Acknowledgements |
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1 | (32) |
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1 Studying writing development with a corpus |
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3 | (12) |
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3 | (1) |
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1.2 Using a corpus to study writing development |
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4 | (7) |
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1.3 How does writing development relate to vocabulary, grammar, formulaic language? |
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11 | (1) |
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12 | (3) |
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13 | (1) |
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13 | (2) |
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2 Learner corpus analysis in practice: some basics |
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15 | (18) |
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15 | (1) |
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2.2 Some housekeeping: getting your computer ready |
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16 | (1) |
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2.3 Getting to know R and RStudio |
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16 | (7) |
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2.3.1 Introduction: why learn R? |
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16 | (2) |
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2.3.2 Entering commands: the Console and Scripts |
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18 | (2) |
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20 | (1) |
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21 | (1) |
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22 | (1) |
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2.4 Some fundamentals of corpus research: encoding, markup, annotation, and metadata |
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23 | (4) |
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2.5 Corpora used in this book |
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27 | (1) |
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2.6 Automatically annotating your corpus for part of speech and syntactic relationships |
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27 | (3) |
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27 | (1) |
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2.6.2 Make sure you have the required software |
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28 | (1) |
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2.6.3 Prepare the corpus for parsing |
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28 | (1) |
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2.6.4 Make a list of the files you want to process |
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28 | (1) |
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2.6.5 Run the CoreNLP pipeline |
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29 | (1) |
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30 | (1) |
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31 | (2) |
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31 | (1) |
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31 | (2) |
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Part Two Studying vocabulary in writing development |
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33 | (60) |
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3 Understanding vocabulary in learner writing |
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35 | (24) |
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35 | (1) |
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3.2 Theorizing development in vocabulary |
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35 | (2) |
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35 | (1) |
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3.2.2 Breadth, depth, and fluency |
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36 | (1) |
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3.2.3 Aspects of word knowledge |
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36 | (1) |
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3.3 Measures of vocabulary development |
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37 | (7) |
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37 | (1) |
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37 | (2) |
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3.3.3 Lexical sophistication |
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39 | (1) |
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39 | (1) |
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40 | (1) |
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3.3.3 Register-based measures |
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41 | (1) |
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3.3.3 Contextual distinctiveness |
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42 | (1) |
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43 | (1) |
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3.3.3 Psycholinguistic measures |
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44 | (1) |
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44 | (9) |
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44 | (1) |
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44 | (1) |
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44 | (1) |
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3.4.2 Defining word tokens |
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45 | (1) |
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3.4.2 Defining word types |
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46 | (3) |
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3.4.3 Choosing a suitable reference corpus |
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49 | (2) |
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3.4.4 Relationships between measures of diversity and sophistication |
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51 | (2) |
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3.4.5 Vocabulary knowledge depth |
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53 | (1) |
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53 | (1) |
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54 | (5) |
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54 | (1) |
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54 | (5) |
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4 Vocabulary research in practice: diversity and academic vocabulary |
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59 | (34) |
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59 | (1) |
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4.2 Measuring vocabulary diversity |
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60 | (14) |
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4.2.1 Getting the metadata and corpus fdenames |
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60 | (2) |
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4.2.2 Generating CTTR scores |
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62 | (8) |
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4.2.3 Recording the results |
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70 | (1) |
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4.2.4 Analyzing vocabulary diversity |
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70 | (4) |
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4.3 Studying academic vocabulary |
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74 | (15) |
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4.3.1 Preparing the list of academic vocabulary |
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75 | (1) |
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4.3.2 Converting the parsed corpus to an easier-to-use format |
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76 | (4) |
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4.3.3 Identifying AVL words in the learner corpus |
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80 | (5) |
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4.3.4 Visualizing variation in measures |
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85 | (2) |
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4.3.5 Investigating the patterns |
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87 | (2) |
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89 | (4) |
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90 | (1) |
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90 | (3) |
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Part Three Studying grammar in writing development |
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93 | (44) |
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5 Understanding grammar in learner writing |
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95 | (18) |
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95 | (1) |
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5.2 Studying development through grammar |
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96 | (3) |
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96 | (1) |
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5.2.2 Selecting and interpreting grammatical features |
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97 | (2) |
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5.3 Approaches to grammatical development |
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99 | (9) |
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5.3.1 Varieties of grammatical approaches |
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99 | (1) |
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5.3.2 Development in grammatical complexity |
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99 | (2) |
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5.3.3 Multi-dimensional analysis |
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101 | (4) |
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5.3.4 Usage-based models of development |
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105 | (3) |
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108 | (1) |
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109 | (4) |
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109 | (1) |
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110 | (3) |
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6 Grammar research in practice: evaluating parser accuracy |
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113 | (24) |
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113 | (1) |
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6.2 Reading a parsed corpus |
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113 | (2) |
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6.3 Accuracy evaluation and fixtagging: an introduction |
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115 | (3) |
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6.4 Accuracy evaluation and fixtagging: a worked example |
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118 | (13) |
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6.4.1 Hand-annotating a sample of texts |
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118 | (1) |
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6.4.2 Getting metadata and filenames |
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119 | (1) |
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6.4.3 Identifying and counting adjectives |
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120 | (3) |
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6.4.4 Identifying true positives, false positives, and false negatives |
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123 | (2) |
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6.4.5 Calculating precision and recall |
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125 | (1) |
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6.4.6 Identifying matches and differences in hand vs. computer parses |
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126 | (2) |
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6.4.7 Identifying and fixing parsing errors |
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128 | (3) |
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6.5 Tracing development in a grammatical feature |
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131 | (3) |
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6.5.1 Counting a feature in texts |
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132 | (1) |
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6.5.2 Visualizing variation across learner groups |
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133 | (1) |
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134 | (3) |
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135 | (1) |
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135 | (2) |
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Part Four Studying formulaic language in writing development |
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137 | (44) |
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7 Understanding formulaic language in learner writing |
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139 | (18) |
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139 | (1) |
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7.2 Defining formulaic language |
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140 | (2) |
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7.3 How can we study formulaic language in a corpus? |
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142 | (6) |
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7.3.1 A frequency-based approach to studying formulaic language |
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142 | (2) |
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144 | (4) |
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148 | (5) |
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153 | (1) |
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153 | (4) |
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154 | (3) |
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8 Formulaic language research in practice: academic collocations |
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157 | (24) |
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157 | (1) |
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8.2 Identifying collocations in a reference corpus |
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157 | (16) |
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8.2.1 Editing the parsed corpus |
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157 | (4) |
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8.2.2 Identifying lemmas and verb + noun combinations |
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161 | (7) |
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8.2.3 Identifying collocations |
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168 | (5) |
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8.3 Quantifying the use of academic collocations across learner groups |
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173 | (6) |
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8.3.1 Preparing the learner corpus |
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174 | (1) |
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8.3.2 Identifying academic collocations in the learner corpus |
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174 | (3) |
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8.3.3 Understanding the use of academic collocations across levels |
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177 | (2) |
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179 | (2) |
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180 | (1) |
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180 | (1) |
Index |
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181 | (2) |
Index of R junctions and concepts |
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183 | |