of Subject and Predicate (Mood) and a complex sentence
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consists of Subject, Predicate, Object/ Complement and Adverb. The Predicate in the Functional
Grammar is called by Mood.
Traditional grammar aims to describe the grammar of standard English by comparing it with
Latin. Formal grammar is concerned with describing the structure of individual sentences. Functional grammar views language as resource for making meaning. This grammar attempts to describe language in actual use and focuses on text and their context. They are concerned not only with the structures but also with those meaning constructions. Functional grammar called functional linguistics considers function or metafunction and semantics as the bases of human language and communicative activity.
Halliday (1985: xii) states “The fundamental components meaning in language are functional components. All languages are organized around three main kinds of meanings such as ideational meanings, interpersonal meanings and textual meanings”. These principal components of meaning or metafunctions are added in the structure of clause.
Interpersonal metafunctions are meanings which express a speaker’s attitude and judgments.
These are meanings for acting upon with others. Meanings are realized in wordings through what is called Mood and Modality. They are most centrally influenced by tenor of discourse.
Mood is the central aspect of the grammar of exchange and its elements including subject have a function to construct a role of clause as an exchange. According to Gerot and Wignell (1994), “the
Mood element consists two parts, they are subject, which is realize by a nominal group and finite element, which is part of the verbal group. The rest of verbal group is the predicator, which forms part of the residue. A clause thus consists of Mood + Residue. Mood element has a clearly defined semantic function: it carries the burden of the clause as an interactive event. So, it remains constant, as the nub of the proposition, unless some positive step is taken to change it. Not only concern with the grammar but also with the meaning.
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Language also has a meaning so as to deliver the meaning or idea between the speaker and the listener. It is why to study about Speech Function and the realizations.
1. Language functions to fulfill human needs in the exchange of experience. Human beings need to
exchange experience as follows: human kinds are social beings, ‘social products’ and consequently
cannot live isolated.
2. No one can completely fulfill one’s needs; one needs others and only human beings are destined
with ineterpersonal function; human culture and civilazation; history.
Speech Function is a way how someone delivers ideas in communication to make listeners understand the ideas well. Speech Function itself can be divided into four kinds: statement, question, command and offer.
Another function of language is a coding. Bernstein made a significant contribution to the study of communication with his sociolinguistic theory of language codes. Within the broader category of language, systems are elaborated and restricted codes. The term code as defined by Stephen Little John in Theories of Human Communication (2002), “refers to a set of organizing principles behind the language employed by members of a social group”. Little John (2002) suggests that Bernstein’s theory shows how the language people use in everyday conversation both reflects and shapes the assumptions of a particular social group. Furthermore, the relationships established within the social group affect the way that the group uses language and the type of speech uses.
A language is a coding system and means by which information may be transmitted or shared between two or more communicators for purposes of command, instruction or play. It realizes in
Congruent and Metaphorical Coding. A sentence which has a same idea or meaning in Mood
(grammar) and Speech Function (meaning) is called by Congruent Coding. While a sentence which has a different idea or meaning in Mood (grammar) and Speech Function (meaning) is called by
Incongruent or Metaphorical Coding.
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Halliday argues that the potential for this kind of decoupling and recombination is a basic
design feature of human language. The possibility of re-setting the relationships between meanings
and wordings, which is a central resource for expanding the meaning potential of language, is known
as grammatical metaphor. (Thompson: 2014)
This research analyzed Congruent and Metaphorical Coding of grammatical metaphor in Mood
(grammar) and Speech Function (meaning). Congruent coding is Mood and Speech Function in the
same way such as Declarative realized in Statement, Interrogative realized in Question, Imperative
realized in Command and Modulated Interrogative realized in Offer. Furthermore, it was called by
Metaphorical Coding when it was different way such as Declarative realized in Question, Command
and offer, Interrogative realized in Statement, Command and Offer, Imperative realized in Statement,
Question and Offer and Modulated Interrogative realized in Statement and Command or vice versa.
The realizations of Speech Function and Mood can be described in both oral and written form.
In this research, Trump’s utterances as the oral language and then printed in written form. The data are all the clause uttered by Trump in Face the Nation Talk Program.
In this modern life, both language and technology grow rapidly. People use language to communicate one another by using modern technology and service. In spoken language besides taking a direct conversation by face to face, people use media as telephone or video call to make a conversation. In conveying news and information also has grown, not only in written but also spoken.
Television is as one of media in transferring information provide many program to entertain and to inform the society. It can be said that the growth of language along with the growth of technology.
This research focuses on talk show as one of program television consisted of discussion various topics.
Face the Nation is a weekly news and morning public affairs program broadcasted on Sundays
on the CBS radio and television network, created by Frank Stanton in 1954. Face the Nation is one of
the longest-running news programs in the history of television. Margaret Brennan is the current
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moderator of Face the Nation, though former host John Dickerson has substituted during Brennan’s maternity leave.
In this research, the data source was Face the Nation talk program, which was in spoken form namely all the questions from the interviewee or the presenter, Margaret Brennan, and the data were the clauses of the interviewees, Donald Trump as the President of the United States. The researcher chose the data found in Face the Nation because this showed the largest of all Sunday public affairs programs in 2017, with an average of 3.538 million viewers. It also presented many distinguished and influencing guess in the world. Trump’s dialogue was chosen due to he is the 45th and current president of the United States. He is one of the powerful man in oration. Much of his utterance is controversial speech. Metaphorical Coding was used for any reasons and one of them is power. This research explained it by analyzing Mood and Speech Function.
1.2 The Focus of the Research
As the main purpose of this study was to analyze how the Mood and the Speech Function were realized in this political talk program. Finding out the realizations of Moods and Speech Function uttered in this program. The findings enabled other speakers to figure out the Mood and Speech
Function and also the realizations. It also conveyed that Metaphor analysis in this case was analysis of
Congruent and Incongruent (Metaphorical) used in this political talk program. In addition, the findings also enriched understandings on how to communicate properly and based on shared knowledge of turn taking and speech acts.
1.3 The Research Questions
Based on the explanation above, the followings are the questions of the present research:
1. What kinds of Mood and Speech Function are used by Trump in Face the Nation talk program?
2. How Congruent and Metaphorical coding of Mood and Speech Function are realized by Trump in
Face the Nation talk program?
3. Why are Congruent and Metaphorical Coding of Mood and Speech Function as the way there are?
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1.4 The Objective of the Research
Based on Research Questions above, here are the objectives of the research:
1. To identify Mood and Speech Function of Trump’s utterances in Face the Nation talk program.
2. To analyze Congruent and Metaphorical Coding of Mood and Speech Function in of Trump’s
utterances in Face the Nation talk program.
3. To explain the use of Congruent and Metaphorical Coding of Mood and Speech Function of
Trump’s utterances in Face the Nation talk program.
1.5 The Significance of Research
As this research was to examine the use of Mood and Speech Function in Face the Nation talk
program. The research made an attempt not only to identify but also to analyze the use of Congruent
and Metaphorical Coding of Mood and Speech Function in Face the Nation program.
It is expected that the research may lead to a better understanding of the relation between the
use of Mood and Speech Function in spoken language that is a political talk program. This research is
also expected to provide a contribution for some advantages in linguistic study, particularly the branch
of New Approach for English Grammar and Systemic Functional Grammar and to embellish the
knowledge of Mood and Speech Function and Congruent and Metaphorical coding to build a good
sentence, paragraph, text or written or spoken language and determine the functions those of which in
spoken language.
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CHAPTER II
REVIEW OF RELATED LITERATURE
2.1 Language
Language can be used as a tool of communication in transmitting or sharing a message, news, information by spoken and written language between two or more communicators for purposes of command, instruction or play. Jackson and Howard state that “language is the particular form of verbal communication used by a specific group of speakers.
A language is defined in part by the particular characteristics of its pronunciation, grammatical structure and vocabulary. It is the human faculty that enables us to exchange meaningful messages with some of our fellow human beings by means of discourse and text, which are structured according to the rules and conversations of the particular language that people share with those fellow human beings.
"A language consists of symbols that convey meaning, plus rules for combining those symbols, that can be used to generate an infinite variety of messages." (Wayne Weiten: 2007). Language is a symbol and a meaning which presents a message and it can be used to share idea and information. We can define language as a system of communication using sounds or symbols that enables us to express our feelings, thoughts, ideas, and experiences." (E. Bruce Goldstein: 2008). The system is the rules used to raise the communication goal.
Language in social interaction consists of three elements: meaning, form/grammar and expression. In other word, Linguistic Functional Systemic consists of three levels: semantic, grammar and phonology. This research focused on analyzing language in grammar (Mood) and meaning
(Speech Function).
2.2 Spoken and Written Language
In this early times, parallel to writing, speaking has also become more adequate and perfect day by day. As a result, research into spoken and written language in English, the global language, has
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been properly addressed. One of the principal aims of this reflection is to analyze how to distinguish between spoken and written grammar.
There are many different definitions of spoken and written language. However, in a minor
scope of the paper, I will give a definition given by Horowitz and Samuels (1987):
Oral language is typically associated by linguists with conversation that is produced, processed, and then evaluated in the context of face-to face exchange and grounded in interpersonal relationships that are often clearly established. Oral language is adapted to a specific audience and to socio-cultural settings and communities that are presumably present, functioning in a context of here and now (p.56).
In contrast:
Written language is typically associated with language of books and explanatory prose such as
is found in schools. Written language is formal, academic, and planned; it hinges on the past
and is reconstructed in such a way that in the future it can be processed by varied readerships.
(p.21)
Spoken and written language are expression side of language, the media by which people disseminate their verbal message. All languages have a spoken form, but not all written, and no natural language has existed in a written form before being a spoken language. Horowitz and Samuels mentions the differences between spoken and written language as shown in table 2.1:
Table 2.1 The oral-written dichotomy (Horowitz and Samuels, 1987)
Oral-Language Written-Language
Talk Text
Face to face conversations with Face to text with limited reciprocity
reciprocity between speaker and between author and reader
listener
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Narrative-like Expository-like
Action-oriented Idea-oriented
Event-oriented Argument-oriented
Story-oriented Explanatory
Here and now Not space-or-time-bound
Informal Formal
Primary discourse Secondary discourse
Natural communication Artificial communication
Interpersonal Objective and distanced
Spontaneous Planned
Sharing of context (situational) No common context
Ellipsis Explicitness in text consciousness
Structureless Highly structured
Cohesion through paralinguistics Cohesion through lexical cues cues
Single predication Multiple predication
Repetition Succinctness
Simple linear structures Complex hierarchical structures
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Paratactic patterns Hypotactic patterns
Right branching with limited Left branching with multiple levels
subordination of subordination
Fleeting Permanent
Unconscious Conscious and restructured
2.3 Systemic Functional Grammar
The term “systematic” refers to the view of language as “a network of systems, or interrelated sets of options for making meaning, as opposed to formal grammar, which focuses on word classes such as nouns and verbs, typically without reference beyond the individual clause. Grammar is one of the subsystems of language; more specifically, it is the system of wordings of a language.
Systemic Functional Grammar is the study of linguistics forms in relation to the meaning that they express. It described as a functional-semantic approach to language which explores both how people use language in different context, and how language is structured for use as a semiotic system.
2.4 Metafunction
Meaning is essentially equated with function, called Metafunction and it is describing language from this perspective appears at first sight to be a much less manageable task than describing the structures.
According to Halliday (1985: xii) the fundamental components of meaning in language are functional components. All languages are organized around three kinds of meaning: interpersonal meaning, experiential meaning, and textual meaning. Three types of metafunctions or meanings are expressed through language because these are strands of meaning we need to make in order to make sense of each other and the world. They can be explained as follows:
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2.4.1 Ideational Function
Experiential Functions or Ideational Functions are functions or meanings about phenomena or about thing (living and non-living, abstract and concrete), about goings on (what he doings). These meanings are realized in wordings through participants, processes, and circumstances. Meanings of this kind are most centrally influenced by the field of discourse.
2.4.2 Textual Function
Textual Functions express the relation of language to its environment, including both the verbal environment, what has been said or written before (context). These functions are realized through pattern of theme and cohesion. Textual functions are most centrally by mode of discourse.
2.4.3 Interpersonal Function
Interpersonal Functions are functions or meanings which express a speaker’s attitudes and judgments. These are meanings for acting upon and with others. Meanings. Meanings are realized in wordings through what is called Mood and modality. Meanings of this kind are most centrally by the tenor of discourse.
Interpersonal functions are meanings which express a speaker’s attitudes and judgments (Gerot and Wignell: 1994). These are meanings for acting upon and with others. Meanings are realized in wordings through what is called Mood and modality. Meanings of this kind are most centrally influenced by the tenor of discourse.
Interpersonal functions construing tenor are realized lexicogrammatically by the system of
Mood and modality with the Mood element further analyzed into subject and finite. This metafunction is about social world, especially the relationship between speaker and hearer, and concerns with the clause as exchanges.
People use language to make interpersonal meanings; meanings about the role relationships with other people and attitudes to each other. Language used are always expressing an attitude and taking up a role. When we use language, there is always something else going on. While construing,
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language is always also enacting; enacting our personal and social relationships with other people around us. The clause of grammar is not only a figure, representing some process-some doing or happening, saying or sensing, being or having-together with its various participants and circumstances; it is also a proportion, or a proposal, whereby we inform or question, give an order or make an offer, and express our appraisal of and attitude towards whoever we are addressing and what we are talking about. This king of meaning is more active; this is language as action Halliday (2004:45).
2.4.3.1 Mood
The Mood carries the interpersonal functions of the clause and consists of subject + finite.
Eggins (1994:152) states that “the Mood structure of the clause refers to the organization of the set of functional constituent, including constituent subject.”
Mood is the central aspect of the grammar of exchange and its elements including subject have a function to construct a role of clause as an exchange.
2.4.3.2 Mood Elements
According to Gerot and Wignell (1994:25), “the Mood element consists two parts, they are subject, which is realize by a nominal group and finite element, which is part of the residue. A clause thus consists of Mood + Residue.
According to Halliday (2004:111), when we come to look closely at statements and questions, and at the various responses to which these naturally give rise, we find that in English they are typically expressed by means of a particular kind of grammatical variation: variation which extends over just one part of the clause, leaving the remainder unaffected.
Mood element has a clearly defined semantic function: it carries the burden of the clause as an interactive event. So it remains constant, as the nub of the proposition, unless some positive step is taken to change it. What is the component that is being bandied about in this way? It is called the Mood element, and it consists of two parts: (1) the Finite operator, which is part of a verbal group, and (2) the Subject, which is a nominal group.
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2.4.3.3 Finite Elements
Gerot and Wignell (1994:25) state that “the finite element is one of the small numbers of verbal operators expressing tense, modality and polarity”. The Finite element, as its name implies, has the function of making the proposition to its context in the speech event.
Finite is being the core that is bandied about exchanges because it carries the validity of the proposition (Thompson, 2004). Finite can be divided into two kinds; Finite Verbal Operator Temporal and modal.
Temporal Finite Verbal Operators: these words anchor the preposition by reference to time but reference to Modality.
Examples:
I don’t take anything off the table
Subject Finite Residue Mood
It Is national emergency
Subject Finite Residue
Mood
Table 2.2 lists the Finite verbal operators, positive and negative. Note that some of the negative forms, such as mayn’t , are rather infrequent; if they occur in a negative clause, the negative is usually separated (may not, used not to). In such cases, the not can be analyzed as part of the Residue; but it is important to note that is an oversimplification-sometimes it belongs functionally with the Finite.
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Table 2.2 Finite Verbal Operators
Temporal Operators
Past Present Future
Positive did, was, had, used to does, is, have will, shall, would, should
Negative didn’t, wasn’t, doesn’t, isn’t, hasn’t won’t, shan’t, wouldn’t, shouldn’t
hadn’t, didn’t + used
to
Modal operators
Low Median High
Positive can, may, could, will, would, should, Must, ought to, need, has/had to
might (dare) is/was to
Negative needn’t, doesn’t/ won’t, wouldn’t, Mustn’t, oughtn’t to, can’t, couldn’t,
didn’t + need to, have shouldn’t, (isn’t/wasn’t (mayn’t, mightn’t, hasn’t/hadn’t to)
to to)
(Halliday 2004:116)
For example:
You may not leave before the end (‘are not allowed to’): not is part of Finite
You may not stay right to the end (‘are allowed not to’): not is part of Residue
a. Subject Elements
“Subject is something by reference to which the proposition can be affirmed or defined”. It
provides the person or thing in whom is vested the success or failure of the proposition, what is “held
responsible” (Halliday 1995:76).
Eggins and Slade (1994:75) state that subject is the pivotal participant in the clause, the person or thing that the preposition is concerned with and without whose presence there could be no argument or negotiation.
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Gerot and Wignell (1994:28) explain that “the subject is that upon which the speaker rests his case in exchanges of information, and the one responsible for insuring that the prescribed action is or is not carried out in exchange of goods and services”.
Example:
It Is The other things
Subject Finite Residue Mood
b. Predicator
Predicator encodes the action or process involved in the clause. It gives to verbal element of the proposition, telling listeners what is or was happening.
Gerot and Wignell (1994:31) explain that the predicator is the verb part of the clause; the bit which tells what’s doing, happening or being. There are also non-finite (‘to’ + verb and verb + ing’) clauses containing a Predicator but no Finite element.
Examples:
She Knows (does) That you need a barrier
Subject Finite Predicator Complement
Mood Residue
c. Complement
Complement is a participant which is somehow implicated in the proposition. The complement answers the questions ‘is/had what’, ‘to whom’, ‘whom’, did to what’
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Examples:
She is Doing a terrible disservice
to
Subject Finite Predicator Complement
Mood Residue d. Adjunct
An Adjunct is an element that has not got the potential of being Subject; that is, it cannot be elevated to the interpersonal status of modal responsibility. This means that arguments cannot be constructed around those elements that serve as Adjuncts; in experiential terms, they cannot be constructed around circumstances, but they can be constructed around participants, either actually, as
Subject, or potentially, as Complement. An Adjunct is typically realized by an adverbial group or a prepositional phrase (rather than by a nominal group).
There are three main types of adjuncts; circumstantial, interpersonal and textual.
Circumstantial Adjuncts
These are adverbs or prepositional phrases which express meanings about when, where, how, why, or with the preposition occurred.
Example:
You (do) Look At Afganistan
Subject Finite Predicator Circ. Adjunct
Mood Residue
Conjunctive Adjuncts
Conjunctive Adjuncts include items such as ‘for instance’, ‘anyway’, ‘moreover’, ‘meanwhile’,
‘therefore’, ‘nevertheless’.
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Conjunctive Adjuncts (sometimes called ‘discourse markers’) have the function of signaling
how the clause as a whole fits in with the preceding text. The meanings that they express are textual
meanings.
Examples:
Because I Do Love To watch football
Conjunctive Adjunct Subject Finite Pred. Complement
Mood Residue
Comment Adjunct
Comment Adjuncts express the speaker’s comment on what he or she is saying. Comment Adjuncts
include such as ‘frankly’, ‘apparently, ‘hopefully’, broadly speaking’, ‘understandably’, ‘to my
surprise’. They express interpersonal rather than textual meanings, but fall outside of Mood-Residue
structure.
