1 Introduction
There is a wealth of analyses of the English analytic causatives make, have and get (e.g. Palmer & Blandford Reference Palmer and Blandford1969; Shibatani Reference Shibatani1975; McCawley Reference McCawley1979; Hantson Reference Hantson1981; Goldsmith Reference Goldsmith, Testen, Mishra and Drogo1984; Haegeman Reference Haegeman1985; Gronemeyer Reference Gronemeyer1999; Fleisher Reference Fleisher, Edwards, Midtlyng, Sprague and Stensrud2008; Hilpert Reference Hilpert2008), while other causatives, such as bring and force, have received far less attention (see, however, Andersson Reference Andersson1985; Stefanowitsch Reference Stefanowitsch2001; Callies Reference Callies, Aarts, Close, Leech and Wallis2013; Healey Reference Healey2013; Mondorf & Schneider Reference Mondorf and Schneider2016; Schneider Reference Schneider2021). Furthermore, few studies have investigated how these constructions have changed diachronically (notable exceptions being Hundt Reference Hundt2001 and Hollmann Reference Hollmann2003). The present study attempts to (partially) fill these gaps by looking at reflexive causation expressed with the verbs bring, cause, force and make, as illustrated in (1) to (4). It aims to determine whether these vary systematically and whether the factors determining this variation have changed over time.
(1) Yet for all this could she not bring herself to believe him absolutely false […]. (ECF1: E. F. Haywood, Jemmy and Jenny Jessamy 1753)
(2) But, Jack, if you cause yourself to be contemptible---; (NCF2: George Meredith, Evan Harrington 1861)
(3) Can I force myself in any manner to believe that I shall ever cease to love you? (NCF2: George Gissing, New Grub Street 1891)
(4) I made myself believe we shared a cause. (BNC, wridom 1)
Previous variationist approaches have primarily focused on variation between structurally different causatives, such as between analytic and synthetic causatives in English, see (5) and (6) (e.g. Shibatani Reference Shibatani1975: 53–4, 62–3; Dixon Reference Dixon, Dixon and Aikhenvald2000; Levshina Reference Levshina2017). These studies indicate that a speaker's choice of causative is determined, among others, by the degree of involvement and the volitionality of the causer as well as the affectedness of the causee.
Most of the proposed predictors of variation are encompassed by Hopper & Thompson's (Reference Hopper and Thompson1980) concept of transitivity, which will therefore be applied in the present study to gauge the (potential) dividing lines between different constructions. Hopper & Thompson's (Reference Hopper and Thompson1980) view of transitivity deviates from the traditional count of objects. They define transitivity as a cline which describes ‘the effectiveness or intensity with which the action is transferred from one participant to another’ (Hopper & Thompson Reference Hopper and Thompson1980: 252). This is measurable with the help of a range of properties of the verb and its arguments. When constructions lose their ability to describe effective transfer, this can be observed in a shift from high-transitivity to low-transitivity properties.
The development of the causative bring + to-infinitive construction (referred to hereafter as bring CI) is a case in point. It has repeatedly been shown that twentieth-century uses of bring CI are largely restricted to contexts in which the causee is a reflexive pronoun (cf. Andersson Reference Andersson1985; Mair Reference Mair1990a, Reference Mair1990b; Stefanowitsch Reference Stefanowitsch2001). Diachronic analyses by Mondorf & Schneider (Reference Mondorf and Schneider2016) demonstrate that twentieth-century bring CI is even more restricted: 65 per cent of tokens found in novels are modal and negated in addition to being reflexive, such as (1). Yet, in the sixteenth and seventeenth centuries, bring CI was typically non-modal, affirmative, active and non-reflexive. Thus the construction has undergone a set of transitivity-reducing shifts. This retreat to a narrow niche is coupled with a steady decline in frequency. bring CI plummeted from 31 uses per million words in the sixteenth and seventeenth centuries to only 10 uses per million words in the twentieth century.
Schneider (Reference Schneider2021) takes a wider perspective, looking at all uses of bring, whether as a transport verb or as a causative, and provides evidence that bring CI's diachronic specialization to reflexives reduces overlap in usage patterns between different bring-constructions. My findings indicate strongly that the sequence bring + reflexive pronoun cues the listener to recognise the comparatively rare bring CI construction. The emerging additional propensity of bring CI to co-occur with modals and negation renders the construction even more strongly marked – both morphosyntactically and semantically – and thus strengthens the cue. Such mechanisms to reduce the amount of functional or formal overlap between constructions have been argued to facilitate cognitive access to the construction most appropriate for a given situation, which, in turn, reduces processing cost and have therefore been termed ‘support strategies’ (cf. Mondorf & Pérez-Guerra Reference Mondorf and Pérez-Guerra2016).
