General Index
Analytical framework
180, 181, 185, 206, 213
Annotation
34, 37, 40, 46, 124
Appraisal resources
16, 17
Aristotle
1, 216
Attitude
17, 19, 23, 24, 86, 131, 132, 228, 235
Attitudinal scale
93, 96
Bandung
2, 139n, 180n, 216n
Berger, Tobias
2, 7, 139, 145, 257, 259
Brown family corpora
78, 81, 88
Budget speeches
34, 187, 187n4, 200, 201, 209, 210, 211, 212
Cantonese
4, 33, 34, 37n, 40, 41, 42, 44, 46, 187
CEPIC corpus
3, 4, 5, 29, 33, 33n, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 46n, 47, 48, 187n7
cepic
4, 5, 33, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48
Children’s literature
252, 253, 254
China
6, 25, 31, 81, 121, 132, 216, 216n, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 242, 242n1, 244, 244n6, 246, 246n, 247, 247n, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 258n44, 258n46, 259, 260, 261
Chinese
3, 4, 5, 6, 11, 11n, 12, 29, 30, 32, 33, 34, 37n, 38, 40, 45, 75, 76, 77, 78, 80, 80n, 81, 82, 84, 85, 86, 88, 88n, 90, 91, 93, 94, 96, 97, 116, 118, 120, 121, 122, 123, 124, 125, 128, 129, 130, 132, 187, 187n7, 189, 198, 199, 199n, 211, 216, 216n, 217, 219, 219n3, 220, 221, 224, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 238, 239, 242, 242n1, 243, 244, 245, 245n8, 246, 247, 248, 249, 250, 250n21, 251, 252, 253, 254, 255, 256, 257, 257n42, 257n43, 258n43, 259, 260, 261
Chinese and English
4, 33, 75, 78, 80, 81, 88, 88n, 90, 91, 93, 96
Chinese literature
6, 242, 242n1, 243, 244, 245, 245n8, 246, 247, 248, 251, 252, 253, 254, 255, 256, 257, 257n42, 257n43, 258n43, 259, 260, 261
Chinese people
246, 247, 250, 257, 261
Cohesion shifts
77
Collocation graphs
199, 200
Communication accommodation theory (cat)
56
Communist party
246, 248, 249, 251, 253, 258
Communities of practice
57, 60
Comparable corpus
75, 82
Comparative politeness studies
000
Conference interpreting
4, 74, 75, 77, 96, 119
Context of culture
14
Corpora
4, 6, 16, 29, 30, 31,32, 32n2, 33, 36, 37, 46, 47, 48, 68, 74, 75, 77, 78, 80, 81, 82, 83n, 88, 88n, 97, 117, 144, 185, 186, 188n9, 220, 221, 237
Corpus
3, 4, 5, 29, 30, 31, 32, 33, 34, 36, 37, 40, 42, 46, 47, 58, 59, 60, 61, 68, 74, 75, 80, 81, 81n, 82, 83, 121, 185, 186, 187, 187n7, 188, 189, 197, 199, 204, 206, 208, 212, 219, 220, 221, 222, 223, 227, 228, 230, 231, 237, 238
Corpus-assisted discourse studies
32
Corpus-assisted tools
5
Corpus based
4, 6, 29, 31, 32, 74, 75, 117, 187
Corpus-based interpreting studies
31, 32, 74
Corpus-based translation studies
32, 74
Culture-specific items
116, 117, 118, 119, 130
Data
5, 29, 30, 31, 32, 33, 34, 37, 38, 39, 40, 42, 44, 45, 46, 46n, 47, 48, 56, 61, 62, 67, 68, 75, 76, 81, 82, 83, 84, 93, 117, 121, 123, 125, 141, 145, 146, 147, 148, 161, 165, 185, 188, 212, 219, 221, 237, 239
Dataset
37, 40, 47, 140, 144, 146, 147, 148, 150, 152, 153, 154, 157, 161, 163, 164, 165, 167, 168, 169, 170, 171, 172, 173, 174
Decolonial
5, 140, 141, 142, 170, 171, 173
Deictic centre
23
Diatopic variation
67
Discourse
1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 14, 15, 19, 21, 25, 26, 29, 30, 31, 32, 38, 40, 44, 45, 46, 47, 56, 57, 58, 59, 60, 66, 67, 68, 80, 87, 88, 121, 128, 139, 139n, 140, 142, 143, 146, 148, 150, 152, 161, 164, 165, 168, 172, 173, 174, 180, 180n, 181, 182, 183, 184, 185, 186, 197, 199, 206, 209, 210, 212, 213, 219, 220, 221, 222, 223, 224, 226, 237
Discourse analysis
6, 13, 29, 38, 180, 181, 182, 183, 185, 237