Example:
Well He Is requested a meeting
Comment Adjunct Subject Finite Predicator Complement
Mood Residue
Mood Adjuncts
Mood Adjuncts relate specifically to the meaning of the finite verbal operators, expressing probability, usuality, obligation, inclination or time.
Example:
Hitting the Frankly We Are caliphat
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e from
Iraq
Predicate Comple Mood Adjunct Subject Finite ment
Mood Residue
Table 2.3 List of Mood Adjunct Types
Type Meaning Examples
Polarity Not, yes, no
Probability “How likely?” Probably, possibly, certainly, perhaps, maybe
Usuality “How often?” Usually, sometimes, always, never, ever,
seldom, rarely
Readiness “I want to” Willingly, readily, gladly, certainly, easily
Obligation “You must” Definitely, absolutely, possibly, at all cost, by all
means
Time Yet, still, already, once, soon, just
Typicality “How Occasionally, generally, regularly, mainly
typical?”
Obviousness “How Of course, surely, obviously, clearly
obvious?”
Intensity Just, simple, merely, only, even, actually, really
Degree Quiet, almost, nearly, scarcely, hardly,
absolutely, totally, utterly, entirely, completely
Halliday (1994:49)
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2.4.3.4 Mood Types
Gerott and Wignell (1994: 38) state that “Mood in English is realized by the position in the clause of the subject and finite”. Mood is divided into two types; there are indicative Mood and
Imperative Mood. Indicative Mood can also be subdivided into two types; there are indicative Mood and Imperative Mood. Indicative Mood can also be subdivided into two kinds, there are Declarative
Mood and Interrogative Mood is also two kinds, that are polar (yes/no question) and Wh-questions.
Types of Mood are realized in the diagram:
Declarative Indicative
Polar
Interrogative Mood
Wh-questions
Imperative
Figure 2.1 Mood Types
Source: (Gerot and Wignell, 1994:38)
It can also be showed in this table below that is Mood types and Speech Functions realizations.
Table 2.4 Mood types and their Speech Functions (culled from Eggins, 2004)
No Mood Types Speech Functions
1 Declarative Mood Giving information by stating what is or happens
2 Interrogative Mood Request of information
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3 Modulated Interrogative Indirect/ tempered request of information
Mood
4 Imperative Mood Getting someone to do something
5 Modulated Imperative Getting indirectly/ in a tempered way somebody to do something
Mood by using, say polite modals
6 Exclamative Mood Expressing wonder, surprise, bewilderment
2.4.3.2.1 Indicative Mood
Indicative Mood is realized by (↘) the features Subject + Finite. There are two kinds of
Indicatives, they are Declarative and Interrogative. Declarative clause expresses the statement which is cover Past, Present and Future Tense and usually showed by the structure which is Subject precede
Finite.
2.4.3.2.1.1 Declarative
Declarative Mood can be identified as clauses in which the structural element of subject occurs before the finite element of the clause. a. Full Declarative
Declarative clauses can be identified as clauses in which the structural element of Subject occurs
before the finite element of the clause. The Subject has been underlined, and the Finite element is
shows in Italics.
For example:
You need a wall b. Elliptical Declarative
Elliptical Declarative clauses is an information significant component of the structure depending
on the context for elliptical Declarative, it means when the second speaker responds to a first
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speaker by cooperatively adding some information the first speaker clause. Moreover, the
production of elliptical Declaratives happens when some way in the process, ellipsing some
elements.
Example:
“Except you”.
c. Tagged Declarative
This clause type falls midway between the Declarative a polar Interrogative. Structurally it has the
sequence of a Declarative, with the subject occurring before the finite element. However, unlike
the simple Declarative, the tagged Declarative has what is called a “Mood tag” added it.
The following is example of tagged Declarative; (subject underlined; finite in italic; Mood tag
in bold).
Example:
I’ve sent you the information that you need, haven’t I?
2.4.3.2.1.2 Interrogative
Interrogative Mood is different from Declarative, the one that make it different are from the structure of the subject and the finite. The Declarative clause are realized by the subject precedes the finite structure, while Interrogative clause are realized by finite precedes subject structure. a. Polar Interrogative
The structure of polar Interrogative is the finite precedes the subject. Polar Interrogative clause
also known as yes/ no question. Example:
Would I Steer Him that way
Finite Subject Predicator Complement Circ. Adjunct
Mood Residue
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b. WH- Interrogative
WH-Interrogative is different from polar Interrogative clauses by having a WH-element, for example: who, what, where, which, why, etc. The WH-element stands for the missing piece of information that the speaker wants the listener to supply.
Example:
What Is your opinion
Subject/Wh. Finite Complement
Mood Residue
2.4.3.2.1.3 Imperative
Imperative Mood typically do not contain element of subject or finite, but Imperative clauses
consists of a predicator, any of the noncore participant of complement and adjuncts.
Example: Don’t throw that! (Subject + Finite)
Let’s put it there! (Subject)
The Imperative Mood expresses direct commands, requests, and prohibition. An Imperative is
used to tell someone to do something without argument.
2.4.3.2.1.4 Exclamatives
Exclamatives structures, which are used in interaction to express emotions such as surprise
disgusts, worry, etc, are blend of Interrogative and Declarative patterns. Wh + S + F + P + where
C/Wh or A/Wh
Example:
What wonderful eyes Have
Complement/Wh. Subject Finite
Residue Mood
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2.5 Speech Function
Halliday states that there are two types of specific role, they are giving and demanding. The commodity exchange can be either goods or services and information can be described as follows:
1. The basic types of speech role
a. Giving
The speaker is giving something to the listener for example a piece for information. Giving
means “inviting to receive”.
b. Demanding
The speaker is demanding something from listener. Demanding means “inviting to give”
2. Commodity exchange
a. Good and service
The speaker says to hearer with the aim of getting to do something or give some object.
b. Information
The speaker says to hearer with the aim of getting to tell something.
The combination of the speech role and the commodity exchanged creates what we called four
Speech Functions to initiate an interaction:
Table 2.5 Giving or Demanding, Goods & Services or Information
Role in Exchange Commodity Exchanged
(a) Good & Services (b) Information
(i) giving ‘Offer’ ‘Statement’
Would you like this He’s giving her the
(ii) Demanding teapot? teapot.
‘Command’ ‘Question’
Give me that teapot! What is he giving her?
Source: Halliday (2004:107)
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These two variables, when taken together, define the four primary Speech Functions of offer, command, statement and question. These, in turn, are matched by a set of desired responses: accepting an offer, carrying out a command, acknowledging a statement and answering a question.
Table 2.6 Speech Functions and Responses
Response Initiation Expected Discretionary
Give Goods & Services Offer Acceptance Rejection
Shall I give you this teapot Yes, please, do! No, thanks
Demand Command Undertaking Refusal
Give me that teapot! Here you are I won’t
Give Information Statement Acknowledgement Contradiction
He’s giving her the teapot Is he? No, he isn’t
Demand Question Answer Disclaimer
What is he giving her? A teapot I don’t know
Halliday (2004: 108); (Eggins, 1994:152)
According to Gerot and Wignell (1994:22), there are options of Speech Functions:
1. Offer
The speaker gives the hearer some goods or services and the speaker inherently invites the hearer to receive those goods and services.
Example: ‘Would I steer him that way?’
2. Command
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The speaker demands the hearer some goods and services and the hearer thereby invited to give
that service or provide the goods.
Example: “Remember this.”
3. Statement
The speaker gives the hearer some information and the speaker inherently is inviting the hearer
to receive the information.
Examples: “But you have to get rid of the Russia witch hunt”
4. Question
The speaker demands the hearer some information and the speaker inherently is inviting the
hearer to give that information.
Example: “Why didn't they go after Hillary Clinton for her emails?”
According to Eggins (1994:151), “there are eight responding Speech Function, they are:
1. Acceptance
The speaker gives the hearer some goods and the speaker inherently inviting the hearer to
supporting those responding.
Example: “ok”
2. Rejection
The speaker gives the hearer some goods and services and the spaker inherently inviting the
hearer to confronting those responding.
Example: “Sorry, I can’t”
3. Compliance
The speaker demands the hearer some responding goods and services the speaker inherently
inviting the hearer to supporting those responding.
Example: “Thank.”
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4. Refusal
The speaker demands the hearer some responding goods and services and the speaker
inherently inviting the hearer to confronting those responding.
Example: “No, thanks!”
5. Acknowledgment
The speaker gives hearer some information and the speaker inherently inviting the hearer to
supporting those responding.
Example: “Yeah”
6. Contradiction
The speaker gives the hearer some information and the speaker inherently inviting the hearer
to supporting those responding.
Example: “No, it’s not!”
7. Answer
The speaker gives hearer some information and the speaker inherently inviting the hearer to
supporting those responding.
Example: “Yes”
8. Disclaimer
The speaker gives the hearer some information and the speaker inherently inviting the hearer
to supporting those responding.
Example: “No, not at all”.
The pattern below is what we called the Congruent one that is involving an unmarked association between discourse function and grammatical form.
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Table 2.7 Speech Functions and Typical Mood in Clause
Speech Function Typical Mood in Clause
Statement Declarative
Question Interrogative
Command Imperative
Offer Modulated Interrogative
Answer Elliptical Declarative
Acknowledgement Minor (non-verbal)
Accept Minor (non-verbal)
Compliance Minor (non-verbal)
Eggins and Slade (1997:183)
Sometimes there are many Incongruent realizations of Speech Functions that can be found in informal dialogue. These phenomena occur when a Speech Function is not realized by the predicated
Mood type; we can see it from the table below:
Table 2.8 Congruent and Metaphorical Realization of Mood
Speech Congruent Clause Metaphorical Clause Mood Function Mood
Statement Declarative Tagged Declarative
Question Interrogative Modulated Declarative
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Command Imperative Modulated Interrogative,
Declarative
Offer Modulated Interrogative Imperative Declarative
Source: Eggins and Scade (1997:184)
2.6 Congruent and Metaphorical Coding
Metaphor comes from meta- meaning a half or not a whole like at metaphysic and -phora means
to refer. (Saragih: 2006). Based on this meaning, metaphor means to refer something toward
experience in other field in a half form. Metaphor in general is intrinsically a second order phenomenon
in language: a linguistic expression can only be labelled metaphorical by virtue of there being a
comparable non-metaphorical expression. In the other research it has been analyzed how various types
of grammatical metaphor contrast with and build upon other, non-metaphorical resources. Because of
its inherent second-order nature, a metaphor can only be recognized as such precisely because of its
contrast with non-metaphorical expressions. This can be most clearly illustrated by means of an
example of metaphor understood in its traditional sense, the legs of the table. In relation to
‘grammatical metaphor’, tableleg is regarded as a lexical metaphor, because its metaphorical nature is
based on the use, not of a grammatical construction type, but of a single word or lexeme. The use of
the word leg in this expression is recognized as metaphorical, precisely because it retains part of its
literal meaning, i.e. ‘a body part of a living being (human or animal)’, and this meaning is used in a transferred sense to refer to part of a piece of furniture.
The variation, contrast or even tension between a metaphorical or transferred meaning on the
one hand, and a non-metaphorical or literal meaning on the other, is a feature of metaphor which has
puzzled meaning on the other, is a feature of metaphor which has puzzled numerous scholars ever
since Aristotle began to study the phenomenon metaphor. In the present section, we will have a closer
look at the semantic variation in both lexical and grammatical metaphor. This will be done in a
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comprehensive way, by taking two complementary viewpoints from which semantic variation in
general can be studied. In this discussion it will be shown that the feature of semantic tension, which
is so typical of metaphor in its traditional sense, is also present in grammatical metaphor. By thus
comparing grammatical metaphor in a detailed way to the more well-known traditional (lexical)
metaphor, the reason why exactly ‘grammatical metaphor’ is ‘metaphorical’ will be further
corroborated. Areas of the study in which the notion of grammatical metaphor has proven to be useful
include the following: scientific writing and the history of scientific discourse, language development,
the teaching of academic writing. (Taverniers: 2006)
Furthermore, metaphor consists of two views about a problem. In this research, there are two
lexis called lexical metaphor and grammatical metaphor.
Lexical Metaphor, as a feature of discourse, ranges across a number of fields. And this
generates multiple theories about lexical metaphors and its use. There is an agreed appreciation of the
concept of lexical metaphor as dealing with “the phenomenon whereby we talk about something in
terms of something else” (Semino: 2008). Three primary functions of lexical metaphors have been
identified: “linguistic (naming), conceptual (framing), and communicative (perspective changing)”
(Bougher: 2012). These functions have been the focuses in different fields. Its communicative
functions in developing persuasive arguments and creating intimacy have been discussed across these
fields, in particular cognitive linguistics and SFL.
Grammatical metaphor (GM hereafter), which was suggested by Halliday (1985) is one of the most important characteristics of academic, bureaucratic and scientific discourses and it is one of the crucial contributions of Systemic Functional Linguistics (SFL hereafter) to the field of linguistics and education. However, GM theory has evolved since its suggestion and there are two models that theorize
GM. Depending on which theory researchers draw on, the instances of GM differ dramatically.
Therefore, this paper firstly aims to explore GM from a theoretical perspective and then it will move on to the application of the theory in language development and language education studies.
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Due to the stratal tension between semantic categories and their realization in lexicogrammar,
GM needs to be read metaphorically and congruently.
The two main GM categories within the stratal model are interpersonal and ideational
metaphors (Halliday: 1985). Interpersonal metaphor consists of metaphors of mood and metaphors of
modality. Ideational metaphor is categorized into two types, namely, experiential and logical
metaphors (Martin: 1992). Each GM type will be explicated below with examples.
Interpersonal metaphor is categorized into metaphors of mood and modality, creating a stratal
tension between discourse semantics and lexicogrammar. Mood metaphorsconstrue a discourse semantic speech function through an incongruent mood option in grammar. To illustrate, the speech function command might be realized as a command, e.g. get up, using imperative mood.
Alternatively, command might also be realized as a suggestion as in “why don’t you get up?”, using
interrogative mood. Mood metaphors are found more commonly in spoken language. However, the
second type of interpersonal metaphor, metaphors of modality, is more likely to be found in written
language.
It is normally that Congruent coding in interpersonal function shows that statement realized
with Declarative, question realized with Interrogative and Imperative realized with command.
Interpersonal metaphor sometimes has Incongruent coding involving types of clause involving Mood
and modality.
Here are some examples realizations of statement in Declarative, Question in Interrogative and
Imperative in Command:
A: Where is my book?
B: It is on the table. (Declarative)
Find it on the table at the corner room! (Imperative)
Have you looked for it on the table? (Interrogative)
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Based on the dialogue above, we can see A asking a question. There are many ways to answer
the question the first answer is by Declarative clause It is on the table. It showed Congruent Coding, because it has same lexical between Mood and Speech Function.
On the other hand, in Interpersonal Function, the Metaphorical coding realizes other side such as a statement expressed in the Interrogative Mood, a statement expressed in the Imperative Mood, a
Command expressed in the Interrogative Mood, a Command expressed in the Declarative Mood, a question expressed in the Declarative Mood, a question expressed in the Imperative Mood. Here are some examples of transference of Mood from Congruent coding Metaphorical coding in terms of interpersonal metaphor of Mood in table 2. This following are Congruent and Metaphorical Realization of Speech Function.
Table 2.9 Congruent and Metaphorical Realization of Speech Function
Speech Congruent Clause Metaphorical Clause Mood Function Mood
Statement Declarative Tagged Declarative
Question Interrogative Modulated Declarative
Command Imperative Modulated Interrogative,
Declarative
Offer Modulated Interrogative Imperative Declarative
Source: Eggins and Scade (1997:184)
Table 2.10 Congruent and Metaphorical Coding in Trump’s Utterances
No Donald Trump’s Clauses Mood Speech Function Coding
1 On a political basis, what she's doing is- Declarative Question Metaphorical
2 let me just say it wasn't so much a report. Declarative Command Metaphorical
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3 You're going to have pockets Declarative Statement Congruent
4 But you're not going to keep armies there Declarative Statement Congruent
5 And you know what we'll do? Declarative Question Metaphorical
From the table above, we can see some of the clauses in the realizations are Congruent and
other clauses are Incongruent or Metaphorical. Donald Trump as the interviewees sometimes used
Metaphorical coding in conveying her intends such as Declarative Mood but realized in question of
Speech Function.
Based on the explanation above; the researcher analyzed the Congruent and Metaphorical
coding in realization of Speech Function related with Mood in the program that is Face the Nation in
Trump’s dialogue.
This research analyzed both the kinds of Grammatical Metaphor semantic categories and the realization in lexicogrammar. In this research, Grammatical Metaphor were analyzed metaphorically and congruently.
2.7 Donald John Trump
Donald John Trump is the 45th and current President of the United States; he took office on
January 20, 2017. Previously, he was a real estate mogul and a former reality TV star. Born in Queens,
New York, in 1946, Trump became involved in large, profitable building projects in Manhattan. In
1980, he opened the Grand Hyatt New York, which made him the city's best-known developer.
In 2004, Trump began starring in the hit NBC reality series The Apprentice. Trump turned his attention to politics, and in 2015 he announced his candidacy for president of the United States on the
Republican ticket. After winning a majority of the primaries and caucuses, Trump became the official
Republican candidate for president on July 19, 2016. That November, Trump was elected the 45th
President of the United States, after defeating Democratic candidate Hillary Clinton.
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(https://www.biography.com/.amp/usp-president/donald-
rump#referrer=https%3A%2F%2Fwww.google.com&-tf=Dari%20%251%24s)
2.8 Face the Nation Talk Program
Face the Nation is a weekly American news and morning public affairs program airing Sundays
on the CBS radio and television network. Created by Frank Stanton in 1954, Face the Nation is one of
the longest-running news programs in the history of television.
Typically, the program features interviews with prominent American officials, politicians and
authors, followed by analysis from a panel of journalists. Margaret Brennan is the current moderator
of Face the Nation, though former host John Dickerson has substituted during Brennan's maternity
leave. The show's full hour broadcasts live from the CBS News Washington, D.C., bureau at 10:30
a.m. Eastern Time, though some stations delay or abbreviate episodes to accommodate local and sports
programming.
In 2017, Face the Nation's audience was the largest of all Sunday public affairs programs, with an average of 3.538 million viewers. NBC competitor Meet the Press has closely competed for the title in 2018, besting Face the Nation's audience for several months.
The current Face the Nation title card, which began use in 2018. The title card appears during
the show's first minute, in the "tease" segment. Similar to its Sunday morning competitors, Face the
Nation begins each episode with a short "tease" segment recapping the week's events and teasing the day's guests, set to the show's theme music.
The remainder of the program's first half-hour typically features interviews of prominent
politicians, often lawmakers and cabinet or White House officials, responding to issues from the week's
news. The program's second-half hour transitions to more discussion-oriented segments, including
interviews of notable authors with forthcoming books and a weekly roundtable discussion, with a
rotating cast of panelists.
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Unlike some of their competitors, Face the Nation and NBC's Meet the Press generally book
only journalists and columnists for their panel discussions, omitting current and former politicians
from providing punditry.