The present article offers a third perspective on the phenomenon, focusing on variation between bring CI and other analytic causatives. It explores whether the retreat of bring CI to lower-transitivity contexts results from a similar reduction in functional overlap between causative constructions. This raises the more general question whether each reflexive causative has a distinct transitivity profile and, if so, whether these profiles have changed or shifted over time. To this purpose, I investigate reflexive uses of analytic causatives over the course of the Early Modern and Late Modern English periods (EModE and LModE respectively).
The third research question addressed by this article concerns variation between bare and to-infinitives, which is assumed to be iconic. Less formal distance (i.e. the absence of to) is thought to stand for ‘a higher degree of integration of the causing and caused events’ (Levshina Reference Levshina2017: 323; see Haiman's Reference Haiman1983 ‘distance principle’). This raises the question whether make – the only causative in the set which takes a bare infinitive as a complement – expresses more direct causation and consequently more effective transfer of action, i.e. whether it displays higher transitivity than the constructions with bring, cause and force.
The analysis is restricted to reflexive uses of the causatives. In the case of these verbs, reflexivity is semantically marked in the sense that the action denoted by the verbs is not generally self-directed (cf. Peitsara Reference Peitsara, Rissanen, Kytö and Heikkonen1997: 281) and reflexiveness therefore needs to be explicitly expressed with the help of a reflexive pronoun which fills the object slot (cf. Lyons Reference Lyons1968: 363; Quirk et al. Reference Quirk, Greenbaum, Leech and Svartvik1985: 358). These types of reflexives are also known as ‘argument reflexives’ (cf. Steinbach Reference Steinbach2002: 177–8).
The reflexive restriction was opted for, firstly, because of the leading role reflexives play in the diachronic development of bring CI; secondly, because of the added benefit of keeping several transitivity parameters stable: causer and causee are the same entity and thus equally agentive; they are animate (mostly human) and causation typically happens volitionally. This means that the reflexive controls for a variety of factors (for further invariant factors, see section 3), which permits a clearer focus on the influence of others, such as modality, negation, person and number. Thirdly, the reflexive limits the number of verbs which need to be considered. Causative have and get – which are commonly contrasted with make – are (nearly) incompatible with the reflexive.Footnote 1
I take a usage-based construction grammar approach to the analysis of reflexive causatives. In this view, linguistic knowledge comes in the form of a network of form–meaning pairs, i.e. constructions, which range from schematic to specific (see e.g. Hilpert Reference Hilpert2014, Reference Hilpert2021). Reflexive causatives are not merely instantiations of causative constructions, but also of separate, albeit connected, reflexive (sub-)constructions, which are more specific than their non-reflexive ‘parents’, but have ‘inherited’ properties from them.
The network is shaped through usage. Repeated use of a construction in a specific context strengthens associations between the context and the construction (see e.g. Beckner et al. Reference Beckner, Blythe, Bybee, Christiansen, Croft, Ellis, Holland, Ke, Larsen-Freeman and Schoeneman2009: 6–7 and sources therein; Bybee Reference Bybee2010: 30–1). In this way, the reflexive constructions may develop specific properties of their own (see e.g. Goldberg Reference Goldberg1995: 72–4; Hilpert Reference Hilpert2014: 57–8).
This approach brings several benefits. Not only can it model both the similarities and the differences between reflexive and non-reflexive uses of a causative, but also the competition between different causatives – which arises because the same meaning is connected to at least two different forms in the network. A final benefit it adds to the analysis is its ability to model diachronic change. The same feedback mechanisms which strengthen the association between a meaning and the form used to express it, also weaken the association between that meaning and competing forms which could have been selected to express it. Over time, this can lead to semantic differentiation (see e.g. Hilpert Reference Hilpert2021: 175). A distinct transitivity profile would thus be a context which has characteristic high or low transitivity properties and which is more strongly linked to one causative which, in turn, is preferred over the others.
