In:Advances in Corpus-based Research on Academic Writing: Effects of discipline, register, and writer expertise
Edited by Ute Römer-Barron, Viviana Cortes and Eric Friginal
[Studies in Corpus Linguistics 95] 2020
► pp. 357–358
Subject index
Published online: 20 February 2020
https://doi.org/10.1075/scl.95.si
https://doi.org/10.1075/scl.95.si
A
- ANOVA 17–18, 20, 124–126, 318, 321
- AVL (Academic Vocabulary List) 9–10, 12–13, 17, 23–24, 335
- audience(s) 187, 205, 265, 319–320, 328
B
- BAWE (British Academic Writing in English) corpus 93, 257, 335
C
- COCA (Corpus of Contemporary American English) 10, 12, 28, 45, 65, 67, 69–78, 80, 98, 199, 271, 336, 338
- collocation 5, 10, 24, 36, 50, 52, 67, 74, 333–340, 342–345, 347–352 ; see also collocational transfer 50, 52–53
- Construction Grammar 33, 59, 61, 63
- CorAAL (Corpus of Articles in Applied Linguistics) 205, 207–208, 210–215, 217–221, 223–224
- CorAChem (Corpus of Articles in Chemistry) 205, 207–208, 210–224
- CRAT (Constructed Response Analysis Tool) 97–98
- cross-disciplinary 137, 172, 174, 180, 192, 212, 334
D
- data-driven learning 245, 258, 272–273
- discourse community 177, 273, 307, 319–320, 322
- discourse functions 68, 178, 180, 213, 227, 229–233, 235–236, 245–246
- discourse organizers117
- ditransitive 33–35, 37, 40–43, 45–46, 51, 53–54
E
- English as a Lingua Franca (ELF) 59–64, 66–67, 71–79
- English for Academic Purposes (EAP) 79, 138, 142, 165, 224, 256, 259, 264, 271, 276, 333, 335–336, 338
- English for Specific Purposes (ESP) 6, 139, 256
- ESP
- evidentials 92, 94
- Exploratory Factor Analysis (EFA) 99, 149
F
- Factor Analysis (FA) 99, 140–141, 307, 311–312, 339–340, 343
- factor loadings 104, 312–313
- form-function mapping289
G
- genre analysis 281–282, 284, 297, 311
- genre-based pedagogy162
I
- IMRD (Introduction Method Results Discussion) 16, 119, 121, 138, 140–143, 162, 211
- informational density 79, 151–153, 160–161, 308
- inter-collocation 336–337, 343
- ISURA (Iowa State University Research Article) corpus 142–143, 145–147, 163
K
- keywords 94, 98–100, 104, 114, 140, 342
L
- lexical bundles
11, 66, 115, 123, 171, 230
see also participant-oriented bundles
117, 123
- referential bundles117
- research-oriented bundles 117, 120, 123–129
- text-oriented bundles 117, 120, 123–124, 126–130
- lexical overlap 94, 98, 100, 104, 108, 114
M
- MICUSP (Michigan Corpus of Upper-level Student Papers) 38–50, 120–121, 255, 257, 259–265, 270–273, 277–278
- modal verb 148, 164, 256, 260, 265–266, 268, 271–272, 277
- move analysis 137–139, 141, 163, 284–285, 295
- MRA (Medical Research Articles) corpus 116, 119–120, 122–124, 127
- MSRP (Medical Student Research Papers) corpus 120–124, 127, 129
- multi-dimensional (MD) analysis 1, 89, 93–94, 99–100, 107, 137–138, 140–141, 146, 152, 162–165, 307–309, 322, 333, 337–341
- multi-disciplinary 169–170, 178, 255
- multiple correspondence analysis164
N
- narrative 38, 48–49, 97, 100–101, 105–106, 308, 310, 319, 324–327
- nominal density 153, 162, 165
- normalized entropy79
O
- ORA (Other Research Articles) corpus 122–123, 127, 129
- OSP (Other Student Papers) corpus 121–124, 127, 129
P
- phrasal verb 34, 43–44
- phrase-frame 66, 69, 72, 74, 79, 235
- Principal Component Analysis (PCA) 149, 164, 311
- productive frame 175–176
- Promax rotation 99, 311
- pronominality 33, 35, 40, 45, 47
R
- reporting verb 89, 91–92, 94, 97–98, 100, 106, 108, 110, 114
- Research Writing Tutor 143, 165
- rhetorical analysis 91, 283, 297
S
- semantic class 35–36, 40, 48–51, 141
- semantic overlap 94, 98, 100–102, 104–105
- source-based writing 89–92, 94, 103, 106, 108–110
- stance 93, 117, 148, 150–152, 159, 161, 236, 240–241, 245, 255–259, 262, 267, 270–271, 273, 313, 316–319, 327–328
T
- Tagcount148
- to-dative 34–35, 37, 40–43, 51, 53
- type-token ratio (TTR) 43–44, 235, 237–238, 245, 250–254
W
- WRELFA (Written English as a Lingua Franca in Academic Settings) 64–65, 67–80
Y
- YELC (Yonsei English Learner Corpus) 37–53