During major news events or breaking news, the program will often feature reports from
various CBS News correspondents before the day's interviews, to allow guests the opportunity to
respond to the latest news. (https://en.m.wikipedia.org/wiki/Face_the_Nation)
2.9 Relavant Studies
There are similar previous researches that related to researchers’ research topic. Therefore, the research uses these researches as the developing of ideas. Three similar previous researches below are:
Some of the research has analyzed Mood and Speech Functions. The first is an International Journal of English Lingustics by Leonard A. Koussouhon & Ashani M. Dossoumou. This journal entitles
Analyzing Interpersonal Metafunction through Mood and Modality in Kaine Agary’s Yellow-Yellow
from Critical Discourse and Womanist Perspective. The findings data revealed by the interpersonal
meaning analysis are discusses against the blackdrop of critical discourse analysis and womanist
theory. The discussion contended that, despite the blend of monologic and dialogic organization of the
novel, Kaine Agary has tried to portray the sociological schisms making up the daily life of young
girls in the oil-resourced region of Nigeria. More importantly, the authoress has shown women’s determination and character goes against this developmental stream flow by impregnating her. The
Mood and modality choices operated show some kind of power and hierarchy relations and conflicting ideologies between Sisi, Lolo, Zilafeya and Admiral. The discursive interpretation eventually found that the interpersonal meaning hidden authorial ideology behind Kaine Agary’s fictional text is geared towards a pro-women social change for a more balanced African society. This is, of course, the gist priorities and great tropical issues calling for urgent response at this time. This journal shows that by using Mood and Modality in a sentence it can empower to deliver the idea and the meaning to the listener.
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The second research is a thesis of Post-Graduated student of State University of Medan,
Indari (2011) that is Realization of Speech Function in Mood of the Susilo Bambang Yudhoyono
(SBY) Speeches. She found that from two kinds of SBY’s speeches namely Bombings and SMS
bermasalah that Speech Function in both of the speeches is realized into the form of Mood: Declarative.
The most Mood using in the speech is Declarative. The form of Declarative sentence is subject and
verb. The function of a Declarative sentence is usually to make a statement the realization of Speech
Function. A Declarative sentence sometimes can ask a question, give a command or even express
emotion. This finding created an idea for this research to analyze how Congruent and Metaphorical
coding in realization of Mood and Speech Function
The third research is a journal by Suhadi (2015) that is Interpersonal Metaphor of Mood
Realized to Some Verses of the Holy Al-Qur’an. He found that some verses of the Holy Al-Qur’an use the transference of Mood in conveying messages: some indicative Moods are expressed in the
Interrogative and Imperative, some Imperative Moods in the indicative and Interrogative, and some
Interrogative Moods in the indicative and Imperative. The writer maintained that Halliday’s theory of
Interpersonal Metaphor can be justified as an adequate linguistic theory. This research had the same significance but it differs from the objective. Suhadi’s research (2015) used Holy Al-Qur’an as the data while this research uses Trump’s dialogue in Face the Nation Talk Program.
This research is hoped to complete the research and the journal before. This analyzed not only
Mood and Speech Function but also Congruent and Incongruent or Metaphorical Coding conversations
in a talk program that is Face the Nation between the presenter and the controversial person, Donald
Trump.
2.10 Conceptual Framework
The research was undertaken by analyzing Congruent and Metaphorical coding in Mood and
Speech Function realization of Trump’s utterances in Face the Nation talk program. This research was
aimed to find out how Mood and Speech Function realized in Trump’s utterances, and then analyzing
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Congruent and Metaphorical Coding in Mood and Speech Function realization. The clause realized in
the same way both Mood and Speech Function is called by Congruent. Meanwhile, the clause realized
in the different way both Mood and Speech Function was called Metaphorical. So, this research aimed
to analyze the using of Mood types and Speech Function, and to analyze Congruent and Metaphorical
Coding in the realization both of them.
Declarative Interrogative Mood Types
Imperative
Modulated Interrogative Trump’s
Utterances Congruent
Statement
Speech Function Question
Command
Offer
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CHAPTER III
RESEARCH METHODOLOGY
3.1 Research Design
Research method is needed in a research, because the findings of a research can be said valid
or not depend on the way of choosing and using the method which is relevant. The research method in
this study covers research design, unit of analysis, source of data, method of data collection and method
of data analysis.
The researcher used descriptive research method, in which the data were described
systematically to get an accurate and factual result. The data analysis in the research used qualitative
analysis, qualitative research is a procedure of research which produces descriptive data in the form of
written words or oral words about the object that is observed. By using the qualitative research method,
this research was intended to find and to describe Congruent and Metaphorical Coding of Mood and
Speech Function Realization in Trump’s utterances.
3.2 The Data and Data Source
The data source used in this research was a video and script of the speakers between Margaret
Brennan as the presenter or the interviewer and Donald Trump as the guest or the interviewee in Face the Nation talk program. The data of the research were Trump’s utterances, furthermore they were the
responses in the presenter’s dialogue. The data were chosen because Face the Nation is one of the
largest of all Sunday public affairs programs, with an average of 3.538 million viewers. The data which
contained both video and script take place in a studio on Sunday, February 3rd 2019 and the duration
is 28 minutes 37 second. This video was downloaded in https://www.cbsnews.com/news/transcript-
president-trump-on-face-the-nation-february-3-2019/
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3.3 Techniques of Data Collection
Data collection is a systematic procedure and standardization to obtain the necessary data
(Nazir:2011). There are four types of data collection techniques (Vanderstoep and Jonston: 2008).
They are interviewing (face-to-face-question-and answer process), ethnography observation
(observing people enacting culture), analysis of documents and material culture (written text or cultural
artifacts), and visual analysis (e.g., interpretation of mediated communication text such as films or
television programs). This research employed visual analysis technique in which the utterances of the
participants a video of a recorder talk program, Face the Nation, were interpreted and analyzed. The
technique was done by these following steps:
1. Watching the video of Face the Nation on Sunday, February 3rd, 2019.
2. Downloading the script of the Face the Nation on Sunday, February 3rd 2019.
3. Examining the transcript of the dialogue, making data sheets for Trump’s utterances, and
categorizing the raw data into the data sheets.
4. Identifying the grammatical Mood and Speech Function realization in the script.
5. Identifying Congruent and Metaphorical coding of the script based on grammatical Mood and
Speech Function.
6. Classifying grammatical Mood and Speech Function of clauses used by Trump in the script.
7. Classifying Congruent and Metaphorical coding of the script based on grammatical Mood and
Speech Function in the sript.
8. Analyzing the use of Congruent and Metaphorical coding used by Trump in the script.
3.4 Techniques of Data Analysis
Data analysis techniques used in this study were Interactive Model Techniques by Miles &
Huberman. According to Miles & Huberman (Miles:1994) in this model there are three components
of analysis, namely data reduction, data display and conclusion drawing (verification). Data analysis
were analyzed by the following steps:
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1. Classifying
The researcher only provided one data sheet for Trump’s dialogue which were divided into three major categories Mood, Speech Function and Coding. They were categorized based on their types such as Mood (Declarative, Interrogative, Imperative, Modulated Interrogative), Speech Function
(Statement, Question, Command, and Offer). After analyzing Mood and Speech Function, it were categorized based on Coding (Congruent and Metaphorical Coding).
2. Analyzing
After classifying all data, the researcher analyzed them. In this step, it was employed a quantitative approach. It was counted all data which were classified in each category. This process helped the researcher to make the analysis more comprehensive by knowing which category ranks the high score vice versa. Finally the result was put in the findings.
3. Discussing
After the findings were revealed, the researcher gave detail explanation of the analysis. The detail explanation covered the answer of how and why the findings could be so. Furthermore, the discussion was conducted to the whole findings.
4. Reporting
The last step was reporting the findings and discussion of the findings. In writing the report of the research, the researcher added some points of conclusion and suggestion.
3.5 Trustworthiness of The Study
Trustworthiness of a research is an important consideration for a qualitative research. It can be used to persuade the readers that the finding of a research are worth paying and worth taking. It proposed four criteria that should be considered by qualitative researchers in ensuring the trustworthiness of a qualitative research. Each of the criteria, credibility, transferability and confirmability is described as follows: a. Credibility
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Credibility means trustee or credible. It means that both the process and the result of a research can be trusted by all researchers stakeholder. Credibility of research is in line with two important aspects; the finding is not bias and it is not subjective. Therefore, the researcher used triangulation method to verify the data and the finding was analyzed by using negative case analysis. Triangulation is perceived as a strategy for improving the research trustworthiness or finding evaluation.
Triangulation is regarded to support findings in a research by showing that independent measures are suitable with it, or at least do not contradict it (Miles and Huberman: 1984).
Denzin classifies four basic types of triangulation, namely (1) time, space, and person- involving data triangulation, (2) multiple researchers-involving triangulation in one investigation, (3) theory triangulation involves more than one theoretical scheme application in the phenomena interpretation, and (4) methodological triangulation applies more than one method in gathering, such as interview, observation, questionnaire, and documents (Denzin: 1994). The triangulation technique realized in this research is theory triangulation involves more than one theoretical scheme application in the phenomena interpretation. b. Transferability
In assuring the transferability of this research, researcher provided a sufficiently thick description when analyzing the document, in this case, the researcher analyzed Congruent and
Metaphorical coding of Mood and Speech Function. This step described the most detailed information needed to ensure transferability. The conclusion drawn in this research was assessed by other researchers so that the result can be transferred to another. By doing transferability, it is hoped that the findings can be realized in other contexts or with other respondents. As a qualitative research cannot be transferable unless it is credible, and it cannot be credible unless it is dependable, the researcher realized quantitative approach to raise the transferability. c. Confirmability
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Confirmability is the degree to which the findings are the product of the focus of the inquiry and not of the biases of the researcher. In assuring confirmability, all data such as Congruent and
Metaphorical Coding of Mood and Speech Function and transcription of the document were kept securely. In assuring the credibility of this study, member-checking was conducted continuously through the data collection. This step can be used to recheck all the data collected. It is important to make sure all grammatical metaphor are correctly analyzed before presenting them.
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CHAPTER IV
FINDINGS AND DISCUSSIONS
This chapter presented the descriptions and data analysis for the findings, interpretations, and
discussion of the research. The findings of the research summarized the result of the analysis and were
described under the sub-chapter of research findings. This sub-chapter was aided by tables for
comprehensive presentation. The discussions and interpretations which explained and reflected the
efforts to achieve the proposed research objective.
4.1 Findings
The findings dealt with the first research question. It required an analysis on the kinds of Mood
and Speech Function used in Face the Nation Talk Program. The data from which the Mood had been analyzed were categorized into Declarative Mood, Interrogative Mood, Modulated Interrogative Mood,
Imperative Mood, Modulated Imperative Mood and Exclamative Mood. Furthermore, the data of
Speech Function analyzed based on the categorization were Statement, Question, Command, and Offer.
The findings showed that in Trump’s utterances were found Mood Types such as Declarative Mood,
Interrogative Mood, Imperative Mood and Modulated Interrogative Mood. It also were found Speech
Function types such as Statement, Question, Command and Offer. Both of Mood and Speech Function realization were in Congruent coding and Metaphorical Coding.
4.2 Mood Types in Trump’s Utterances
This part discussed about the Mood in Trump’s utterances based on Mood types categorization
such as Declarative Mood, Interrogative Mood, Modulated Interrogative Mood, Imperative Mood,
Modulated Imperative Mood and Exclamative Mood. Having been analyzed, Trump’s utterances
consisted of Declarative Mood, Interrogative Mood, Imperative Mood and Modulated Interrogative
Mood.
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4.2.1 Declarative Mood
Declarative can be identified from the position the Subject that precedes finite. A Declarative
Mood function to give information and this is called Statement (in Speech Function Realization). Trump used Declarative Mood in delivering or answering the question from the interviewer. It was congruent, because a question from the interviewer must be answered in a Declarative Mood. Declarative Mood were the most dominant used in Trump’s utterances. There were 591 Declarative Mood (97.36%) in
Trump’s utterances. Trump was an interviewee in this talk program, because he answered all the question from the interviewer. Here were the representatives examples of Declarative Mood and the rests were on Appendix 3.
There have been plenty national emergencies called
Subject Finite Complement
Mood Residue
And We are going to have a strong border
Adjunct Subject Finite Predicator Complement
Residue Mood Residue
And You (do) Know
Adjunct Subject Finite Predicator
Residue Mood Residue
She (did) want to win a political point
Subject Finite Predicator Adjunct Complement
Mood Residue
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Somebody (did) say
Subject Finite Predicator
Mood Residue
She doesn’t mind human trafficking
Subject Finite Predicator Complement
Mood Residue
All the examples above were called Declarative Mood because the Subject preceded the Finite.
Subject and Finite as Mood and the rests were called by Residue. Based on the characterization of
Declarative Mood, all examples were Declarative Mood.
This following examples also showed Declarative Mood:
On a political basis What she is doing
Adjunct W-h question Subject Finite Predicator
Residue Mood Residue
And you (do) know what we will do
Adjunct Subject Finite Predicator Complement
Mood Residue
You were Precipitously bringing to precipitously?
Subject Finite Adjunct Predicator Adjunct
Mood Residue
And we will see what happens with Taliban
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Adjunct Subject Finite Predicator Complement
Residue Mood Residue
I (do) mean Who knows
Subject Finite Predicator Complement
Mood Residue
But you (do) Know
A S F P
R M R
4.2.2. Interrogative Mood
Interrogative sentence is a sentence that asks about a question. The term is used in grammar to refer to features that form questions. Thus, an Interrogative sentence is a sentence whose grammatical form shows that it is a question. Such sentences may exhibit an Interrogative grammatical Mood. This applies particularly to languages that use different inflected verb forms to make questions.
Interrogative sentences can serve as yes–no questions or as wh-questions, the latter being formed using an Interrogative word such as who, which, where or how to specify the information required.
There are 10 (1.64 %) Interrogative Mood in Trump’s utterances. The examples of Interrogative Mood found in Trump’s utterances as follows:
Because what is Happening
Circ. Adjunct Wh-Question Finite Predicator
Residue Mood Residue
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What is going on Because of the shutdown
Wh- Finite Predicator Complement
question
Mood Residue
What has happened to my son
Wh-question Finite Predicator Adjunct
Residue Mood Residue
What has happened in some cases to my
daughter
Wh-question Finite Predicator Adjunct Adjunct
Residue Mood Residue
Why didn’t they Go After
Hillary
Clinton
for her
emails
Wh-question Finite Subject Predicator Adjunct
Residue Mood Residue
From the examples, Interrogative in Mood realized Question in Speech Function. It was
concluded that Interrogative clause was started by W-h Question such as What and Why. There was no other Interrogative found such as yes/no question.
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3.2.3 Imperative Mood
Imperative Mood typically do not contain the element of subject or finite, but they consist of a predicator, plus any of the non-core participant of complement and adjuncts. Imperative Mood are the Mood typically used for exchanging goods and services. The Mood element of Imperative Mood may consist of Subject + Finite, Subject Only, or the Imperative clauses may not have Mood element, but there will always be a Predicator. There are 5 (0.82 %) Imperative clauses found in the Trump’s dialogue. Here are the examples:
See Appendix 3 No 58
Let me just Say
Predicator Subject Adjunct Predicator
Residue Mood Residue
a great
American
Look we have company
known as the
NFL
Predicator Subject Finite Complement
Residue Mood Residue
Look whether we Should There
have been
Predicator Adjunct Subject Finite Adjunct
Residue Mood Residue
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Look we are Protecting the world
Predicator Subject Finite Predicator Complement
Mood Residue
Let’s see what Happens
Predicator Predicator w-h question Complement
Residue Residue
Predicator preceded Subject and Finite called Mood was an Imperative. All the examples above were imperative if analyzed in Mood. Imperative in Mood was realized in Command in Speech Function.
But, if we see the examples, all the Imperative clauses used in Trump’s dialogue are not congruent. The
Imperative clauses used were Statement in Speech function analysis. It showed Metaphorical Coding.
3.2.4 Modulated Interrogative Mood
Modulated Interrogative Mood is an offering. This Mood is the least clause used in Trump’s utterances. There are only 1 clause (0.16 %). Modulated Interrogative Mood is Congruent with Offer in Speech Function. While it is Metaphorical when realized with Statement and Command. A
Modulated Interrogative Mood found in Trump’s utterances is below:
Would I steer Him that way
Finite Subject Predicator Complement Complement
Mood Residue
The findings of the categorization were then, quantified, and the overall findings were summarized in the table below.
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Table 4.1 Mood Types in Trump’s Utterances
Mood
Modulated Total Declarative Interrogative Imperative Interrogative
Freq % Freq % Freq % Freq % Freq %
591 97,36 10 1.64 5 0.82 1 0.16 607 100
From the table 4.1, it can be seen that all Mood types were found in the Trump’s utterances, there are
Declarative Mood, Interrogative Mood, Imperative Mood and Modulated Interrogative Mood. In the
table 4.1, there are 591 (97.36 %) Declarative Mood in the text. It meant that Declarative Mood were
more than others. Interrogative Mood were 10 (1.64 %) clauses, Imperative Mood were 5 (0.82 %)
clauses and the least clause was Modulated Interrogative, a clause (0.16 %).
4.3 Speech Function in Trump’s Utterances
People use language to interact; there is a relationship between the person who is speaking now and the person who will probably speak next. Speech Function are the combination of both speech role
(either giving or demanding) and commodity exchanged (either information or good and services)
Examples:
Speech Function No Trump’s Utterances Mood Realization Realization
1 There have been plenty Declarative Statement
national emergencies called
2 And we're going to have a Declarative Statement
strong border
3 And you know. Declarative Statement
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4 She wanted to win a Declarative Statement
political point
5 She doesn't mind human Declarative Statement
trafficking
6 Because what's happening is Interrogative Statement
7 What's going on because of Interrogative Statement
the shutdown
8 What has happened to my Interrogative Statement
son
9 What has happened in some Interrogative Statement
cases to my daughter?
10 Why didn't they go after Interrogative Question
Hillary Clinton for her
emails?
11 Let me just say Imperative Statement
12 Look we have a great Imperative Statement
American company known
as the NFL
13 Look whether we should Imperative Statement
have been there
14 Look we are protecting the Imperative Statement
world
15 Let’s see what happens Imperative Statement
16 Would I steer him at way? Modulated Offer
Interrogative
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From examples above it discussed about the Speech Function in Trump’s utterances based on
Speech Function Types such as Statement, Question, Command and Offer. Speech indicated meaning
or functions in delivering the ideas. This part discussed about the Mood in Trump’s utterances based on
Mood Types such as Declarative, Interrogative, Imperative, and Modulated Interrogative. This
following examples showed how Speech Function realization was conducted in each clause in Trump’s
utterances.
4.3.1 Statement
There are 582 (95.82 %) Statement in Trump’s utterances. It is the most dominant Speech
Function in this research. Statement as a Speech Function has a purpose to give information. This
Speech Function is used to express the speaker’s ideas, to sure and to receive that information. Trump
is an interviewee in this dialogue, meanwhile the presenter as the interviewer. In this dialogue, Trump
expresses his idea and information.
4.3.2 Question
There are 19 (3.13 %) Question in Trump’s utterances. Although Trump is an interviewee, he
delivered questions to the presenter. Question is used to demand an information, to ask something. In
delivering a question, it can be done by a yes/no question and Wh-question. In questioning, the speaker
needed an answer.
4.3.3 Command
As a Speech Function, Command has a purpose to demand goods and services in a utterances.
We can say that command functions to ask someone to do something or to ask something to be done.