The rest of the article is structured as follows. Section 2 introduces the parameters which Hopper & Thompson (Reference Hopper and Thompson1980) propose as measures of transitivity and discusses how these have been linked to causative variation. It then summarises what we know so far about the potential transitivity profiles of the causatives bring CI, make CI, force CI and cause CI. Section 3 provides a brief introduction to the Chadwyck-Healey corpora of British fiction covering the EModE and LModE periods and explains how the corpora were searched for reflexive causatives. The section furthermore provides information about data coding as well as the method of analysis. It is followed by a three-step analysis of the data in section 4, which consists of an account of diachronic changes in the frequency of the constructions as well as a multivariate analysis of variation based on CART trees and random forests and finally a comparative analysis of transitivity profiles. Section 5 summarises the results and discusses the function of transitivity in constructional networks as well as the role of reflexive causation in narrative storytelling.
2 Transitivity and analytic causatives
The following section introduces Hopper & Thompson's (Reference Hopper and Thompson1980) parameters of transitivity before briefly showing how they have been linked to causative variation. This is followed by summaries of the analytic causatives’ transitivity profiles.
2.1 Scalar transitivity
As mentioned above, Hopper & Thompson (Reference Hopper and Thompson1980: 252) define transitivity as ‘the effectiveness or intensity with which the action is transferred from one participant to another’. This intensity is determined with the help of the ten parameters listed in table 1.
Table 1. Parameters of transitivity (based on Hopper & Thompson Reference Hopper and Thompson1980: 251–3)
The highest degree of transitivity, i.e. ‘cardinal transitivity’ (Hopper & Thompson Reference Hopper and Thompson1980: 253), is given in cases where we have two participants: a volitional, human agent who is performing a telic, punctual action upon a single, concrete, human patient, the latter being physically affected, such as in (7).
(7) I punched Felix.
Cardinal transitivity has come to be equated with prototypical transitivity (cf. e.g. Taylor Reference Taylor1995: 206; Givón Reference Givón2001: 93; Næss Reference Næss2007: 15; Gilquin Reference Gilquin2010: 146–7). It is closely paralleled by the top rung in Cole's (Reference Cole1983: 131) ‘Hierarchy of Agency’, by Givón's (Reference Givón1984: 96–7) definition of ‘prototypical transitive verbs’, by Lakoff's (Reference Lakoff1987: 54–5) description of ‘prototypical causation’ as well as by a ‘Proto-Agent’ acting upon a ‘Proto-Patient’ in Dowty's (Reference Dowty1991: 572) terminology. The low-transitivity end of the scale, in turn, is linked to Givón's (Reference Givón2001: 93–4) ‘de-transitive voice’.
The present study tests Hopper & Thompson's (Reference Hopper and Thompson1980: 279) claim that ‘diachronic processes may be understood more clearly in terms of Transitivity’. More specifically, it explores the question whether, over time, the semantically (near-)equivalent analytic causatives have developed distinct transitivity profiles.
A similar claim has been made concerning the variation between structurally different causatives. Dixon (Reference Dixon, Dixon and Aikhenvald2000: 61–2, 74), for instance, argues that if a language has several causatives which differ in their degree of compactness, as illustrated by (8a–d) (ordered from least to most compact), a speaker's choice in a given context is predictable from at least one of the parameters listed in table 2.
(8)
(a) periphrastic/analytic, e.g. make s.o. walk
(b) complex predicate, e.g. French faire fondre ‘melttrans’
(c) morphological, e.g. productive processes of the kind in fall > fell
(d) lexical, e.g. walk (the dog); melt
Table 2. Semantic parameters determining the choice of causative (based on Dixon Reference Dixon, Dixon and Aikhenvald2000: 62)
The majority of these are, at least indirectly, included in Hopper & Thompson's (Reference Hopper and Thompson1980) list. Thus, Dixon's (Reference Dixon, Dixon and Aikhenvald2000) findings can be interpreted as evidence that the choice between causatives is transitivity-based. However, he links each split to only one parameter and, in some languages, it is the low-transitivity context which takes a more compact causative and in other languages it is the high-transitivity context.
More recently, Levshina (Reference Levshina2017) has shown that the choice between lexical and analytic causatives in English (see (8a, d)) is iconic and depends on the degree of involvement of the causer and affectedness of the object. If the effect of the causative is mental, as in (9), or another source of energy, such as the physical process in (10), is involved, i.e. if there is no transfer of energy or only a part of the required energy is supplied by the causer, speakers are more likely to select the longer analytic causative constructions compared to situations where the ‘[c]auser is the main energy source’ (Levshina Reference Levshina2017: 330), in which they prefer the shorter lexical constructions.
