1.1Popular intensifiers across time (from Reference Tagliamonte and RobertsTagliamonte and Roberts 2005: 282, based on Reference MustanojaMustanoja 1960)

3.1Scalar (Reference Quirk, Greenbaum, Leech and SvartvikQuirk et al. 1985) versus boundedness (Reference ParadisParadis 2008) models

4.1Facsimile from Old Bailey Online

4.2aExample of proceeding from the searchable edition of Old Bailey Online

4.2bExcerpt of XML-annotated Old Bailey Corpus file, with utterance marked off within <u>…</u> tags

4.2cScreenshot of part of concordance in the OBC2Conc tool (Reference NisselNissel 2016)

4.3Diachronic distribution of the full inventory of intensifiers across the period studied (1720–1913) per 100,000 words

4.4Diachronic distribution of the intensifier categories across the period studied (1720–1913), frequencies normalized per 100,000 words

4.5Distribution of the ten most frequent intensifiers per 100,000 words. Raw frequencies and the proportion of a type among all intensifiers are listed in the right margin

4.6Distribution of top six intensifiers in the Old Bailey Corpus, by subperiod (frequencies normalized per 100,000 words)

4.7Zero-form proportions of wide(ly), great(ly), other boosters with zero form, maximizer zero forms, and downtoner zero forms, among all occurrences of each item or category

4.8Gender and role of the 129,176 speakers annotated for gender and role

4.9Gender and class of the 79,653 speakers annotated for gender and class

4.10aBoosters and maximizers by gender across subperiods, and the average of all speakers annotated for gender (frequency-labelled, broken line); frequencies per 100,000 words

4.10bDowntoners by gender across subperiods, and the average of all speakers annotated for gender (frequency-labelled, broken line); frequencies per 100,000 words

4.11aBoosters and maximizers per social class across subperiods, and the average of all speakers annotated for social class (frequency-labelled, broken line); frequencies per 100,000 words

4.11bDowntoners per social class across subperiods, and the average of all speakers annotated for social class (frequency-labelled, broken line); frequencies per 100,000 words

5.1Distribution of the maximizers per 100,000 words, shown as bars. Raw frequencies and the proportion of a type among all maximizers are listed in the right margin

5.2Distribution of the seven most frequent maximizers across the period studied (1720–1913) in normalized frequencies per 100,000 words

5.3Diachronic distribution of the seven most frequent maximizers in our Old Bailey Corpus data that are also found in Reference Hessner and GawlitzekHessner and Gawlitzek’s (2017) study of BNC2014S (normalized frequencies)

5.4The top seven Old Bailey Corpus maximizers and their occurrence in the British National Corpus trials

5.5Proportion of zero form for dual-form maximizers

5.6Semantic input domains of maximizers

5.7Maximizers by target of modification; proportional distribution of target categories

5.8Syntactic distribution of 200 adjectives modified by the top five maximizers

5.9Semantic classes of maximized adjectives (based on Reference DixonDixon 1977, Reference Beal2004); proportional distribution

5.10Semantic process types of maximized verbs/verb phrases (based on Reference Halliday and ChristianHalliday and Matthiessen 2004); proportional distribution

6.1aDistribution of the boosters per 100,000 words. Raw frequencies and the proportion of a type among all boosters are listed in the right margin

6.1bDistribution of the infrequent boosters per 100,000 words. Raw frequencies and the proportion of a type among all boosters are listed in the right margin

6.2The top five Old Bailey Corpus boosters and their occurrence in the British National Corpus trials

6.3Proportion of zero form for dual-form boosters

6.4Semantic input domains of boosters

6.5Boosters by target of modification (proportions). This includes approximate proportions for very and so, extrapolated from classified samples of 10 per cent each

6.6Syntactic distribution of adjectives modified by the top five boosters (for each booster except greatly pertaining to a random sample of 200 adjectives)

6.7Semantic classes of boosted adjectives (based on Reference DixonDixon 1977, Reference Dixon, Dixon and Alexandra2004); proportional distribution. This includes approximative proportions for very and so, extrapolated from classified samples of 10 per cent each

6.8Semantic process types of boosted verbs/verb phrases (based on Reference Halliday and ChristianHalliday and Matthiessen 2004); proportional distribution

7.1Intensifiers per 100,000 words in the Old Bailey Corpus, by category

7.2Distribution of the downtoners per 100,000 words, shown as bars. Raw frequencies and the proportion of a type among all downtoners are listed in the right margin

7.3Distribution of the five most frequent downtoners across the period studied (1720–1913) in normalized frequencies per 100,000 words

7.4Diachronic distribution of the four downtoners in our Old Bailey Corpus data that are also found in Reference Hessner and GawlitzekHessner and Gawlitzek’s (2017) study of BNC2014S (normalized frequencies)

7.5The top five Old Bailey Corpus downtoners and their occurrence in the British National Corpus trials

7.6Downtoners by semantic category (normalized frequencies)

7.7Semantic input domains of downtoners

7.8Downtoners by target of modification; proportional distribution of target categories

7.9Semantic process types of downtoned verbs/verb phrases (based on Reference Halliday and ChristianHalliday and Matthiessen 2004); proportional distribution

7.10Syntactic distribution of adjectives modified by the top five downtoners (for a little pertaining to a random sample of 200 adjectives)

7.11Semantic classes of downtoned adjectives (based on Reference DixonDixon 1977, Reference Dixon, Dixon and Alexandra2004); proportional distribution

8.1Intensifiers: diachronic, pragmatic, and sociolinguistic patterns in their estimated usage rate. Each pane shows for a given predictor model-based rate estimates (per 100,000 words), statistically controlling for the other predictors in the model

8.2Maximizers: diachronic, pragmatic, and sociolinguistic patterns in their estimated usage rate. Each pane shows for a given predictor model-based rate estimates (per 100,000 words), statistically controlling for the other predictors in the model

8.3Boosters: diachronic, pragmatic, and sociolinguistic patterns in their estimated usage rate. Each pane shows for a given predictor model-based rate estimates (per 100,000 words), statistically controlling for the other predictors in the model

8.4Downtoners: diachronic, pragmatic, and sociolinguistic patterns in their estimated usage rate. Each pane shows for a given predictor model-based rate estimates (per 100,000 words), statistically controlling for the other predictors in the model

9.1Scribes’ average normalized frequency of intensifiers across their working years (per 100,000 words). The broken line reflects the average of the full inventory of intensifiers for subperiods 1720–59, 1760–99, 1800–39, 1840–79 and 1880–1913 (per 100,000 words)

10.1Model-based estimated rates of intensifiers of different categories (per 100,000 words) by speakers of different roles in the courtroom

11.1Model-based estimated rates of intensifiers of different categories (per 100,000 words) by speakers of different roles in the courtroom

11.2Model-based estimated rates of intensifiers of different categories (per 100,000 words) by speakers of different social classes

C1Very: diachronic and sociopragmatic patterns in its estimated usage rate

C2Boosters without very: diachronic and sociopragmatic patterns in their estimated usage rate

C3Intensifiers without very: diachronic and sociopragmatic patterns in their estimated usage rate

D1A little: diachronic and sociopragmatic patterns in its estimated usage rate

D2Downtoners without a little: diachronic and sociopragmatic patterns in their estimated usage rate

E1Diminishers: diachronic and sociopragmatic patterns in their estimated usage rate

E2Minimizers: diachronic and sociopragmatic patterns in their estimated usage rate