Discourse community
56, 57, 58, 60, 66, 67, 68
Discourse semantics
15
Discriminant correspondence analysis
62, 63
Domestic affairs
230, 231, 234
Dutch
4, 30, 31, 56, 57, 60, 61, 62, 63, 65, 66, 67, 68
East Germany
242, 242n1, 243, 244, 246, 247, 248, 249, 251, 252, 253, 254, 256, 256n37, 257n43, 258, 259, 260, 261
Engagement
6, 23, 140, 143, 152, 170
English
3, 4, 5, 7, 14, 16, 25, 29, 30, 31, 33, 34, 37n, 38, 40, 41, 42, 43, 44, 45, 46, 59, 61, 62, 68, 74, 75, 76, 77, 78, 80, 81, 82, 83, 83n, 84, 87, 88, 88n, 89, 90, 91, 93, 94, 96, 97, 120, 121, 122, 126, 127, 128, 129, 130, 144, 152, 163, 167, 168, 169, 183, 184, 187, 187n4, 187n7, 188, 189, 192n3, 194n3, 197, 198, 199, 199n, 211, 217, 219, 219n2, 227n, 242n1
epicg corpus
61
Equalising effect
76, 89, 90, 91, 93, 96, 97
Ethics
3, 17, 23, 184
Ethnography
146
European Parliament
4, 30, 32, 33, 47, 55, 56, 57, 59, 60, 61, 66, 67, 68, 77, 78, 230
Evaluative profile
18, 19
Explicitation
77
Face
6, 32, 55, 216, 216n, 217, 218, 219, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239
National face
6, 216, 216n, 219, 227, 238, 239
Negative face
216, 227, 228, 229, 230, 231, 234, 239
Facework
6, 183, 216, 216n, 217, 219, 224, 232, 233, 237, 238, 239
Feature distributions
75
Field
1, 2, 3, 6, 7, 11, 15, 19, 31, 32, 33, 47, 48, 140, 181, 182, 185, 244, 249n15, 257, 259
Frequency
17, 19, 40, 41, 58, 62, 75, 77, 82, 147, 189, 192n1, 192n2, 192n3, 194n1, 194n3, 196, 197, 198, 206, 208, 210, 211, 212, 220, 221, 222
Functional dimensions
75
Functional scales
75, 80, 81, 88, 93, 96
Genre
1, 5, 7, 14, 15, 16, 29, 30, 31, 34, 57, 58, 59, 67, 68, 76, 121, 180, 182, 212, 244, 249, 250n21, 252, 254
German Democratic Republic
.
see East Germany
Global-centric
142, 170, 175
Globalnorth
140, 141, 142, 169, 170, 172, 173, 174
Globalsouth
139, 139n, 140, 170, 173, 174, 180n, 216n
Government
6, 25, 34, 37, 46, 77, 81, 127, 146, 152, 154, 164, 180, 187, 187n6, 189, 196, 197, 198, 199, 200, 201, 202, 204, 206, 208, 209, 210, 211, 212, 217, 218, 219, 221, 224, 229, 230, 232, 233, 234, 236, 237, 239, 243, 247n11, 256, 257
Graduation
17, 23
Hierarchical agglomerative cluster analysis
75, 84, 93
High frequency
77, 189, 196, 197, 198, 206, 211
hk budget
200
hk policy
200, 201
Hong Kong
2, 5, 34, 42, 43, 48, 77, 180, 184, 187, 187n2, 187n3, 187n4, 189, 196, 206, 208, 209, 210, 211, 212, 213, 228, 232, 233, 234, 239
House press
6, 217, 218, 220, 222, 223, 239
ictclas
80, 80n
Identity
1, 3, 5, 6, 13, 14, 130, 139, 139n, 140, 141, 142, 145, 146, 150, 153, 159, 160, 161, 163, 164, 170, 172, 173, 174, 208, 210, 230, 234, 243, 254
Idioms
118, 119, 121, 123, 127, 128, 129, 130, 131
India
5, 139, 143, 154, 155, 197
Interdisciplinary approaches
6
Interpretese
4, 43
Language varieties
13, 30, 75
Languaging
5, 139, 139n, 140, 141, 145, 146, 147, 152, 153, 165, 167, 168, 169, 170, 173, 174, 175
Levelling effect
77
Lexical bundles
56, 58, 59, 60, 61, 66, 68, 221
Lexical patterns
76
Linguistic convergence
4, 55, 56, 67
Linguistic metaphors
118, 123, 130, 131
Media
2, 5, 7, 118, 139n, 140, 141, 143, 144, 145, 146, 148, 148n, 149, 151, 160, 161, 165, 167, 171, 172, 174, 180, 181, 183, 184, 185, 210, 213, 220, 223, 225, 236, 259
Ministry of Chinese Foreign Affairs
6
Mixed effects model
63, 65
Modalities
139, 141, 142, 167, 168,169, 174
Mode
3, 6, 7, 12, 13, 15, 16, 26, 75, 77, 97
Multidimensional analysis
74