In summary, we have some evidence that transitivity parameters, such as agency and affectedness, can explain variation between structurally different causatives (cf. also arguments in Shibatani Reference Shibatani1975: 53–4, Reference Shibatani and Shibatani1976: 38; Degand Reference Degand2001: 176–7; Givón Reference Givón2001: 75; Halliday & Matthiessen Reference Halliday and Matthiessen2004: 509). The picture is a lot more complex where variation between structurally similar analytic causatives is concerned, partially due to a lack of quantitative variationist analyses. The following sections provide short summaries of the causatives’ ‘transitivity profiles’ as they can be deduced from the literature.
2.2 Bring
As discussed in section 1, causative bring + to-infinitive (bring CI) has come to be largely restricted to self-causation (cf. Andersson Reference Andersson1985; Mair Reference Mair1990a, Reference Mair1990b; Stefanowitsch Reference Stefanowitsch2001; Mondorf & Schneider Reference Mondorf and Schneider2016; Schneider Reference Schneider2021). In these reflexive contexts, there are two syntactic participants, but only one referent (cf. Kemmer Reference Kemmer1993: 65–6, 133; Stefanowitsch Reference Stefanowitsch2001: 246; Gilquin Reference Gilquin2010: 85). This means that the criterion of ‘two or more participants’ is not fully met, which lowers transitivity (see also Givón Reference Givón2001: 94–6).
Furthermore, 89 per cent of Present-Day English (PDE) tokens of the construction contain a modal and 72 per cent are negated (cf. Mondorf & Schneider Reference Mondorf and Schneider2016: 452–4). This means that in the case of modern-day uses of bring CI, mostly no effective transfer takes place as the verb phrase is either irrealis or negated. In fact, 65 per cent of twentieth-century tokens combine the three transitivity-lowering features modal, negation and a reflexive. bring CI has thus retreated to a narrow niche characterised by low-transitivity properties.
2.3 Make
As we saw earlier, the bare infinitive is said to indicate situations where causation and effect happen in close succession (cf. Haiman Reference Haiman1983: 781; Givón Reference Givón2001: 44; Fischer et al. Reference Fischer, De Smet and van der Wurff2017: 169–70) or where the patient has little control (cf. Givón Reference Givón2001: 48; for links between these properties and causative make see Kemmer & Verhagen Reference Kemmer and Verhagen1994: 122; DeLancey Reference DeLancey1984: 183; Levshina Reference Levshina2017: 330; and critical discussion in Callies Reference Callies, Aarts, Close, Leech and Wallis2013: 242). And indeed, causative make CI has been associated with coercive causation, where the causee's will is overruled (cf. Shibatani Reference Shibatani1975: 46; Hantson Reference Hantson1981: 151; Goldsmith Reference Goldsmith, Testen, Mishra and Drogo1984: 122).
However, coercion is only one of several types of causation which can be expressed with make CI. The most common properties of PDE uses of make CI (inanimate causer, animate causee and non-volitional effect; Gilquin Reference Gilquin2010: 113, 128–30) are present in uses such as (11).
(11) The thought made her smile wryly. (BNC, wridom1)
In fact, the most distinctive feature of the construction seems to be its association with non-volitional effects, or, more specifically, its ‘strong bias towards verbs of emotion and psycho-physiological reaction’ (Hilpert Reference Hilpert2008: 491), such as laugh, feel, look and think (see also Gilquin Reference Gilquin2010: 103, 205; Reference Gilquin2015: 262–4).
Thus, the transitivity profile of PDE make CI is diverse. The dominant emotional and psycho-physiological effects do not require volitional causers who are high in potency and do not leave the causee totally physically affected. The causee, on the other hand, has been found to be predominantly definite and/or human and more frequently first or second person than in other causative constructions (cf. Hollmann Reference Hollmann2003: 156; Gilquin Reference Gilquin2010: 116–18), all of which are transitivity-raising factors. Additionally, effects can rarely be negated (?She made it not fall over; Mittwoch Reference Mittwoch1990: 114). Gilquin (Reference Gilquin2010: 134) concludes that make CI is ‘the most flexible construction, as it attracts the largest number of distinctive features’ (see also Dixon Reference Dixon, Dixon and Aikhenvald2000: 36–7 and Hollmann Reference Hollmann2003: 156).Footnote 2
Diachronic analyses show that until the middle of the twentieth century, the construction also permitted to-infinitives and, until the eighteenth century, an even longer for to variant (cf. Visser Reference Visser1973: 2261–2; Mittwoch Reference Mittwoch1990: 125; Hollmann Reference Hollmann2003: 166).