The commodity exchanged in a command is good and services. The researcher found services as the commodity exchanged in the dialogue. In the dialogue, the researcher found 5 (0.82 %) Commands.
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4.3.4 Offer
There are an Offer in Trump’s utterances (0.16 %). Offer in Speech Function has the same way and meaning with Modulated Interrogative. It kinds of Interrogative which has meaning to offer something. It is the least Speech Function realized in Trump’s utterances.
The findings of the categorization were then, quantified, and the overall findings were summarized in the table below.
Table 4.2 Speech Function inTrump’s Utterances
Speech Function Total Statement Question Command Offer
Freq % Freq % Freq % Freq % Freq %
582 95.88 19 3.13 5 0.82 1 0.16 607 100
From the table 4.2, it can be seen that the researcher found 607 clauses in Trump’s dialogue. In initiating Speech Function, Statements 582 (95.88 %), Questions 19 (3.13%), Commands 5 (0.82 %) and Offer 1 (0.16 %). It meant that Statements was dominant than others.
4.4 Coding in Trump’s Utterances
Dealing with the second research question in this research is the Congruent and Metaphorical
Coding of Mood and Speech Function realized in Face the Nation. Mood as the grammar or rule while
Speech Function as the meaning or function in delivering the ideas. It was called Congruent Coding if
Mood and Speech Function have same meaning such as Declarative for Statement, Interrogative for
Question, Imperative for Command and Modulated Interrogative for Offer. Meanwhile, it was called
Metaphorical Coding or Incongruent Coding if Mood and Speech Function have the different way in delivering the ideas such as Declarative for Question, Command, and Offer, Interrogative for Statement,
Command and Offer, Imperative for Statement, Question and Offer and Modulated Interrogative for
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Statement, Question and Command. This following examples showed Congruent and Metaphorical
Coding in Trump’s utterances based on Mood and Speech Function realization.
Table 4.3 Congruent and Metaphorical Coding in Trump’s Utterances
Mood Speech Function Coding No Trump’s Utterances Realization Realization
1 I don't take anything Declarative Statement Congruent
off the table
2 And we're going to Declarative Statement Congruent
have a strong border
3 Because what's Declarative Question Metaphorical
happening is
4 What's going on Interrogative Statement Metaphorical
because of the
shutdown
5 What's happening Interrogative Statement Metaphorical
6 On a political basis, Interrogative Statement Metaphorical
what she's doing is-
7 What-- you're going Declarative Statement Congruent
to have people, like
the one armed man
who blew up a
restaurant.
8 Let me just say Imperative Statement Metaphorical
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9 We'll see what Declarative Question Metaphorical
happens, who
knows--
10 Look, whether we Imperative Statement Metaphorical
should have been
there in the first
place, that's first
question. Second
question--
11 Look, we're Imperative Statement Metaphorical
protecting the world
12 Somebody said you Declarative Question Metaphorical
were precipitously
bringing to-
precipitously?
13 And we’ll see what Declarative Question Metaphorical
happens with the
Taliban
14 Let's see what Imperative Statement Metaphorical
happens.
15 Guess what? Declarative Question Metaphorical
16 Ok, you ready? Declarative Question Metaphorical
17 but Margaret, why-- Declarative Question Metaphorical
18 Doesn't implicate me Declarative Statement Congruent
in any way
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19 We're going to see Declarative Statement Congruent
what happened
20 And now you look at Declarative Command Metaphorical
the poverty
21 and you look at the Declarative Command Metaphorical
anguish
22 and you look at the Declarative Command Metaphorical
crime
23 and you look at all of Declarative Command Metaphorical
the things happening
24 Well that's what-- Declarative Statement Congruent
25 And we'll see what Declarative Question Metaphorical
happens
26 And you know what Declarative Question Metaphorical
we'll do?
27 Look we have a great Imperative Statement Metaphorical
American company
known as the NFL
28 Would I steer him Modulated Offer Congruent
that way? Interrogative
29 And now you look at Declarative Statement Congruent
the poverty
30 but Robert Mueller Declarative Statement Congruent
said
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31 before we're talking Declarative Statement Congruent
about
32 I mean who knows Declarative Statement Congruent
33 But you know Declarative Statement Congruent
34 that we're going to Declarative Statement Congruent
make one
35 And if it is a deal Declarative Statement Congruent
36 We have a good Declarative Statement Congruent
chance to make a
deal
37 Are they the same Interrogative Question Congruent
now?
38 We have 40,000 Declarative Statement Congruent
troops in South
Korea
39 Well, yes but I think Declarative Statement Congruent
40 I've never even Declarative Statement Congruent
discussed removing
them
Some examples above showed Declarative Mood but not realized in Statement. This was the description the example above.
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PRESIDENT DONALD TRUMP: No, she can keep playing her games, but we will win. Because we
have a much better issue. On a political basis, what she's doing is- I actually think it's bad politics, but much more importantly it's very bad for our country. (See Appendix 2 No 52)
The bold example above, it showed Question realized in Declarative Mood, and it showed
Metaphorical coding.
PRESIDENT DONALD TRUMP: And you know what we'll do? We'll come back if we have to. We have very fast airplanes, we have very good cargo planes. We can come back very quickly, and I'm not leaving. We have a base in Iraq and the base is a fantastic edifice. I mean I was there recently, and I couldn't believe the money that was spent on these massive runways. And these- I've rarely seen anything like it. And it's there. And we'll be there. And frankly, we're hitting the caliphate from Iraq and as we slowly withdraw from Syria. Now the other thing--(See Appendix 2 No 117)
We can see this example was Declarative Mood but Trump’s showed in Question. It was called
Congruent, it would be Declarative Mood realized in Statement. In this example, it was Metaphorical coding because Declarative Mood realized in Question.
PRESIDENT DONALD TRUMP: I think so. I mean I- I was just one that felt very important,
you can't be kneeling for the national anthem. You have to respect our flag and our country. I want that
as president and I'd want that as a citizen. And I have a very good relationship. I did them a big favor
in negotiating the USMCA, which is basically the replacement to NAFTA, which is one of the worst
trade deals ever made. And I said to Canada, look we have a great American company known as the
NFL, and they were being hurt and treated unfairly, the NFL, by Canada for a long time. And I said to
Prime Minister Trudeau, who was very nice about it and really understood it, I hope you can settle the difference immediately and fast. And they did. So I did the NFL a big favor, as a great American company and they appreciated it. And Roger Goodell, this is a dispute that has gone on for years. Roger
Goodell called me and he thanked me. And I appreciated that. But they haven't been kneeling and they
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have been respecting the flag and their ratings have been terrific ever since. And a lot of good things happened.
From the example above, it showed Trump’s clause was Statement realized in Imperative Mood.
It was called Metaphorical Coding. In showing the statement, he used Imperative Mood. (See Appendix
2 No 334)
PRESIDENT DONALD TRUMP: She's- she's costing the country hundreds of billions of dollars because what's happening is when you have a porous border, and when you have drugs pouring in, and when you have people dying all over the country because of people like Nancy Pelosi who don't want to give proper border security for political reasons, she's doing a terrible disservice to our country.
And on the 15th we have now set the table beautifully because everybody knows what's going on because of the shutdown. People that didn't have any idea- they didn't have a clue as to what was happening, they now know exactly what's happening. They see human trafficking. They see drugs and gangs and criminals pouring in. Now, we catch them because we're doing a great job. But if we had proper border security we wouldn't have to work so hard and we could do an even better job, and I think Nancy Pelosi is doing a terrible disservice to the people of our country. But she can—
From the example above, it showed Trump’s clause was Statement realized in Declarative Clause. It was called Metaphorical Coding. (See Appendix 2 No 334)
PRESIDENT DONALD TRUMP: She's- she's costing the country hundreds of billions of dollars because what's happening is when you have a porous border, and when you have drugs pouring in, and when you have people dying all over the country because of people like Nancy Pelosi who don't want to give proper border security for political reasons, she's doing a terrible disservice to our country.
And on the 15th we have now set the table beautifully because everybody knows what's going on because of the shutdown. People that didn't have any idea- they didn't have a clue as to what was happening, they now know exactly what's happening. They see human trafficking. They see drugs and gangs and criminals pouring in. Now, we catch them because we're doing a great job. But if we had proper border
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security we wouldn't have to work so hard and we could do an even better job, and I think Nancy Pelosi
is doing a terrible disservice to the people of our country. But she can—
From the clause What’s happening, it showed Statement realized in Interrogative Mood and it was
Metaphorical coding.
PRESIDENT DONALD TRUMP: I think- let me just say it wasn't so much a report. It was the questions
and answers as the report was submitted and they were asked questions and answers. We've done an
incredible job with Syria. When I took over Syria it was infested with ISIS. It was all over the place.
And now you have very little ISIS and you have the caliphate almost knocked out. We will be announcing
in the not too distant future 100 percent of the caliphate which is the area- the land- the area- 100.
We're at 99 percent right now, we'll be at 100. When I took it over it was a disaster. I think we've done
a great job with that. At the same time, at a certain point, we want to bring our people back home. If
you look at Afghanistan we're going in very soon we'll be going into our 19th year spending 50 billion
dollars a year. Now if you go back and look at any of my campaign speeches or rallies, I talked about
it all the time.
From the bold example above, it showed Statement realized in Imperative Mood. It was called
Metaphorical coding.
PRESIDENT DONALD TRUMP: You're going to always have pockets of something. What-- you're
going to have people, like the one armed man who blew up a restaurant. You're going to have pockets.
But you're not going to keep armies there because you have a few people. Or you even have fairly
reasonable numbers of people. We've been there for many, many years. We were supposed to be in
Syria for four months. We've been there for years. We have been in Afghanistan for 19 years. And by
the way, I've been hitting very hard in Afghanistan and now we're negotiating with the Taliban. We'll see what happens, who knows—
From the example above, the clause was Question realized in Declarative Mood. It was called
Metaphorical coding.
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PRESIDENT DONALD TRUMP: Look, whether we should have been there in the first place, that's first question. Second question—
This clause showed Statement realized in Imperative and it was Metaphorical coding.
PRESIDENT DONALD TRUMP: We have to protect Israel. We have to protect other things that we have. But we're- yeah, they'll be coming back in a matter of time. Look, we're protecting the world.
We're spending more money than anybody's ever spent in history, by a lot. We spent, over the last five years, close to 50 billion dollars a year in Afghanistan. That's more than most countries spend for everything including education, medical, and everything else, other than a few countries.
From the example above, Look, we're protecting the world. This was Statement realized in Imperative.
It was Metaphorical coding.
PRESIDENT DONALD TRUMP: I ran against 17 Republicans. This was a big part of what I was saying, and I won very easily. I think the people out in the world- I think people in our country agree.
We've been fighting for 19 years. Somebody said you were precipitously bringing to- precipitously?
We've been there for 19 years. I want to fight. I want to win, and we want to bring our great troops back home. I've seen the people. I go to Walter Reed Hospital. I see what happens to people. I see with no legs and no arm- arms. And I've seen also what happens to them up here because they're in this situation, and they come back and they are totally different people-- where the wives and the fathers and the mothers say, "What has happened to my son? What has happened in some cases to my daughter?" It's a terrible thing. We've been there close to 19 years. And it's time. And we'll see what happens with the Taliban. They want peace. They're tired. Everybody's tired. We'd like to have- I don't like endless wars. This war. What we're doing is got to stop at some point.
The first example above showed Declarative Mood realized in Question and the second example showed Command realized in Declarative clause. Both of the clauses are Metaphorical coding.
PRESIDENT DONALD TRUMP: --in Iraq had nuclear weapons- had all sorts of weapons of mass destruction. Guess what? Those intel people didn't know what the hell they were doing, and they got us
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tied up in a war that we should have never been in. And we've spent seven trillion dollars in the Middle
East and we have lost lives—
The example above showed Question realized in Declarative Mood. It was Metaphorical coding.
PRESIDENT DONALD TRUMP: Excuse me. Ok, you ready? Ok, you ready? Of the 34 people, many
of them were bloggers from Moscow or they were people that had nothing to do with me, had nothing
to do with what they're talking about or there were people that got caught telling a fib or telling a lie. I
think it's a terrible thing that's happened to this country because this investigation is a witch hunt. It's
a terrible witch hunt and it's a disgrace--
The example bolded above showed Question realized in Declarative Mood. It was Metaphorical coding.
PRESIDENT DONALD TRUMP: I would say this. I decided at the time, "no" because so many really
horrible things have been happening in Venezuela when you look at that country. That was the wealthiest country of all in that part of the world which is a very important part of the world. And now you look at the poverty and you look at the anguish and you look at the crime and you look at all of the things happening. So, I think the process is playing out - very very big tremendous protests
The examples showed Command realized in Declarative Mood. It was Metaphorical coding.
The findings of the coding were then, quantified, and the overall findings were summarized in
the table below:
Table 4.4 Frequency of Congruent and Metaphorical Coding in Trump’s Utterances
Coding Total Trump’s Congruent Metaphorical
Utterances Freq % Freq % Freq %
577 95.05 30 4.94 607 100
From table 4.3, it can be seen that both the Congruent and Metaphorical coding initiating and responding
between Mood and Speech Function weer found in Trump’s utterances. The frequency of Congruent
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Coding produced was 577 (95.05 %) and Metaphorical (Incongruent) Coding produced is 30 (4.94 %).
The Metaphorical Coding produced was as followings:
4.4.1 Congruent Coding in Mood and Speech Function Realization
Having been analyzed, Trump delivered his clause or sentence in 2 codings, namely Congruent
and Metaphorical Coding. In Congruent Coding, Trump answered question from the presenter as the
way it was. Declarative Mood in Statement, Interrogative Mood in Question, Imperative Mood in
Command and Modulated Interrogative Mood in Offer. The most dominant coding in Trump’s dialogue
was Congruent, there are 577 Congruent Clauses. Congruent clause meant similar clause. It meant the
clause used by Trump after being analyzed based on Mood (grammatically) and Speech Function
(semantically) using Congruent Coding dominantly. There were 3 applications in the coding, they were
Declarative Mood realized in Statement (Speech Function) 572 clauses (94.23 %) , Interrogative Mood
realized in Question (Speech Function) 4 clauses (0.69 %), Modulated Interrogative Mood realized in
Offer 1 clause (0.16 %).
Trump was as the interviewee who has been responsible to answer, to share and to give his idea
and information of the presenter’s question. It is why Congruent coding was the most dominant in this
dialogue.
4.4.2 Metaphorical Coding in Mood and Speech Function Realization
In Metaphorical Coding, there was incongruent between Mood and Speech Function
realizations. In the data, Trump used Declarative Mood to express his Command, Interrogative Mood
to express his Statement and Declarative Mood to express his Offer. There were 30 Metaphorical
Coding (4.94 %) in Trump’s dialogue. Metaphorical Coding was realized in Trump’s dialogue because
there was difference Mood and Speech Function realization. Based on the data analysis, there were 5
Metaphorical coding of Mood and Speech Function realization. They were Declarative Mood realized
in Command 6 clauses (20 %), Interrogative Mood realized in Statement 4 (13.33 %), Declarative Mood
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realized in Question 13 clauses (43.33 %), Imperative Mood realized in Statement 4 clauses (13.33 %) and Declarative Mood realized in Offer 1 clause (3.33 %).
Metaphorical coding was the different way of speaker in delivering his idea in Mood and Speech
Function realization. After being analyzed, there were 5 Metaphorical coding in the dialogue. It was explained in this sub-chapter below:
4.4.2.1 Declarative Mood Realized in Command
Based on Mood and Speech Function realization, it can be seen that Declarative Mood was
Congruent with Statement, meanwhile it was Metaphorical with Question, Command and Offer. Trump in delivering his idea sometimes used this Metaphorical Coding that was Declarative clause realized in
Command. There were 6 clauses (20 %) of Metaphorical Coding. It meant to express his idea and information, he used Declarative Clause to express his asking. It was the suitable way meanwhile Trump was very controversial person by his quotation and policy in this world. It can be seen in this table below:
Table 4.5 Declarative Mood Realized in Command
Metaphorical Coding Total Trump’s Mood Speech Function Frequency % Utterances Declarative Command 6 20
4.4.2.2 Interrogative Mood Realized in Statement
The next application of Metaphorical Coding was Interrogative Mood realized in Statement.
Interrogative Mood was Congruent with Question, but it was Metaphorical with Statement, Command and Offer. Yet, there were clauses used by Trump was in this way that was Interrogative Mood realized in Statement. Trump asked a question to the presenter in expressing his idea and information. There are
4 clauses (14.33 %). It can be seen in this following table below:
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Table 4.6 Interrogative Mood Realized in Statement
Metaphorical Coding Total Trump’s Mood Speech Function Frequency % Utterances Interrogative Statement 4 13.33
4.4.2.3 Declarative Mood Realized in Question
This was the most Metaphorical Coding in Trump’s Dialogue, Declarative Mood realized in
Question. There were 13 clauses (43.33 %). Declarative Mood was Congruent with Statement, but
Metaphorical with Question. Trump expressed his idea and information by a question, not by a statement. It has been the most frequency of Metaphorical Coding in this dialogue. It can be drawn in this following table:
Table 4.7 Declarative Mood Realized in Question
Metaphorical Coding Total Trump’s Mood Speech Function Frequency % Utterances Declarative Question 13 43.33
4.4.2.4 Imperative Clause Realized in Statement
The other form of Metaphorical coding was Imperative Mood realized in Statement. There were
4 clauses (13.33 %). Imperative Mood was Congruent with Command, but it was Metaphorical with others. By this coding, it meant Trump asked the presenter in order to ask something that he had not convinced the truth. This is the frequency in the table below:
Table 4.8 Imperative Mood Realized in Statement
Metaphorical Coding Total Trump’s Mood Speech Function Frequency % Utterances Imperative Statement 4 13.33
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4.4.2.5 Declarative Mood Realized in Offer
This the least Metaphorical coding in Trump’s dialogue that was Declarative Mood realized in
Offer. In doing an offer, Trump used a Declarative Mood. Declarative Mood was Congruent with
Statement but it was Metaphorical with others included Offer. It was drawn in this following table below:
Table 4.9 Declarative Mood Realized in Offer
Metaphorical Coding Total Trump’s Mood Speech Function Frequency % Utterances Declarative Offer 1 0,33
4.5 Discussions
Language is often used as mastery media and sharing the influence. It is because language is a suitable media to enter and to force conceptual view, idea, value and doctrine of the speaker to the listener. It can be seen in Trump’s utterances.
A video analysis which was published from dig.comanswer, try to describe how Trump’s language style can influence society in the United State. This video analyzed one of an interview in television
Donald Trump.
In this research, it was found that Donald Trump was different in delivering his speech. The last president was very care full in delivering his speech but Trump was on the contrary.
Trump was a salesman, he usually sold feeling and idea and he used this strategy in his campaign and speech in social media. When the interviewer gave questions, it should answer or response with declarative or statement. In this research, Trump used his Declarative clause realized in Command,
Question and Offer. Interrogative clause realized in Statement, Imperative clause realized in Statement.
This was called by Metaphorical Coding. The most dominant was Congruent coding, Declarative clause realized in statement and it was prevalent.
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Trump often used Command in realized his Declarative clause. This made the listener to agree with his statement. For example: Look, whether we should have been there in the first place, that’s first question.
Second question—(See Appendix 3 No 97), Look we’re protecting the world (See Appendix 3 No 144).