Multidimensional (md) analysis tagger
74, 80
Narrative scale
91
Nation states
139, 143, 144, 164
New media
140, 143, 144, 145, 151, 170, 171, 181
N-grams
4, 55, 57, 58, 59, 60, 62, 63, 67, 68, 220, 221, 222, 227
Novice interpreters
5, 116, 117, 119, 121, 122, 125, 126, 127, 128, 130, 131, 132
Online corpus
40
Oral and literate scale
88
Oral/literate opposition
85, 87, 88
Oral-literate continuum
75, 76
Parallel corpus
30, 32, 81, 82
Parliamentary discourse
59
Paratexts
242n1, 245, 261
Podium
219, 223, 225, 226, 229, 230, 231, 232, 234, 235, 236, 237, 238, 239
Policy speeches
6, 46, 180, 180n, 187, 189, 200, 201, 206, 208, 209, 212, 213
Politeness
181, 182, 183, 216, 217, 226, 233
Political discourse
1, 2, 3, 4, 5, 6, 7, 11, 13, 14, 26, 29, 30, 31, 32, 38, 40, 45, 46, 47, 128, 139, 140, 146, 152, 161, 165, 168, 173, 174, 180, 180n, 181, 182, 183, 184, 185, 186, 206, 210, 212, 213
Political interpreting
3, 29, 33, 46, 48, 75, 187n7
Political language
1, 5, 180, 183, 184, 206, 210, 211, 212, 213
Political parties
5, 140, 143, 145, 146, 147, 148, 165, 168, 169, 170, 171, 172
Political speech
4, 7, 11, 12, 17, 20, 30, 31, 33, 82, 116, 121, 129, 131, 132, 180, 185
Political translation
3, 4, 29, 31, 32, 33, 36, 46, 47
Positioning
5, 23, 26
Pragmatics
3, 180, 180n, 181, 182, 183, 184, 185, 206, 210, 212, 213
Presidential speeches
3, 30
Press conferences
6, 7, 31, 32, 34, 81, 216, 216n, 219, 224
Press briefings
6, 77, 217, 219, 220, 222, 223, 239
Prime minister
237
Professional interpreters
32, 116, 117, 121, 122, 124, 125, 126, 127, 128, 129, 130, 131, 132
Professional experience
55, 117, 119, 124, 131, 132
Proper names
118, 120, 121, 123, 126, 127, 128, 129, 130, 131
Putonghua
4, 33, 34, 41, 42, 45, 46, 122
Readability analyser
74
Reading positions
3, 24, 25
Register
3, 4, 14, 15, 19, 24, 26, 45, 58, 60, 74, 75, 76, 77, 78, 80, 81, 82, 84, 85, 86, 87, 88, 90, 91, 93, 94, 95, 96, 97, 121
Register analysis
3, 4, 15, 26
Register shifts
74, 75, 76, 77, 78, 88, 93
Register variation
75, 80, 84, 85, 87
Relevant frequency
189, 197, 198
Republic of China
233, 242, 250, 256, 257, 260
Simplification
77, 189, 196
Simultaneous interpreting
11, 31, 55, 59, 117, 118, 122, 187
Social media
5, 7, 140, 143, 144, 145, 146, 160, 161, 165, 172, 174, 184
Socialism
243, 243n3, 245, 246, 247, 249, 250, 252, 253, 254, 255, 256, 258, 260, 261
Socialist world
242, 245, 249, 254
Sociocultural perspective
5, 140, 141
Source speech
4, 43, 74, 76, 76n, 77, 78, 88, 96, 97, 117, 118, 121, 123, 125, 126, 127, 128, 131
Speech
3, 4, 5, 6, 7, 11, 11n, 12, 17, 18, 19, 20, 22, 22n2, 23, 25, 26, 30, 31, 33, 37, 38, 39, 40, 41, 43, 45, 46, 56, 60, 61, 62, 63, 65, 67, 68, 74, 75, 76, 76n, 77, 78, 80, 81, 82, 84, 85, 86, 88, 90, 91, 92, 93, 94, 95, 96, 97, 116, 117, 118, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 180, 180n, 181, 182, 184, 185, 187, 187n3, 187n6, 188, 189, 196, 199, 200, 201, 202, 206, 208, 209, 210, 211, 212, 213, 225, 236
Spoken Dutch corpus
61
Stanford tagger
80, 81
Swales, John
56, 58, 67
Sweden
5, 139, 143, 146, 150, 158
Systemic Functional Linguistics (sfl)
3, 13
Tenor
15, 16
Transcription
12, 32, 34, 37, 38, 40, 46, 121, 123, 219
Translation and interpreting
2, 3, 6, 11, 21, 31, 32, 33, 116, 117, 122, 184, 211
Twitter
12, 145, 148, 167, 174
Tymoczko, Maria
22
UK budget
201, 208, 209
UK policy
210
White House
6, 23, 217, 218, 220, 222, 223, 224, 231, 238, 239