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CHAPTER V
CONCLUSIONS AND SUGGESTIONS
5.1 Conclusions
This chapter presented the descriptions for the findings, interpretations, and discussion of the research. The findings of the research summarized the result of the analysis and were described under the sub-chapter of research findings. This sub-chapter was aided by tables and diagrams for comprehensive presentation. Meanwhile the presentation and discussion of the research were covered under the sub-chapter of discussions which reflected the efforts to achieve the proposed research objective.
1. The researcher found that there were Mood types and Speech Function types in Trump’s dialogue.
There were 607 clauses in Trump’s utterances. It can be found there were There were 4 Mood Types
from 6 Mood Types found namely Declarative Mood 591 (97,36 %), Interrogative Mood 10 (1.64
%), Imperative Mood 5 (0.82 %) and Modulated Interrogative Mood 1 (0.16 %). Furthermore, for
the Speech Function, there were Statement 582 (95.88 %), Question 19 (3.13%), Command 5 (0.82
%) and Offer 1 (0.16 %). There was different frequency or percentage both Mood Types and Speech
Function even they were same meaning or function. Declarative Mood realized in Statement,
Interrogative Mood realized in Question, Imperative Mood realized in Command and Modulated
Interrogative Mood realized in Offer were Congruent Coding.
2. By seeing the differences between Mood Types and Speech Function Realization, it meant that there
were some clause which was Incongruent or Metaphorical. It meant that Trump used some
Metaphorical Coding in conveying his idea. It showed that among 607 clauses in Trump’s
utterances, there were 577 (95.05 %) clauses were Congruent while 30 (4.94 %) were Metaphorical.
Metaphorical coding was the different way or express between Mood Types and Speech Function.
30 Metaphorical coding realization consisted of some difference in Mood and Speech Function
realization. They were 5 Metaphorical Coding, such as Declarative Mood realized in Command 6
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clauses (20 %), Interrogative Mood realized in Statement 4 (13.33 %), Declarative Mood realized
in Question 13 (43.33 %) clauses, Imperative Mood realized in Statement 4 (13.33 %) clauses and
Declarative Mood realized in Offer 1 clause (3.33%).
3. Metaphorical Coding was one of the ways in delivering your idea. The using of Metaphorical coding
was influenced by many factors. One of the factors was power. The more powerful person was, the
more he used Metaphorical Coding in expressing his statement, question, command and offer. The
findings of this research, Trump had used more many Congruent Coding than Metaphorical Coding.
And the most dominant frequency of Metaphorical Coding was Declarative Mood realized in
Question. It meant in delivering his idea or information, Trump expressed his Declarative Clause
by asking a Question not using Declarative clause. As we know that, Trump was as a controversial
and powerful person in his character and policy, especially in his speech and tweets. This research
supported and gave the data analysis for the description.
5.2 Suggestions
Based on the research findings, the researcher would like to give suggestions as follows:
1. It should analyze the occurrences, when analyzing spoken or written sentence for the readers.
2. It will be urged that those want to conduct the similar research, they should read and analyze the
whole dialogue between the speaker or the interviewee and the presenter to ease in analyzing the
data.
3. It will be very helpful for the lecturer to practice the theory of Congruent and Metaphorical Coding
in teaching and learning process.
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https://www.biography.com/.amp/usp-president/donald-
trump#referrer=https%3A%2F%2Fwww.google.com&-tf=Dari%20%251%24s
https://en.m.wikipedia.org/wiki/Face_the_Nation
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APPENDIX 1
Transcription of Interview between Donald Trump and Margaret Brennan in Face the Nation Talk Program
The following is a transcript of an interview with President Trump airing Sunday, Feb. 3, 2019, on "Face the Nation."
MARGARET BRENNAN: Would you shut down the government again?
PRESIDENT DONALD TRUMP: Well, we're going to have to see what happens on February 15th and I- I think—
MARGARET BRENNAN: You're not taking it off the table?
PRESIDENT DONALD TRUMP: Well, I don't- I don't take anything off the table. I don't like to take things off the table. It's that alternative. It's national emergency, it's other things and you know there have been plenty national emergencies called. And this really is an invasion of our country by human traffickers. These are people that are horrible people bringing in women mostly, but bringing in women and children into our country. Human trafficking. And we're going to have a strong border. And the only way you have a strong border is you need a physical barrier. You need a wall. And anybody that says you don't, they're just playing games.
MARGARET BRENNAN: You had quite the showdown with Speaker Pelosi. What did you learn about negotiating with her?
PRESIDENT DONALD TRUMP: Well, I think that she was very rigid - which I would expect - but I think she is very bad for our country. She knows that you need a barrier. She knows that we need border security. She wanted to win a political point. I happen to think it's very bad politics because basically she wants open borders. She doesn't mind human trafficking or she wouldn't do this because you know--
MARGARET BRENNAN: She offered you over a billion dollars for border security.
PRESIDENT DONALD TRUMP: Excuse me?
MARGARET BRENNAN: She offered over a billion dollars for border security. She doesn't want the wall.
PRESIDENT DONALD TRUMP: She's- she's costing the country hundreds of billions of dollars because what's happening is when you have a porous border, and when you have drugs pouring in, and when you have people dying all over the country because of people like Nancy Pelosi who don't want to give proper border security for political reasons, she's doing a terrible disservice to our country. And on the 15th we have now set the table beautifully because everybody knows what's going on because of the shutdown. People that didn't have any idea- they didn't have a clue as to what was happening, they now know exactly what's happening. They see human trafficking. They see drugs and gangs and criminals pouring in. Now, we catch them because we're doing a great job. But if we had proper border security we wouldn't have to work so hard and we could do an even better job, and I think Nancy Pelosi is doing a terrible disservice to the people of our country. But she can--
MARGARET BRENNAN: You're still going to have to deal with her now.
PRESIDENT DONALD TRUMP: No, she can keep playing her games, but we do win. Because we have a much better issue. On a political basis, what she's doing is- I actually think it's bad politics, but much more importantly it's very bad for our country.
MARGARET BRENNAN: I want to ask you about your intelligence leaders who were testifying on Capitol Hill this week. Did you read the report that they presented?
PRESIDENT DONALD TRUMP: I did.
MARGARET BRENNAN: And did you - there was some conversation you had because you went on Twitter and you called them naive and told them to go back to school.
PRESIDENT DONALD TRUMP: Well, I think--
MARGARET BRENNAN: What specifically was wrong about what they said?
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PRESIDENT DONALD TRUMP: I think- let me just say it wasn't so much a report. It was the questions and answers as the report was submitted and they were asked questions and answers. We've done an incredible job with Syria. When I took over Syria it was infested with ISIS. It was all over the place. And now you have very little ISIS and you have the caliphate almost knocked out. We will be announcing in the not too distant future 100 percent of the caliphate which is the area- the land- the area- 100. We're at 99 percent right now, we'll be at 100. When I took it over it was a disaster. I think we've done a great job with that. At the same time, at a certain point, we want to bring our people back home. If you look at Afghanistan we're going in very soon we'll be going into our 19th year spending 50 billion dollars a year. Now if you go back and look at any of my campaign speeches or rallies, I talked about it all the time.
MARGARET BRENNAN: You did. You've been talking about- and that--
PRESIDENT DONALD TRUMP: --I want to bring people home.
MARGARET BRENNAN: But that's one of the questions here. Is because you have these strongly held convictions and people ask, "Well, why don't the facts influence those opinions, if those facts change?" And- and your director of national intelligence said ISIS still has strongholds in Iraq and Syria--
PRESIDENT DONALD TRUMP: By the way--
MARGARET BRENNAN: --and will launch attacks from there.
PRESIDENT DONALD TRUMP: You're going to always have pockets of something. What-- you're going to have people, like the one armed man who blew up a restaurant. You're going to have pockets. But you're not going to keep armies there because you have a few people. Or you even have fairly reasonable numbers of people. We've been there for many, many years. We were supposed to be in Syria for four months. We've been there for years. We have been in Afghanistan for 19 years. And by the way, I've been hitting very hard in Afghanistan and now we're negotiating with the Taliban. We'll see what happens, who knows--
MARGARET BRENNAN: Can you trust the Taliban? Can you actually broker a deal?
PRESIDENT DONALD TRUMP: Look, whether we should have been there in the first place, that's first question. Second question--
MARGARET BRENNAN: That's where 9/11 was launched from.
PRESIDENT DONALD TRUMP: --we've been there for 19 years, almost, we are fighting very well. We're fighting harder than ever before. And I think that they will- I think they're tired and, I think everybody's tired. We got to get out of these endless wars and bring our folks back home. Now, that doesn't mean we're not going to be watching with intelligence. We're going to be watching, and watching closely. North Korea--
MARGARET BRENNAN: Isn't that harder when you don't have troops on the ground?
PRESIDENT DONALD TRUMP: Well, everything's harder. But, you know you pay a big price for troops on the ground. We're spending hundreds of billions of dollars on military. We're the policemen of the world and we don't- -
MARGARET BRENNAN: Because the concern in here by your intelligence chiefs, though, is that you could in that vacuum see a resurgence of ISIS.
PRESIDENT DONALD TRUMP: Sure.
MARGARET BRENNAN: See a resurgence of terror groups like Al-Qaeda--
PRESIDENT DONALD TRUMP: And you know what we'll do? We'll come back if we have to. We have very fast airplanes, we have very good cargo planes. We can come back very quickly, and I'm not leaving. We have a base in Iraq and the base is a fantastic edifice. I mean I was there recently, and I couldn't believe the money that was spent on these massive runways. And these- I've rarely seen anything like it. And it's there. And we'll be there. And frankly, we're hitting the caliphate from Iraq and as we slowly withdraw from Syria. Now the other thing--
MARGARET BRENNAN: How many troops are still in Syria? When are they coming home?
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PRESIDENT DONALD TRUMP: 2,000 troops.
MARGARET BRENNAN: When are they coming home?
PRESIDENT DONALD TRUMP: They're starting to, as we gain the remainder, the final remainder of the caliphate of the area, they'll be going to our base in Iraq, and ultimately some will be coming home. But we're going to be there and we're going to be staying--
MARGARET BRENNAN: So that's a matter of months?
PRESIDENT DONALD TRUMP: We have to protect Israel. We have to protect other things that we have. But we're- yeah, they'll be coming back in a matter of time. Look, we're protecting the world. We're spending more money than anybody's ever spent in history, by a lot. We spent, over the last five years, close to 50 billion dollars a year in Afghanistan. That's more than most countries spend for everything including education, medical, and everything else, other than a few countries.
MARGARET BRENNAN: Is there a scenario where you would keep troops in Afghanistan? A smaller number?
PRESIDENT DONALD TRUMP: Yes. And I'll leave intelligence there. Real intelligence, by the way. I'll leave intelligence there and if I see nests forming, I'll do something about it. But for us to be spending 51 billion dollars, like last year, or if you average the cost it's- I mean you're talking about numbers that nobody's ever heard of before.
MARGARET BRENNAN: The Senate Republicans voted, the vast majority of them said that they don't support what you're doing. That what you're doing risks national intelligence by a precipitous withdrawal from Syria and Afghanistan. Doesn't that concern you?
PRESIDENT DONALD TRUMP: I ran against 17 Republicans. This was a big part of what I was saying, and I won very easily. I think the people out in the world- I think people in our country agree. We've been fighting for 19 years. Somebody said you were precipitously bringing to- precipitously? We've been there for 19 years. I want to fight. I want to win, and we want to bring our great troops back home. I've seen the people. I go to Walter Reed Hospital. I see what happens to people. I see with no legs and no arm- arms. And I've seen also what happens to them up here because they're in this situation, and they come back and they are totally different people-- where the wives and the fathers and the mothers say, "What has happened to my son? What has happened in some cases to my daughter?" It's a terrible thing. We've been there close to 19 years. And it's time. And we'll see what happens with the Taliban. They want peace. They're tired. Everybody's tired. We'd like to have- I don't like endless wars. This war. What we're doing is got to stop at some point.
MARGARET BRENNAN: But you- but you also campaigned saying that, you know, President Obama made a big mistake by telegraphing his military moves. You're telegraphing your retreat.
PRESIDENT DONALD TRUMP: I'm not telegraphing anything. No, no, no. There's a difference. When President Obama pulled out of Iraq in theory we had Iraq. In other words, we had Iraq. We never had Syria because President Obama never wanted to violate the red line in the sand. So we never had Syria. I was the one that actually violated the red line when I hit Syria with 59 Tomahawk missiles, if you remember. But President Obama chose not to do that. When he chose not to do that, he showed tremendous weakness. But we didn't have Syria whereas we had Iraq. So when he did what he did in Iraq, which was a mistake. Being in Iraq was a mistake. Okay. Being in Iraq- it was a big mistake to go- one of the greatest mistakes going into the Middle East that our country has ever made. One of the greatest mistakes that we've ever made--
MARGARET BRENNAN: But you want to keep troops there now?
PRESIDENT DONALD TRUMP: --but when it was chosen-- well, we spent a fortune on building this incredible base. We might as well keep it. And one of the reasons I want to keep it is because I want to be looking a little bit at Iran because Iran is a real problem.
MARGARET BRENNAN: Whoa, that's news. You're keeping troops in Iraq because you want to be able to strike in Iran?
PRESIDENT DONALD TRUMP: No, because I want to be able to watch Iran. All I want to do is be able to watch. We have an unbelievable and expensive military base built in Iraq. It's perfectly situated for looking at all over
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different parts of the troubled Middle East rather than pulling up. And this is what a lot of people don't understand. We're going to keep watching and we're going to keep seeing and if there's trouble, if somebody is looking to do nuclear weapons or other things, we're going to know it before they do.
MARGARET BRENNAN: So you're going to trust the intelligence that you receive?
PRESIDENT DONALD TRUMP: I am going to trust the intelligence that I'm putting there, but I will say this: my intelligence people, if they said in fact that Iran is a wonderful kindergarten, I disagree with them 100 percent. It is a vicious country that kills many people. When you talk about torture and so many other things. And- maybe they'll come back. The country is getting absolutely- when I ended the horrible Iran nuclear deal- it was a horrible deal done by President Obama and John Kerry that didn't know what the hell he was doing. When I ended that deal, Margaret, all of a sudden Iran became a different country. They became- very rapidly- right now they're a country that's in big financial trouble. Let's see what happens.
MARGARET BRENNAN: I want to move on here but I should say your intel chiefs do say Iran's abiding by that nuclear deal. I know you think it's a bad deal, but--
PRESIDENT DONALD TRUMP: I disagree with them. I'm- I'm- by the way--
MARGARET BRENNAN: You disagree with that assessment?
PRESIDENT DONALD TRUMP: --I have intel people, but that doesn't mean I have to agree. President Bush had intel people that said Saddam Hussein--
MARGARET BRENNAN: Sure.
PRESIDENT DONALD TRUMP: --in Iraq had nuclear weapons- had all sorts of weapons of mass destruction. Guess what? Those intel people didn't know what the hell they were doing, and they got us tied up in a war that we should have never been in. And we've spent seven trillion dollars in the Middle East and we have lost lives--
MARGARET BRENNAN: Do you trust your national security adviser John Bolton because he worked in the Bush administration?
PRESIDENT DONALD TRUMP: I do, and I respect John and John is not one of the people that happened to be testifying or on.
MARGARET BRENNAN: Got it.
PRESIDENT DONALD TRUMP: And you know what I tell people- you can testify any way you want. I'm not going to stop them from testifying. They said they were mischaracterized-- maybe they were maybe they weren't, I don't really know-- but I can tell you this, I want them to have their own opinion and I want them to give me their opinion. But, when I look at Iran, I look at Iran as a nation that has caused tremendous problems.
MARGARET BRENNAN: Yeah.
PRESIDENT DONALD TRUMP: When I came in as president of the United States, my first year, I went to the Pentagon two weeks after I came in, a short time after, and I was given a- because I wanted to know what's going on with Iran.
MARGARET BRENNAN: Right.
PRESIDENT DONALD TRUMP: We were in many many locations in the Middle East in huge difficulty. Every single one of them was caused by the number one terrorist nation in the world which is Iran. So when my intelligence people tell me how wonderful Iran is- if you don't mind, I'm going to just go by my own counsel.
MARGARET BRENNAN: You've had a lot of change up in you administration recently too. Are you satisfied with the cabinet and the staff you have now?
PRESIDENT DONALD TRUMP: So we have a great cabinet. I have great people. I think now we have a really great cabinet. I think Bill Barr will be a fantastic attorney general, and I think that we have- Mike Pompeo's been doing a fantastic job. We have--
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MARGARET BRENNAN: He's not leaving?
PRESIDENT DONALD TRUMP: No, I don't- I mean he tells me he wouldn't want to leave. I think that was-
MARGARET BRENNAN: Because McConnell was talking to him--
PRESIDENT DONALD TRUMP: That was fake news.
MARGARET BRENNAN: --about running for the Senate. He said McConnell had spoken to him about running for the Senate.
PRESIDENT DONALD TRUMP: Well, he may have spoken to him, but I think he loves being secretary of state. He's doing a fantastic job. And I asked him the question the other day, he says he's absolutely not leaving. I don't think he'd do that. And he doesn't want to be lame duck. And he's doing a fantastic job as our secretary of state. Great energy and great- a great, smart gentleman.
MARGARET BRENNAN: Cause you have an acting AG until you get Barr confirmed--
PRESIDENT DONALD TRUMP: Yes.
MARGARET BRENNAN: An acting defense secretary. An acting chief of staff. An acting interior secretary.
PRESIDENT DONALD TRUMP. It's OK. It's easier to make moves when they're acting.
MARGARET BRENNAN: So you are going to shake up--
PRESIDENT DONALD TRUMP: Some, and some not.
MARGARET BRENNAN: --positions.
PRESIDENT DONALD TRUMP: Some are doing a fantastic job. Really- I like acting because I can move so quickly. It gives me more flexibility. But- but actually, some of the names you mentioned, they're doing a fantastic job.
MARGARET BRENNAN: How do you know when to fire someone?
PRESIDENT DONALD TRUMP: When it's not happening. When--
MARGARET BRENNAN: What do you mean?
PRESIDENT DONALD TRUMP: When it doesn't get done. Like with General Mattis, I wasn't happy with his service. I told him give me a letter.
MARGARET BRENNAN: He resigned.
PRESIDENT DONALD TRUMP: He resigned because I asked him to resign. He resigned because I was very nice to him. But I gave him big budgets and he didn't do well in Afghanistan. I was not happy with the job he was doing in Afghanistan. And if you look at Syria what's happened, I went to Iraq recently, if you look at Syria, what's happened in Syria in the last few weeks, you would see that things are going down that were not going down. That things are happening that are very good. So I was not happy with him, but I wish him well.
MARGARET BRENNAN: I want to ask you about your relationship with NFL Commissioner Roger Goodell. Have- have you put your differences aside?
PRESIDENT DONALD TRUMP: I think so. I mean I- I was just one that felt very important, you can't be kneeling for the national anthem. You have to respect our flag and our country. I want that as president and I'd want that as a citizen. And I have a very good relationship. I did them a big favor in negotiating the USMCA, which is basically the replacement to NAFTA, which is one of the worst trade deals ever made. And I said to Canada, look we have a great American company known as the NFL, and they were being hurt and treated unfairly, the NFL, by Canada for a long time. And I said to Prime Minister Trudeau, who was very nice about it and really understood it, I hope
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you can settle the difference immediately and fast. And they did. So I did the NFL a big favor, as a great American company and they appreciated it. And Roger Goodell, this is a dispute that has gone on for years. Roger Goodell called me and he thanked me. And I appreciated that. But they haven't been kneeling and they have been respecting the flag and their ratings have been terrific ever since. And a lot of good things happened.
MARGARET BRENNAN: Talking about the- the kneeling position you've taken and the controversy around it. Do you think that the players who did kneel had a point? I mean did you- are you sensitive at all to players like Colin Kaepernick, who- who point out that the majority of victims of police violence are black?
PRESIDENT DONALD TRUMP: Well, you know, I'm the one that had passed judicial reform. And if you look at what I did, criminal judicial reform, and what I've done- President Obama tried. They all tried. Everybody wanted to do it. And I got it done and I've been, you know, really- a lot of people in the NFL have been calling and thanking me for it.
MARGARET BRENNAN: Really?
PRESIDENT DONALD TRUMP: They have been calling and thanking, you know, that people have been trying to get that taken care of and it's now signed into law and affects tremendous numbers of people, and very good people. I think that when you want to protest I think that's great. But I don't think you do it at the sake of our flag, at the sake of our national anthem. Absolutely.
MARGARET BRENNAN: But you are- do I understand you saying there though, that you still are sensitive though? I mean you- you understand the motivation for the protest--
PRESIDENT DONALD TRUMP: Well I do--
MARGARET BRENNAN: Though you don't like the form of it.
PRESIDENT DONALD TRUMP: A lot of it is having to do with reform from what I understand. Whether it's criminal justice or whatever it may be and they have different versions and everybody seemed to have a different version of it. But a lot of it had to do with that, and I took care of that. I think that people have to, at all times, respect our flag and at all times respect our net- our- our national anthem and our country. And I think there are plenty of places and times you can protest and you can do a lot. But you can't do that. That's my opinion.
MARGARET BRENNAN: In a CBS poll we just took, 63 percent of Americans say they disapprove about how you're handling issues of race in the US.
PRESIDENT DONALD TRUMP: Well--
MARGARET BRENNAN: What do you think of that?
PRESIDENT DONALD TRUMP: What has happened is very interesting. The economy is so good right now. You saw the jobs report just came out. Three hundred and four thousand added jobs, which is a shocker, for the month. A shocker to a lot of people. They thought it was going to be half that number. The African-Americans have the best employment numbers in the history of our country. Hispanic Americans have the best employment numbers in the history of our country. Asian-Americans the best in the history of our country. You look at women, the best in 61 years. And our employment numbers are phenomenal, the best in over 50 years. So I think I've been given a lot of credit for that. And in terms of race, a lot of people are saying well this is something very special what's happening.
MARGARET BRENNAN: So- because when colleagues of yours, even like Republican Senator Tim Scott. He said Donald Trump is not racist. But he said you're racially insensitive.
PRESIDENT DONALD TRUMP: I have a great relationship with Tim and certainly with his state, South Carolina, and- where we do very well. And I think if you look at the numbers for African-American unemployment, best numbers they've had- literally the best numbers they've had in history. And I think they like me a lot and I like them a lot.
MARGARET BRENNAN: Would you let your son Barron play football?
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PRESIDENT DONALD TRUMP: It's very, it's very tough question. It's a very good question. If he wanted to? Yes. Would I steer him that way? No, I wouldn't.
MARGARET BRENNAN: Why?
PRESIDENT DONALD TRUMP: I wouldn't. And he actually plays a lot of soccer. He's liking soccer. And a lot of people, including me, thought soccer would probably never make it in this country, but it really is moving forward rapidly. I- I just don't like the reports that I see coming out having to do with football—I mean, it's a dangerous sport and I think it's- I- it's- really tough, I thought the equipment would get better, and it has. The helmets have gotten far better but it hasn't solved the problem. So, you know I- I hate to say it because I love to watch football. I think the NFL is a great product, but I really think that as far as my son- well I've heard NFL players saying they wouldn't let their sons play football. So. It's not totally unique, but I- I would have a hard time with it.
MARGARET BRENNAN: What surprised you about some of the questions that Robert Mueller asked you?
PRESIDENT DONALD TRUMP: Well, look the Russia thing is a hoax. I have been tougher on Russia than any president, maybe ever. But than any president.
MARGARET BRENNAN: But when it comes to the investigation that the special counsel's conducting- I mean 34 people have been charged here. Seven guilty pleas --
PRESIDENT DONALD TRUMP: Excuse me. Ok, you ready? Ok, you ready? Of the 34 people, many of them were bloggers from Moscow or they were people that had nothing to do with me, had nothing to do with what they're talking about or there were people that got caught telling a fib or telling a lie. I think it's a terrible thing that's happened to this country because this investigation is a witch hunt. It's a terrible witch hunt and it's a disgrace--
MARGARET BRENNAN: Do you think it should be made public?
PRESIDENT DONALD TRUMP: --when you look at General Flynn where the FBI said he wasn't lying, but Robert Mueller said he was, and they took a man and destroyed his life. When you look at so many of the things that have happened- why didn't they go after Hillary Clinton for her emails? She had thirty three thousand emails that were deleted after receiving a subpoena from Congress--
MARGARET BRENNAN: And according to the special counsel--
PRESIDENT DONALD TRUMP: Excuse me, but Margaret, why--
MARGARET BRENNAN: --they were posted on WikiLeaks and your friend Roger Stone was just indicted for his involvement there and for lying.
PRESIDENT DONALD TRUMP: First of all, Roger Stone didn't work on the campaign, except way way at the beginning long before we're talking about. Roger is somebody that I've always liked, but a lot of people like Roger some people probably don't like Roger, but Roger Stone's somebody I've always liked. I mean Roger's a character but Roger was not- I don't know if you know this or not- Roger wasn't on my campaign except way at the beginning- -
MARGARET BRENNAN: Right.
PRESIDENT DONALD TRUMP: So, it's all- and- and yet you will ask me a question like that, wasn't involved in my campaign.
MARGARET BRENNAN: Would you pardon him?
PRESIDENT DONALD TRUMP: I have not thought about it. It looks like he's defending himself very well. But you have to get rid of the Russia witch hunt because it is indeed. And remember--
MARGARET BRENNAN: Because you think--
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PRESIDENT DONALD TRUMP: Remember this. Remember this. There's been no president that has been tougher on Russia than Donald Trump.
MARGARET BRENNAN: Would you make the Mueller report public because you say there's nothing in there? Congress can subpoena it anyway, though.
PRESIDENT DONALD TRUMP: Totally up to to the Attorney General.
MARGARET BRENNAN: But what do you want them to do?
PRESIDENT DONALD TRUMP: Even the Mueller report said it had nothing to do with the campaign. When you look at some of the people and the events it had nothing to do--
MARGARET BRENNAN: You wouldn't have a problem--
PRESIDENT DONALD TRUMP: Excuse me.
MARGARET BRENNAN: --if it became public?
PRESIDENT DONALD TRUMP: Excuse me. That's up to the attorney general. I don't know. It depends. I have no idea what it's going to say.
MARGARET BRENNAN: Okay.
PRESIDENT DONALD TRUMP: So far this thing's been a total witch hunt. And it doesn't implicate me in any way. There was no collusion. There was no obstruction. There was no nothing. Doesn't implicate me in any way but I think it's a disgrace.
MARGARET BRENNAN: What would make you use the U.S. military in Venezuela? What's the national security interest?
PRESIDENT DONALD TRUMP: Well I don't want to say that. But certainly it's something that's on the- it's an option.
MARGARET BRENNAN: Would you personally negotiate with Nicolás Maduro to convince him to exit?
PRESIDENT DONALD TRUMP: Well he is requested a meeting and I've turned it down because we're very far along in the process. You have a young and energetic gentleman but you have other people within that same group that have been very very - if you talk about democracy - it's really democracy in action.
MARGARET BRENNAN: When did he request a meeting?
PRESIDENT DONALD TRUMP: We're going to see what happened. A number of months ago he wanted to meet.
MARGARET BRENNAN: But now because you're at that crisis point--
PRESIDENT DONALD TRUMP: Well now we'd have to see.
MARGARET BRENNAN: Would you negotiate that?
PRESIDENT DONALD TRUMP: I would say this. I decided at the time, "no" because so many really horrible things have been happening in Venezuela when you look at that country. That was the wealthiest country of all in that part of the world which is a very important part of the world. And now you look at the poverty and you look at the anguish and you look at the crime and you look at all of the things happening. So, I think the process is playing out - very very big tremendous protests.
MARGARET BRENNAN: North Korea. When and where are you going to meet Kim Jong Un?
PRESIDENT DONALD TRUMP: I won't tell you yet, but you'll be finding out probably State of the Union or shortly before. But the meeting is set. He's looking forward to it. I'm looking forward to it. We've made tremendous progress. If you remember, before I became president, it looked like we were going to war with North Korea. Now
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we have a very good relationship. The hostages are back. Okay, the remains are starting to come back. The remains of our Korean War veterans--
MARGARET BRENNAN: But your intelligence chief testified this week that Kim Jong Un is still very unlikely to give up his nuclear--
PRESIDENT DONALD TRUMP: Well that's what--
MARGARET BRENNAN: --weapons program.
PRESIDENT DONALD TRUMP: That's what the intelligence chief thinks, and I think--
MARGARET BRENNAN: Why is he wrong?
PRESIDENT DONALD TRUMP: --there's a good possibility of that too. But there's also a very good chance that we will make a deal. I think he's also tired of going through what he's going through. He has a chance to have North Korea be a tremendous economic behemoth. It has a chance to be one of the great economic countries in the world. He can't do that with nuclear weapons and he can't do that on the path they're on now. I like him. I get along with him great. We have a fantastic chemistry. We have had tremendous correspondence that some people have seen and can't even believe it. They think it's historic. And we'll see what happens. Now that doesn't mean we're going to make a deal. But certainly I think we have a very good chance of making a deal. And one of the reasons is because North Korea has a chance being located between Russia, China, and South Korea. What a location- I'm in the real estate business- what a location. They have a chance to be an economic powerhouse.
MARGARET BRENNAN: You're going to keep U.S. troops there, in South Korea?
PRESIDENT DONALD TRUMP: Yeah, I mean we haven't talked about anything else. Maybe someday. I mean who knows. But you know it's very expensive to keep troops there. You do know that. We have 40,000 troops in South Korea, it's very expensive. But I have no plans, I've never even discussed removing them.
MARGARET BRENNAN: I want to quickly get to China. The last time you spoke with FACE THE NATION you were one hundred days into office and you said you would accept a less than perfect trade deal with China, if it meant they'd be helpful with North Korea. Do you stand by that?
PRESIDENT DONALD TRUMP: Well, yes but I think we're in a different position now.
MARGARET BRENNAN: What do you mean?
PRESIDENT DONALD TRUMP: We've put very massive tariffs on China. China is paying a big price and it's hurt China's economy very badly. I want them to make a fair deal.They have been very helpful, especially at the beginning when I first came in with North Korea. They have stopped goods from going in. They have stopped a lot of things from going in through the border. Because as you know they have a border just like we have a border with Mexico, where crime is way up by the way, way up, and you have to remember that. But we have a border with- they have a border with North Korea.
MARGARET BRENNAN: Right.
PRESIDENT DONALD TRUMP: We've put very massive tariffs on China. China is paying a big price and it's hurt China's economy very badly. I want them to make a fair deal.They have been very helpful, especially at the beginning when I first came in with North Korea. They have stopped goods from going in. They have stopped a lot of things from going in through the border. Because as you know they have a border just like we have a border with Mexico, where crime is way up by the way, way up, and you have to remember that. But we have a border with- they have a border with North Korea. They have been very vigilant. Are they the same now? Probably a little bit less so. But North Korea is absolutely talking. And I think North Korea wants to make a deal. We are making a deal. It looks like we're doing very well with making a deal with China. I can tell you this, no two leaders of this country and China have ever been closer than I am with President Xi. We have a good chance to make a deal. I don't know that we're going to make one, but we have a good chance. And if it is a deal it's going to be a real deal. It's not going to be a stopgap.
MARGARET BRENNAN: Sir, I hear your helicopters. I'm being told to wrap. I appreciate you being generous with your time.
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PRESIDENT DONALD TRUMP: Thank you very much, Margaret.
MARGARET BRENNAN: Thank you.
PRESIDENT DONALD TRUMP: Thank you.
© 2019 CBS Interactive Inc. All Rights Reserved.
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APPENDIX 2 Donald Trump’s Utterances in Face the Nation Talk Program
No Donald Trump’s Utterances th 1 Well, we're going to have to see what happens on February 15 2 And I- I think-- 3 Well, I don't- 4 I don't take anything off the table 5 I don't like to take things off the table 6 It's that alternative 7 It's national emergency 8 It's other things 9 And you know. 10 There have been plenty national emergencies called 11 And this really is an invasion of our country by human traffickers. 12 These are people that are horrible people bringing in women mostly 13 But bringing in women and children into our country
14 And we're going to have a strong border 15 And the only way you have a strong border is 16 You need a physical barrier 17 You need a wall 18 And anybody that says you don't 19 They're just playing games 20 Well, I think that she was very rigid - which I would expect 21 But I think she is very bad for our country 22 She knows that you need a barrier 23 She wanted to win a political point 24 I happen to think
25 She doesn't mind human trafficking
26 Or she wouldn't do this because you know--
27 Excuse me?
28 She's- she's costing the country hundreds of billions of dollars 29 Because what's happening is 30 When you have a porous border 31 And when you have drugs pouring in, 32 And when you have people dying all over the country 33 She's doing a terrible disservice to our country 34 On the 15th we have set the table beautifully 35 Because everybody knows 36 What's going on because of the shutdown 37 that didn't have any idea- 38 They didn't have a clue as to what was happening 39 What's happening 40 They see human trafficking 41 They see drugs and gangs and criminals pouring in. 42 Now, we catch them because we're doing a great job 43 But if we had proper border security 44 We wouldn't have to work so hard 45 And we could do an even better job 46 And I think 47 Nancy Pelosi is doing a terrible disservice to the people of our country
48 But she can--
49 she can keep playing her games
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50 But we will win. 51 Because we have a much better issue 52 On a political basis, what she's doing is- 53 I actually think it's bad politics, 54 But much more importantly it's very bad for our country. 55 I did. 56 Well, I think-- 57 I think- 58 Let me just say 59 It wasn't so much a report.
60 It was the answers
61 As the report was submitted
62 And they were asked questions and answers.
63 We've done an incredible job with Syria. 64 When I took over Syria 65 It was infested with ISIS 66 It was all over the place 67 And now you have very little ISIS 68 And you have the caliphate almost knocked out 69 We will be announcing in the not too distant future 100 percent of the caliphate which is the area- the land- the area- 100. 70 We're at 99 percent right now 71 We'll be at 100 72 When I took it over 73 It was a disaster 74 I think we've done a great job with that. 75 At the same time, at a certain point, we want to bring our people back home. 76 If you look at Afghanistan 77 We're going in very soon 78 We'll be going into our 19th year spending 50 billion dollars a year. 79 Now if you go back 80 And look at any of my campaign speeches or rallies 81 I talked about it all the time. 82 --I want to bring people home.
83 By the way--
84 You're going to always have pockets of something.
85 What-- you're going to have people, like the one armed man who blew up a restaurant.
86 You're going to have pockets 87 But you're not going to keep armies there 88 Because you have a few people 89 Or you even have fairly reasonable numbers of people. 90 We've been there for many, many years. 91 We were supposed to be in Syria for four months. 92 We've been there for years 93 We have been in Afghanistan for 19 years 94 And by the way, I've been hitting very hard in Afghanistan 95 And now we're negotiating with the Taliban. 96 We'll see what happens, who knows-- 97 Look, whether we should have been there in the first place, that's first question. Second question-- 98 We've been there for 19 years, almost, 99 We are fighting very well. 100 We're fighting harder than ever before 101 And I think 102 that they will- 103 I think 104 they're tired and, 105 I think everybody's tired
106 We got to get out of these endless wars and bring our folks back home.
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107 Now, that doesn't mean. 108 We're not going to be watching with intelligence 109 We're going to be watching, and watching closely. 110 North Korea-- 111 Well, everything's harder 112 But, you know 113 You pay a big price for troops on the ground. 114 We're spending hundreds of billions of dollars on military. 115 We're the policemen of the world and we don't-- 116 Sure.
117 And you know what we'll do?
118 We'll come back
119 If we have to
120 We have very fast airplanes, 121 We have very good cargo planes. 122 We can come back very quickly, 123 And I'm not leaving 124 We have a base in Iraq 125 And the base is a fantastic edifice. 126 I mean I was there recently 127 And I couldn't believe the money that was spent on these massive runways. 128 I've rarely seen anything like it 129 And it's there 130 And we'll be there 131 And frankly, we're hitting the caliphate from Iraq and as we slowly withdraw from Syria 132 And as we slowly withdraw from Syria 133 Now the other thing-- 134 2,000 troops. 135 They're starting to 136 As we gain the remainder, the final remainder of the caliphate of the area 137 They'll be going to our base in Iraq 138 And ultimately some will be coming home 139 But we're going to be there
140 And we're going to be staying--
141 We have to protect Israel
142 We have to protect other things that we have
143 they'll be coming back in a matter of time. 144 Look, we're protecting the world 145 We're spending more money than anybody's ever spent in history, by a lot 146 We spent, over the last five years, close to 50 billion dollars a year in Afghanistan. 147 That's more than most countries spend for everything including education, medical, and everything else, other than a few countries. 148 if I see nests forming 149 And I'll leave intelligence there. Real intelligence, by the way. 150 I'll leave intelligence there 151 I'll do something about it 152 But for us to be spending 51 billion dollars, like last year, or if you average the cost 153 I mean you're talking about numbers that nobody's ever heard of before. 154 I ran against 17 Republicans. 155 This was a big part of what I was saying, and I won very easily 156 I think the people out in the world- 157 I think people in our country agree 158 We've been fighting for 19 years 159 Somebody said you were precipitously bringing to- precipitously? 160 We've been there for 19 years. 161 I want to fight. 162 I want to win
163 I've seen the people.
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164 I go to Walter Reed Hospital. 165 I see what happens to people. 166 I see with no legs and no arm- arms 167 And I've seen also what happens to them up here because they're in this situation 168 And they come back 169 And they are totally different people-- 170 Because they're in this situation 171 What has happened to my son 172 What has happened in some cases to my daughter?
173 It's a terrible thing
174 We've been there close to 19 years.
175 And we’ll see what happens with the Taliban
176 They want peace 177 They're tired 178 Everybody's tired 179 We'd like to have- 180 I don't like endless wars 181 What we're doing is got to stop at some point. 182 I'm not telegraphing anything. 183 because President Obama never wanted to violate the red line in the sand 184 There's a difference 185 When President Obama pulled out of Iraq in theory 186 In other words, we had Iraq 187 We never had Syria 188 So we never had Syria 189 I was the one that actually violated the red line 190 But President Obama chose not to do that 191 he showed tremendous weakness 192 But we didn't have Syria whereas we had Iraq 193 So when he did what he did in Iraq, which was a mistake. 194 Being in Iraq was a mistake 195 it was a big mistake to go- one of the greatest mistakes going into the Middle East that our country has ever made--
196 --but when it was chosen--.
197 well, we spent a fortune on building this incredible base
198 We might as well keep it
199 I want to keep 200 because I want to be looking a little bit at Iran 201 because Iran is a real problem 202 No, because I want to be able to watch Iran 203 I want to do is be able to watch 204 We have an unbelievable and expensive military base built in Iraq 205 It's perfectly situated for looking at all over different parts of the troubled Middle East rather than pulling up 206 And this is what a lot of people don't understand 207 We're going to keep watching 208 and we're going to keep seeing 209 and if there's trouble 210 if somebody is looking to do nuclear weapons or other things 211 we're going to know it 212 before they do 213 I am going to trust the intelligence 214 that I'm putting there 215 but I will say this: my intelligence people 216 if they said in fact 217 that Iran is a wonderful kindergarten 218 I disagree with them 100 percent
219 It is a vicious country that kills many people
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220 When you talk about torture and so many other things. 221 And- maybe they'll come back. 222 The country is getting absolutely- 223 when I ended the horrible Iran nuclear deal- 224 it was a horrible deal done by President Obama and John Kerry that didn't know 225 what the hell he was doing 226 When I ended that deal, Margaret,
227 all of a sudden Iran became a different country
228 They became- very rapidly- right now
229 They're a country that's in big financial trouble.
230 Let's see what happens. 231 I disagree with them. 232 I'm- I'm- by the way-- 233 --I have intel people, but that doesn't mean 234 I have to agree 235 President Bush had intel people that said Saddam Hussein-- 236 you want 237 Guess what? 238 Those intel people didn't know what the hell 239 they were doing 240 and they got us tied up in a war 241 that we should have never been in 242 And we've spent seven trillion dollars in the Middle East 243 and we have lost lives-- 244 I do 245 and I respect John 246 and John is not one of the people that happened to be testifying or on 247 And you know what I tell people- 248 you can testify any way 249 I'm not going to stop them from testifying.
250 They said they were mischaracterized--
251 they were mischaracterized
252 maybe they weren't
253 I don't really know-- 254 but I can tell you this 255 I want them to have their own opinion 256 and I want them to give me their opinion 257 But, when I look at Iran, 258 I look at Iran as a nation that has caused tremendous problems 259 When I came in as president of the United States, my first year, 260 I went to the Pentagon two weeks 261 after I came in, a short time after 262 and I was given a- 263 because I wanted to know what's going on with Iran 264 We were in many locations in the Middle East in huge difficulty 265 Every single one of them was caused by the number one terrorist nation in the world which is Iran 266 So when my intelligence people tell me how wonderful Iran is-, 267 if you don't mind 268 I'm going to just go by my own counsel 269 Bill Barr will be a fantastic attorney general, 270 So we have a great cabinet 271 I have great people 272 I think now
273 we have a really great cabinet
274 I think
275 and I think
276 that we have- Mike Pompeo
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277 We have-- 278 No, I don't- 279 I mean 280 he tells me 281 he wouldn't want to leave 282 I think that was-- 283 That was fake news. 284 Well, he may have spoken to him, 285 he loves being secretary of state 286 He's doing a fantastic job
287 And I asked him the question the other day,
288 he says
289 he's absolutely not leaving
290 I don't think 291 he'd do that 292 And he doesn't want to be lame duck 293 And he's doing a fantastic job as our secretary of state 294 that were not going down 295 that are very good 296 It's OK 297 It's easier to make moves 298 when they're acting 299 Some are doing a fantastic job 300 I like acting 301 because I can move so quickly 302 It gives me more flexibility 303 some of the names you mentioned, 304 They're doing a fantastic job 305 When it's not happening. 306 When it doesn't get done 307 Like with General Mattis, I wasn't happy with his service 308 I told him give me a letter. 309 He resigned because
310 I asked him to resign
311 He resigned
312 Because I was very nice to him
313 But I gave him big budgets and 314 He didn't do well in Afghanistan 315 I was not happy with the job 316 He was doing in Afghanistan 317 And if you look at Syria what's happened 318 I went to Iraq recently 319 If you look at Syria c 320 You would see 321 That things are going down 322 That things are happening 323 So I was not happy with him, 324 But I wish him well 325 I think so 326 I was just one that felt very important 327 You can't be kneeling for the national anthem 328 You have to respect our flag and our country 329 I want that as president 330 And I'd want that as a citizen 331 And I have a very good relationship 332 I did them a big favor in negotiating the USMCA,
333 And I said to Canada
334 Look we have a great American company known as the NFL
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335 And they were being hurt and treated unfairly, the NFL, by Canada for a long time 336 And I said to Prime Minister Trudeau, who was very nice about it and really understood it, 337 I hope you can settle the difference immediately and fast 338 And they did. 339 So I did the NFL a big favor, as a great American company and they appreciated it. 340 Roger Goodell And Roger Goodell, this is a dispute that has gone on for years called me 341 and he thanked me 342 And I appreciated that 343 But they haven't been kneeling 344 and they have been respecting the flag
345 and their ratings have been terrific ever since
346 And a lot of good things happened
347 Well, you know
348 I'm the one that had passed judicial reform 349 And if you look at what I did, criminal judicial reform 350 and what I've done- President Obama tried 351 They all tried 352 Everybody wanted to do it 353 And I got it done 354 and I've been 355 you know 356 really- a lot of people in the NFL have been calling and thanking me for it 357 They have been calling and thanking 358 you know, that people have been trying to get that taken care of and it's now signed into law and affects tremendous numbers of people, and very good people 359 I think that when you want to protest 360 I think that's great 361 But I don't think 362 you do it at the sake of our flag, at the sake of our national anthem 363 Absolutely. 364 Well I do-- 365 A lot of it is having to do with reform from what I understand 366 Whether it's criminal justice 367 or whatever it may be
368 and they have different versions
369 and everybody seemed to have a different version of it
370 But a lot of it had to do with that
371 and I took care of that 372 I think that people have to, at all times 373 respect our flag and at all times 374 respect our net- our- our national anthem and our country 375 And I think 376 there are plenty of places 377 and times you can protest 378 and you can do a lot 379 But you can't do that 380 That's my opinion 381 Well-- 382 What has happened is very interesting 383 The economy is so good right now 384 You saw the jobs report just came out 385 Three hundred and four thousand added jobs, which is a shocker, for the month 386 They thought 387 It was going to be half that number 388 The African-Americans have the best employment numbers in the history of our country 389 Hispanic Americans have the best employment numbers in the history of our country 390 You look at women, the best in 61 years
391 And our employment numbers are phenomenal, the best in over 50 years
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392 So I think I've been given a lot of credit for that 393 And in terms of race, a lot of people are saying well this is something very special what's happening 394 I have a great relationship with Tim and certainly with his state, South Carolina 395 And- where we do very well 396 And I think if you look at the numbers for African-American unemployment 397 Best numbers they've had- literally the best numbers they've had in history 398 And I think they like me a lot and I like them a lot 399 It's very 400 It's very tough question 401 It's a very good question
402 If he wanted to?
403 Would I steer him that way?
404 No, I wouldn't
405 I wouldn't 406 And he actually plays a lot of soccer 407 He's liking soccer 408 And a lot of people, including me, thought soccer would probably never make it in this country 409 But it really is moving forward rapidly 410 I- I just don't like the reports that I see coming out having to do with football 411 I mean, 412 It's a dangerous sport 413 And I think 414 I- it's- really tough 415 I thought 416 The equipment would get better 417 And it has 418 The helmets have gotten far better 419 But it hasn't solved the problem 420 So, you know 421 I- I hate to say it 422 because I love to watch football 423 I think 424 the NFL is a great product
425 but I really think that as far as my son- well
426 I've heard NFL players saying
427 they wouldn't let their sons play football
428 they wouldn't let their sons play football 429 but I- I would have a hard time with it 430 Well, look the Russia thing is a hoax 431 I have been tougher on Russia than any president, maybe ever 432 But than any president 433 Excuse me. 434 Ok, you ready? 435 Of the 34 people, many of them were bloggers from Moscow 436 or they were people that had nothing to do with me, had nothing to do with 437 what they're talking about 438 or there were people that got caught telling a fib or telling a lie 439 I think 440 it's a terrible thing that's happened to this country 441 because this investigation is a witch hunt 442 It's a terrible witch hunt 443 and it's a disgrace-- 444 --when you look at General Flynn 445 where the FBI said 446 he wasn't lying 447 but Robert Mueller said
448 he was
449 and they took a man and destroyed his life
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450 When you look at so many of the things that have happened- 451 Why didn't they go after Hillary Clinton for her emails? 452 She had thirty three thousand emails that were deleted after receiving a subpoena from Congress-- 453 Excuse me 454 but Margaret, why-- 455 First of all, Roger Stone didn't work on the campaign, except way way at the beginning long 456 before we're talking about 457 Roger is somebody 458 that I've always liked 459 but a lot of people like Roger
460 some people probably don't like Roger
461 but Roger Stone's somebody I've always liked
462 I mean Roger's a character
463 but Roger was not 464 I don't know 465 if you know this or not- 466 Roger wasn't on my campaign except way at the beginning-- 467 So, it's all 468 you will ask me a question like that. 469 I have not thought about it 470 It looks like 471 he's defending himself very well 472 But you have to get rid of the Russia witch hunt 473 because it is indeed 474 Remember this 475 Remember this 476 There's been no president 477 that has been tougher on Russia than Donald Trump 478 Totally up to to the Attorney General even the Mueller report said 479 it had nothing to do with the campaign 480 When you look at some of the people 481 it had nothing to do-- 482 Excuse me
483 Excuse me
484 That's up to the attorney general
485 I don't know
486 It depends 487 I have no idea 488 what it's going to say 489 So far this thing's been a total witch hunt 490 And it doesn't implicate me in any way 491 There was no collusion 492 There was no obstruction 493 There was no nothing 494 Doesn't implicate me in any way 495 But I think it's a disgrace. 496 Well I don't want to say that 497 But certainly it's something 498 That's on the- it's an option. 499 Well he is requested a meeting 500 And I've turned it down 501 Because we're very far along in the process 502 You have a young and energetic gentleman 503 But you have other people within that same group that have been very very - 504 If you talk about democracy 505 It's really democracy in action
506 We're going to see what happened
507 A number of months ago he wanted to meet.
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508 Well now we'd have to see. 509 I would say this 510 I decided at the time, "no" 511 because so many really horrible things have been happening in Venezuela 512 when you look at that country 513 That was the wealthiest country of all in that part of the world which is a very important part of the world 514 And now you look at the poverty 515 and you look at the anguish 516 and you look at the crime 517 and you look at all of the things happening
518 So, I think
519 the process is playing out - very very big tremendous protests.
520 I won't tell you yet
521 but you'll be finding out probably State of the Union or shortly before 522 But the meeting is set 523 He's looking forward to it 524 I'm looking forward to it 525 We've made tremendous progress 526 If you remember 527 before I became president 528 it looked 529 like we were going to war with North Korea 530 Now we have a very good relationship 531 The hostages are back 532 the remains are starting to come back 533 I'm in the real estate business 534 Well that's what-- 535 That's what 536 the intelligence chief thinks 537 and I think-- 538 --there's a good possibility of that too 539 But there's also a very good chance 540 that we will make a deal
541 I think
542 he's also tired of going through
543 what he's going through
544 He has a chance to have North Korea be a tremendous economic behemoth 545 It has a chance to be one of the great economic countries in the world 546 He can't do that with nuclear weapons 547 and he can't do that on the path 548 they're on now 549 I like him 550 I get along with him great 551 We have a fantastic chemistry 552 We have had tremendous correspondence 553 that some people have se 554 They think it's historic 555 And we'll see what happens 556 Now that doesn't mean 557 we're going to make a deal 558 But certainly I think 559 we have a very good chance of making a deal 560 And one of the reasons is 561 because North Korea has a chance being located between Russia, China, and South Korea 562 What a location- 563 They have a chance to be an economic powerhouse
564 Yeah, I mean
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565 we haven't talked about anything else 566 I mean who knows 567 But you know 568 it's very expensive to keep troops there 569 You do know that 570 We have 40,000 troops in South Korea 571 it's very expensive 572 But I have no plans 573 I've never even discussed removing them 574 Well, yes but I think
575 we're in a different position now
576 We've put very massive tariffs on China
577 China is paying a big price
578 and it's hurt China's economy very badly 579 I want them to make a fair deal. 580 They have been very helpful, especially at the beginning 581 when I first came in with North Korea 582 They have stopped goods from going in 583 They have stopped a lot of things from going in through the border 584 Because as you know 585 they have a border 586 just like we have a border with Mexico 587 where crime is way up by the way, way up 588 and you have to remember that 589 But we have a border with- 590 they have a border with North Korea 591 They have been very vigilant. 592 Are they the same now? 593 But North Korea is absolutely talking 594 And I think 595 North Korea wants to make a deal 596 We are making a deal 597 It looks
598 like we're doing very well with making a deal with China
599 I can tell you this, no two leaders of this country
600 and China have ever been closer than I am with President Xi
601 We have a good chance to make a deal 602 I don't know 603 that we're going to make one 604 but we have a good chance 605 And if it is a deal 606 it's going to be a real deal 607 It's not going to be a stopgap.
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APPENDIX 4
Congruent and Metaphorical Coding of Trump’s Utterances in Face the Nation Talk Program
Note: D : Declarative Q : Question I : Interrogative Co : Command Im : Imperative O : Offer MI : Modulated Interrogative C : Congruent S : Statement M : Metaphorical
No Donald Trump’s Clauses Mood Speech Function Coding 1 Well, we're going to have to see what happens on February 15th D S C 2 And I- I think-- D S C 3 Well, I don't- D S C 4 I don't take anything off the table D S C 5 I don't like to take things off the table D S C 6 It's that alternative D S C 7 It's national emergency D S C 8 It's other things D S C 9 And you know. D S C 10 There have been plenty national emergencies called D S C 11 And this really is an invasion of our country by human traffickers. D S C 12 These are people that are horrible people bringing in women mostly D S C 13 But bringing in women and children into our country D S C
14 And we're going to have a strong border D S C 15 And the only way you have a strong border is D S C 16 You need a physical barrier D S C 17 You need a wall D S C 18 And anybody that says you don't D S C 19 They're just playing games D S C 20 Well, I think that she was very rigid - which I would expect D S C 21 But I think she is very bad for our country D S C 22 She knows that you need a barrier D S C 23 She wanted to win a political point D S C 24 I happen to think D S C 25 She doesn't mind human trafficking D S C 26 Or she wouldn't do this because you know-- D S C 27 Excuse me? D Co M 28 She's- she's costing the country hundreds of billions of dollars D S C 29 Because what's happening is I S M 30 When you have a porous border D S C 31 And when you have drugs pouring in, D S C 32 And when you have people dying all over the country D S C 33 She's doing a terrible disservice to our country D S C 34 And on the 15th we have now set the table beautifully D S C 35 Because everybody knows D S C 36 What's going on because of the shutdown I S M 37 People that didn't have any idea- D S C 38 They didn't have a clue as to what was happening D S C 39 What's happening I S M 40 They see human trafficking D S C 41 They see drugs and gangs and criminals pouring in. D S C
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42 Now, we catch them because we're doing a great job D S C 43 But if we had proper border security D S C 44 We wouldn't have to work so hard D S C 45 And we could do an even better job D S C 46 And I think D S C 47 Nancy Pelosi is doing a terrible disservice to the people of our D S C country 48 But she can-- D S C 49 No, she can keep playing her games D S C 50 But we will win. D S C 51 Because we have a much better issue D S C 52 On a political basis, what she's doing is- D Q M 53 I actually think it's bad politics, D S C 54 But much more importantly it's very bad for our country. D S C 55 I did. D S C 56 Well, I think-- D S C 57 I think- D S C 58 Let me just say Im S M 59 It wasn't so much a report. D S C 60 It was the D S C s and answers 61 As the report was submitted D S C 62 And they were asked Qs and answers. D S C 63 We've done an incredible job with Syria. D S C 64 When I took over Syria D S C 65 It was infested with ISIS D S C 66 It was all over the place D S C 67 And now you have very little ISIS D S C 68 And you have the caliphate almost knocked out D S C 69 We will be announcing in the not too distant future 100 percent of D S C the caliphate which is the area- the land- the area- 100. 70 We're at 99 percent right now D S C 71 We'll be at 100 D S C 72 When I took it over D S C 73 It was a disaster D S C 74 I think we've done a great job with that. D S C 75 At the same time, at a certain point, we want to bring our people D S C back home. 76 If you look at Afghanistan D S C 77 We're going in very soon D S C 78 We'll be going into our 19th year spending 50 billion dollars a year. D S C 79 Now if you go back D S C 80 And look at any of my campaign speeches or rallies D S C 81 I talked about it all the time. D S C 82 --I want to bring people home. D S C 83 By the way-- D S C 84 You're going to always have pockets of something. D S C 85 What-- you're going to have people, like the one armed man who D Q M blew up a restaurant. 86 You're going to have pockets D S C 87 But you're not going to keep armies there D S C 88 Because you have a few people D S C 89 Or you even have fairly reasonable numbers of people. D S C 90 We've been there for many, many years. D S C 91 We were supposed to be in Syria for four months. D S C 92 We've been there for years D S C 93 We have been in Afghanistan for 19 years D S C 94 And by the way, I've been hitting very hard in Afghanistan D S C
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95 And now we're negotiating with the Taliban. D S C 96 We'll see what happens, who knows-- D Q M 97 Look, whether we should have been there in the first place, that's Im S M first Q. Second Q-- 98 We've been there for 19 years, almost, D S C 99 We are fighting very well. D S C 100 We're fighting harder than ever before D S C 101 And I think D S C 102 that they will- D S C 103 I think D S C 104 they're tired and, D S C 105 I think everybody's tired D S C 106 We got to get out of these endless wars and bring our folks back D S C home. 107 Now, that doesn't mean. D S C 108 We're not going to be watching with intelligence D S C 109 We're going to be watching, and watching closely. D S C 110 North Korea-- D S C 111 Well, everything's harder D S C 112 But, you know D S C 113 You pay a big price for troops on the ground. D S C 114 We're spending hundreds of billions of dollars on military. D S C 115 We're the policemen of the world and we don't-- D S C 116 Sure. D S C 117 And you know what we'll do? D Q M 118 We'll come back D S C 119 If we have to D S C 120 We have very fast airplanes, D S C 121 We have very good cargo planes. D S C 122 We can come back very quickly, D S C 123 And I'm not leaving D S C 124 We have a base in Iraq D S C 125 And the base is a fantastic edifice. D S C 126 I mean I was there recently D S C 127 And I couldn't believe the money that was spent on these massive D S C runways. 128 And these- I've rarely seen anything like it D S C 129 And it's there D S C 130 And we'll be there D S C 131 And frankly, we're hitting the caliphate from Iraq and as we slowly D S C withdraw from Syria 132 And as we slowly withdraw from Syria D S C 133 Now the other thing-- D S C 134 2,000 troops. D S C 135 They're starting to D S C 136 As we gain the remainder, the final remainder of the caliphate of the D S C area 137 They'll be going to our base in Iraq D S C 138 And ultimately some will be coming home D S C 139 But we're going to be there D S C 140 And we're going to be staying-- D S C 141 We have to protect Israel D S C 142 We have to protect other things that we have D S C 143 But we're- yeah, they'll be coming back in a matter of time. D S C 144 Im S M , we're protecting the world
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145 We're spending more money than anybody's ever spent in history, by D S C a lot 146 We spent, over the last five years, close to 50 billion dollars a year D S C in Afghanistan. 147 That's more than most countries spend for everything including D S C education, medical, and everything else, other than a few countries. 148 Yes. D S C 149 And I'll leave intelligence there. Real intelligence, by the way. D S C 150 I'll leave intelligence there and if I see nests forming D S C 151 I'll do something about it D S C 152 But for us to be spending 51 billion dollars, like last year, or if you D S C average the cost 153 It's- I mean you're talking about numbers that nobody's ever heard of D S C before. 154 I ran against 17 Republicans. D S C 155 This was a big part of what I was saying, and I won very easily D S C 156 I think the people out in the world- D S C 157 I think people in our country agree D S C 158 We've been fighting for 19 years D S C 159 Somebody said you were precipitously bringing to- precipitously? D Q M 160 We've been there for 19 years. D S C 161 I want to fight. D S C 162 I want to win, and we want to bring our great troops back home. D S C 163 I've seen the people. D S C 164 I go to Walter Reed Hospital. D S C 165 I see what happens to people. D S C 166 I see with no legs and no arm- arms D S C 167 And I've seen also what happens to them up here because they're in D S C this situation 168 And they come back D S C 169 And they are totally different people-- D S C 170 Because they're in this situation D S C 171 What has happened to my son I Q C 172 What has happened in some cases to my daughter? I Q C 173 It's a terrible thing D S C
174 We've been there close to 19 years. And it's time. D S C 175 And we’ll see what happens with the Taliban D Q M 176 They want peace D S C 177 They're tired D S C 178 Everybody's tired D S C 179 We'd like to have- I don't like endless wars D S C 180 This war D S C 181 What we're doing is got to stop at some point. D S C 182 I'm not telegraphing anything. D S C 183 No, no, no. D S C 184 There's a difference D S C 185 When President Obama pulled out of Iraq in theory we had Iraq D S C 186 In other words, we had Iraq D S C 187 We never had Syria because President Obama never wanted to D S C violate the red line in the sand 188 So we never had Syria D S C 189 I was the one that actually violated the red line when I hit Syria with D S C 59 Tomahawk missiles, if you remember 190 But President Obama chose not to do that D S C 191 When he chose not to do that, he showed tremendous weakness D S C 192 But we didn't have Syria whereas we had Iraq D S C
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193 So when he did what he did in Iraq, which was a mistake. Being in D S C Iraq was a mistake 194 Okay D S C 195 Being in Iraq- it was a big mistake to go- one of the greatest D S C mistakes going into the Middle East that our country has ever made- - 196 --but when it was chosen--. D S C 197 well, we spent a fortune on building this incredible base D S C 198 We might as well keep it D S C 199 And one of the reasons I want to keep it is D S C 200 because I want to be looking a little bit at Iran D S C 201 because Iran is a real problem D S C 202 No, because I want to be able to watch Iran D S C 203 All I want to do is be able to watch D S C 204 We have an unbelievable and expensive military base built in Iraq D S C 205 It's perfectly situated for looking at all over different parts of the D S C troubled Middle East rather than pulling up 206 And this is what a lot of people don't understand D S C 207 We're going to keep watching D S C 208 and we're going to keep seeing D S C 209 and if there's trouble D S C 210 if somebody is looking to do nuclear weapons or other things D S C 211 we're going to know it D S C 212 before they do D S C 213 I am going to trust the intelligence D S C 214 that I'm putting there D S C 215 but I will say this: my intelligence people D S C 216 if they said in fact D S C 217 that Iran is a wonderful kindergarten D S C 218 I disagree with them 100 percent D S C 219 It is a vicious country that kills many people D S C 220 When you talk about torture and so many other things. D S C 221 And- maybe they'll come back. D S C 222 The country is getting absolutely- D S C 223 when I ended the horrible Iran nuclear deal- D S C 224 it was a horrible deal done by President Obama and John Kerry that D S C didn't know 225 what the hell he was doing D S C 226 When I ended that deal, Margaret, D S C 227 all of a sudden Iran became a different country D S C 228 They became- very rapidly- right now D S C 229 They're a country that's in big financial trouble. D S C 230 Let's see what happens. Im S M 231 I disagree with them. D S C 232 I'm- I'm- by the way-- D S C 233 --I have intel people, but that doesn't mean D S C 234 I have to agree D S C 235 President Bush had intel people that said Saddam Hussein-- D S C 236 President Bush had intel people that said Saddam Hussein-- D S C 237 Guess what? D Q M 238 Those intel people didn't know what the hell D S C 239 they were doing D S C 240 and they got us tied up in a war D S C 241 that we should have never been in D S C 242 And we've spent seven trillion dollars in the Middle East and we D S C have lost lives-- 243 and we have lost lives-- D S C 244 I do D S C
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245 and I respect John D S C 246 and John is not one of the people that happened to be testifying or on D S C 247 And you know what I tell people- D S C 248 you can testify any way you want D S C 249 I'm not going to stop them from testifying. D S C 250 They said they were mischaracterized-- D S C 251 maybe they were D S C 252 maybe they weren't D S C 253 I don't really know-- D S C 254 but I can tell you this D S C 255 I want them to have their own opinion D S C 256 and I want them to give me their opinion D S C 257 But, when I look at Iran, D S C 258 I look at Iran as a nation that has caused tremendous problems D S C 259 When I came in as president of the United States, my first year, D S C 260 I went to the Pentagon two weeks D S C 261 after I came in, a short time after D S C 262 and I was given a- D S C 263 because I wanted to know what's going on with Iran D S C 264 We were in many many locations in the Middle East in huge D S C difficulty 265 Every single one of them was caused by the number one terrorist D S C nation in the world which is Iran 266 So when my intelligence people tell me how wonderful Iran is-, D S C 267 if you don't mind D S C 268 I'm going to just go by my own counsel D S C 270 So we have a great cabinet D S C 271 I have great people D S C 272 I think now D S C 273 we have a really great cabinet D S C 274 I think Bill Barr will be a fantastic attorney general, D S C 275 and I think D S C 276 that we have- Mike Pompeo's been doing a fantastic job D S C 277 We have-- D S C 278 No, I don't- D S C 279 I mean D S C 280 he tells me D S C 281 he wouldn't want to leave D S C 282 I think that was-- D S C 283 That was fake news. D S C 284 Well, he may have spoken to him, D S C 285 he loves being secretary of state D S C 286 He's doing a fantastic job D S C 287 And I asked him the Q the other day, D S C 288 he says D S C 289 he's absolutely not leaving D S C 290 I don't think D S C 291 he'd do that D S C 292 And he doesn't want to be lame duck D S C 293 And he's doing a fantastic job as our secretary of state D S C 294 Great energy and great- a great, smart gentleman D S C 295 Yes D S C 296 It's OK D S C 297 It's easier to make moves when they're acting D S C 298 Some, and some not D S C 299 Some are doing a fantastic job D S C 300 Really- I like acting D S C 301 because I can move so quickly D S C
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302 It gives me more flexibility D S C 303 But- but actually, some of the names you mentioned, D S C 304 They're doing a fantastic job D S C 305 When it's not happening. When-- D S C 306 When it doesn't get done D S C 307 Like with General Mattis, I wasn't happy with his service D S C 308 I told him give me a letter. D S C 309 He resigned because D S C 310 I asked him to resign D S C 311 He resigned D S C 312 Because I was very nice to him D S C 313 But I gave him big budgets and D S C 314 He didn't do well in Afghanistan D S C 315 I was not happy with the job D S C 316 He was doing in Afghanistan D S C 317 And if you look at Syria what's happened D S C 318 I went to Iraq recently D S C 319 If you look at Syria what's happened in Syria in the last few weeks, D S C 320 You would see D S C 321 That things are going down that were not going down D S C 322 That things are happening that are very good D S C 323 So I was not happy with him, D S C 324 But I wish him well D S C 325 I think so D S C 325 I mean D S C 326 I was just one that felt very important D S C 327 You can't be kneeling for the national anthem D S C 328 You have to respect our flag and our country D S C 329 I want that as president D S C 330 And I'd want that as a citizen D S C 331 And I have a very good relationship D S C 332 I did them a big favor in negotiating the USMCA, which is basically D S C the replacement to NAFTA, which is one of the worst trade deals ever made 333 And I said to Canada D S C 334 Look we have a great American company known as the NFL Im S C 335 And they were being hurt and treated unfairly, the NFL, by Canada D S C for a long time 336 And I said to Prime Minister Trudeau, who was very nice about it D S C and really understood it, 337 you can settle the difference immediately and fast D S C 338 And they did. D S C 339 So I did the NFL a big favor, as a great American company and they D S C appreciated it. 340 this is a dispute that has gone on for years called me D S C 341 and he thanked me D S C 342 And I appreciated that D S C 343 But they haven't been kneeling D S C 344 and they have been respecting the flag D S C 345 and their ratings have been terrific ever since D S C 346 And a lot of good things happened D S C 347 Well, you know D S C 348 I'm the one that had passed judicial reform D S C 349 And if you look at what I did, criminal judicial reform D S C 350 and what I've done- President Obama tried D S C 351 They all tried D S C 352 Everybody wanted to do it D S C 353 And I got it done D S C
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354 and I've been D S C 355 you know D S C 356 a lot of people in the NFL have been calling and thanking me for it D S C 357 They have been calling and thanking D S C 358 you know, that people have been trying to get D S C 359 I think that when you want to protest D S C 360 I think that's great D S C 361 But I don't think D S C 362 you do it at the sake of our flag, at the sake of our national anthem D S C 363 when you want to protest D S C 364 Well I do-- D S C 365 A lot of it is having to do with reform from what I understand D S C 366 Whether it's criminal justice D S C 367 or whatever it may be D S C 368 and they have different versions D S C 369 and everybody seemed to have a different version of it D S C 370 But a lot of it had to do with that D S C 371 and I took care of that D S C 372 I think that people have to, at all times D S C 373 respect our flag and at all times D S C 374 respect our net- our- our national anthem and our country D S C 375 And I think D S C 376 there are plenty of places D S C 377 and times you can protest D S C 378 and you can do a lot D S C 379 But you can't do that D S C 380 That's my opinion D S C 381 this is something very special what's happening D S C 382 What has happened is very interesting I S M 383 The economy is so good right now D S C 384 You saw the jobs report just came out D S C 385 Three hundred and four thousand added jobs, which is a shocker, for D S C the month 386 They thought D S C 387 It was going to be half that number D S C 388 The African-Americans have the best employment numbers in the D S C history of our country 389 Hispanic Americans have the best employment numbers in the D S C history of our country 390 You look at women, the best in 61 years D S C 391 And our employment numbers are phenomenal, the best in over 50 D S C years 392 So I think I've been given a lot of credit for that D S C 393 And in terms of race, a lot of people are saying well D S C 394 I have a great relationship with Tim and certainly with his state, D S C South Carolina 395 And- where we do very well D S C 396 And I think D S C 397 they've had- literally the best numbers they've had in history D S C 398 And I think they like me a lot and I like them a lot D S C 399 if you look at the numbers for African-American unemployment D S C 400 It's very tough Q D S C 401 It's a very good Q D S C 402 If he wanted to? D Q C 403 Would I steer him that way? MI O C 404 I wouldn't D S C 405 that I see coming out having to do with football D S C 406 And he actually plays a lot of soccer D S C
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407 He's liking soccer D S C 408 And a lot of people, including me, thought soccer would probably D S C never make it in this country 409 But it really is moving forward rapidly D S C 410 I- I just don't like the reports D S C 411 I mean, D S C 412 It's a dangerous sport D S C 413 And I think D S C 414 I- it's- really tough D S C 415 I thought D S C 416 The equipment would get better D S C 417 And it has D S C 418 The helmets have gotten far better D S C 419 But it hasn't solved the problem D S C 420 So, you know D S C 421 I- I hate to say it D S C 422 because I love to watch football D S C 423 I think D S C 424 the NFL is a great product D S C 425 but I really think that as far as my son- well D S C 426 I've heard NFL players saying D S C 427 they wouldn't let their sons play football D S C 428 they wouldn't let their sons play football D S C 429 I would have a hard time with it D S C 430 Well, look the Russia thing is a hoax Im Co M 431 I have been tougher on Russia than any president, maybe ever D S C 432 But than any president D S C 433 Excuse me. D S C 434 Ok, you ready? D Q M 435 Of the 34 people, many of them were bloggers from Moscow D S C 436 they were people that had nothing to do with me, had nothing to do D S C with 437 what they're talking about D S C 438 or there were people that got caught telling a fib or telling a lie D S C 439 I think D S C 440 it's a terrible thing that's happened to this country D S C 441 because this investigation is a witch hunt D S C 442 It's a terrible witch hunt D S C 443 and it's a disgrace-- D S C 444 --when you look at General Flynn D S C 445 where the FBI said D S C 446 he wasn't lying D S C 447 but Robert Mueller said D S C 448 he was D S C 449 and they took a man and destroyed his life D S C 450 When you look at so many of the things that have happened- D S C 451 Why didn't they go after Hillary Clinton for her emails? I Q C 452 She had thirty three thousand emails that were deleted after D S C receiving a subpoena from Congress-- 453 that were deleted after receiving a subpoena from Congress-- D S C 454 but Margaret, why-- D Q M 455 First of all, Roger Stone didn't work on the campaign, except way D S C way at the beginning long 456 before we're talking about D S C 457 Roger is somebody D S C 458 that I've always liked D S C 459 but a lot of people like Roger D S C
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460 some people probably don't like Roger D S C 461 but Roger Stone's somebody I've always liked D S C 462 I mean Roger's a character D S C 463 but Roger was not D S C 464 I don't know D S C 465 if you know this or not- D S C 466 Roger wasn't on my campaign except way at the beginning-- D S C 467 So, it's all D S C 468 - and- and yet you will ask me a Q like that, wasn't involved in my D S C campaign. 469 I have not thought about it D S C 470 It looks like D S C 471 he's defending himself very well D S C 472 But you have to get rid of the Russia witch hunt D S C 473 because it is indeed D S C 474 Remember this D S C 475 Remember this D S C 476 There's been no president D S C 477 that has been tougher on Russia than Donald Trump D S C 478 Totally up to to the Attorney General even the Mueller report said D S C 479 it had nothing to do with the campaign D S C 480 When you look at some of the people D S C 481 and the events it had nothing to do-- D S C 482 Excuse me D S C 483 Excuse me D S C 484 That's up to the attorney general D S C 485 I don't know D S C 486 It depends D S C 487 I have no idea D S C 488 what it's going to say D S C 489 So far this thing's been a total witch hunt D S C 490 And it doesn't implicate me in any way D S C 491 There was no collusion D S C 492 There was no obstruction D S C 493 There was no nothing D S C 494 Doesn't implicate me in any way I S M 495 But I think it's a disgrace. D S C 496 Well I don't want to say that D S C 497 But certainly it's something D S C 498 That's on the- it's an option. D S C 499 Well he is requested a meeting D S C 500 And I've turned it down D S C 501 Because we're very far along in the process D S C 502 You have a young and energetic gentleman D S C 503 But you have other people within that same group that have been D S C very very - 504 If you talk about democracy D S C 505 It's really democracy in action D S C 506 We're going to see what happened D Co M 507 A number of months ago he wanted to meet. D S C 508 Well now we'd have to see. D S C 509 I would say this D S C 510 I decided at the time, "no" D S C 511 because so many really horrible things have been happening in D S C Venezuela 512 when you look at that country D S C 513 That was the wealthiest country of all in that part of the world which D S C is a very important part of the world
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514 And now you look at the poverty D Co M 515 and you look at the anguish D Co M 516 and you look at the crime D Co M 517 and you look at all of the things happening D Co M 518 So, I think D S C 519 the process is playing out - very very big tremendous protests. D S C 520 I won't tell you yet D S C 521 but you'll be finding out probably State of the Union or shortly D S C before 522 But the meeting is set D S C 523 He's looking forward to it D S C 524 I'm looking forward to it D S C 525 We've made tremendous progress D S C 526 If you remember D S C 527 before I became president D S C 528 it looked D S C 529 like we were going to war with North Korea D S C 530 Now we have a very good relationship D S C 531 The hostages are back D S C 532 Okay, the remains are starting to come back D S C 533 The remains of our Korean War veterans-- D S C 534 Well that's what-- D Q M 535 That's what D Q M 536 the intelligence chief thinks D S C 537 and I think-- D S C 538 --there's a good possibility of that too D S C 539 But there's also a very good chance D S C 540 that we will make a deal D S C 541 I think D S C 542 he's also tired of going through D S C 543 what he's going through D S C 544 He has a chance to have North Korea be a tremendous economic D S C behemoth 545 It has a chance to be one of the great economic countries in the D S C world 546 He can't do that with nuclear weapons D S C 547 and he can't do that on the path D S C
548 they're on now D S C 549 I like him D S C 550 I get along with him great D S C 551 We have a fantastic chemistry D S C 552 We have had tremendous correspondence D S C 553 that some people have seen and can't even believe it D S C 554 They think it's historic D S C 555 And we'll see what happens D Q M 556 Now that doesn't mean D S C 557 we're going to make a deal D S C 558 But certainly I think D S C 559 we have a very good chance of making a deal D S C 560 And one of the reasons is D S C 561 because North Korea has a chance being located between Russia, D S C China, and South Korea 562 What a location- I'm in the real estate business- what a location D S C 563 They have a chance to be an economic powerhouse D S C 564 Yeah, I mean D S C 565 we haven't talked about anything else D S C 566 I mean who knows D Q M
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567 But you know D Q M 568 it's very expensive to keep troops there D S C 569 You do know that D S C 570 We have 40,000 troops in South Korea D S C 571 it's very expensive D S C 572 But I have no plans D S C 573 I've never even discussed removing them D S C 574 Well, yes but I think D S C 575 we're in a different position now D S C 576 We've put very massive tariffs on China D S C 577 China is paying a big price D S C 578 and it's hurt China's economy very badly D S C 579 I want them to make a fair deal. D S C 580 They have been very helpful, especially at the beginning D S C 581 when I first came in with North Korea D S C 582 They have stopped goods from going in D S C 583 They have stopped a lot of things from going in through the border D S C 584 Because as you know D S C 585 they have a border D S C 586 just like we have a border with Mexico D S C 587 where crime is way up by the way, way up D S C 588 and you have to remember that D S C 589 But we have a border with- D S C 590 they have a border with North Korea D S C 591 They have been very vigilant. D S C 592 Are they the same now? I Q C 593 But North Korea is absolutely talking D S C 594 And I think D S C 595 North Korea wants to make a deal D S C 596 We are making a deal D S C 597 It looks D S C 598 like we're doing very well with making a deal with China D S C 599 I can tell you this, no two leaders of this country D S C 600 and China have ever been closer than I am with President Xi D S C 601 We have a good chance to make a deal D S C 602 I don't know D S C 603 that we're going to make one D S C 604 but we have a good chance D S C 605 And if it is a deal D S C 606 it's going to be a real deal D S C 607 It's not going to be a stopgap. D S C
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