2.4 Force
Force + to-infinitive (force CI) is typically described as being used for situations in which a human, volitionally acting agent causes a human unwilling patient to perform an action (cf. Givón Reference Givón2001: 48; Stefanowitsch Reference Stefanowitsch2001: 151; Hollmann Reference Hollmann2003: 156). Each of these properties is associated with high transitivity. Yet not all uses of force CI are characterised by such highly transitive properties. Andersson (Reference Andersson1985: 85), for instance, finds that in PDE almost half the tokens of force CI are passives, which have a lowered transitivity as the causer is backgrounded or not expressed at all (cf. Givón Reference Givón2001: 94). Furthermore, Stefanowitsch (Reference Stefanowitsch2001: 153) argues that there is a subtype of the construction, which he terms the ‘force-causative of decision’, where the causer is merely an initial event and the causee performs the effect because they see no other option, as in (12).
(12) The Macintosh is about the only one that's going right, forcing IBM and the rest of the DOS world to follow along. (Stefanowitsch Reference Stefanowitsch2001: 153, my emphasis)
Overall, inanimate causers are common in the force CI construction (cf. Hollmann Reference Hollmann2003: 156). Due to their lower agency and lack of volitionality, these inanimate causers yield more control to the causee (see also syntactic arguments by Givón Reference Givón2001: 48) and consequently lower the transitivity.
While historically, force CI permitted both bare and to-infinitives (cf. Visser Reference Visser1973: 2279), the variant with to seems to have been dominant since EModE (cf. Hollmann Reference Hollmann2003: 167). Today, the variant with the bare infinitive has all but disappeared (cf. Callies Reference Callies, Aarts, Close, Leech and Wallis2013: 245).
2.5 Cause
Cause + to-infinitive (cause CI) has been termed ‘most dissimilar to the others’ (Gilquin Reference Gilquin2010: 136; see also Shibatani Reference Shibatani and Shibatani1976: 38) and ‘the most abstract causative’ (Shibatani Reference Shibatani1975: 51; Stefanowitsch Reference Stefanowitsch2001: 162). It is formal and associated with academic writing (Hantson Reference Hantson1981: 152) and technical contexts (Gilquin Reference Gilquin2010: 173, 231). Therefore, it is no surprise that it takes almost exclusively transitivity-lowering inanimate causers, most of them generic and/or abstract entities, like states and events (cf. Hollmann Reference Hollmann2003: 156; Gilquin Reference Gilquin2010: 110–14). Causation is mostly physical but non-punctual and non-volitional (cf. Givón Reference Givón and Kimball1975: 62–70; Stefanowitsch Reference Stefanowitsch2001: 160; Gilquin Reference Gilquin2010: 120) and causees are commonly inanimate (cf. Givón 1974: 71; Gilquin Reference Gilquin2010: 118). Example (13) illustrates these properties.
(13) The infant's eye is elastic and so a raised intra-ocular pressure causes the eyeball to enlarge. (BNC; Gilquin Reference Gilquin2010: 117)
Furthermore, cause CI can encode very indirect causation with long causal chains. In fact, it is flexible and able to ‘encode any kind of causal link’ (Stefanowitsch Reference Stefanowitsch2001: 160, 175).
Historically, the bare infinitive was possible besides the (for) to variant (cf. Jespersen Reference Jespersen1927: 291; Visser Reference Visser1973: 2256), but even as early as ME it seems to have been rare or restricted to specific genres (cf. Hollmann Reference Hollmann2003: 166).
Thus we have seen that English analytic causatives have partially overlapping profiles, but each has several characteristic core functions. The following analysis will test whether the same is true for the subgroup of reflexive causatives.
3 Data and coding
3.1 Corpora and data retrieval
The present study is based on three of the Chadwyck-Healey collections of prose published in Great Britain between 1500 and 1899 (Early English Prose Fiction [EEPF; Klein, Margolies & Todd Reference Klein, Margolies and Todd1997–2015]; Eighteenth-Century Fiction [ECF; Hawley, Keymer & Mullan Reference Hawley, Keymer and Mullan1996–2015]; Nineteenth-Century Fiction [NCF; Karlin & Keymer Reference Karlin and Keymer1999–2000]). Data for the twentieth century is supplied by the fiction subcorpus (wridom1) of the British National Corpus (BNC; BNC Consortium/Oxford University Computing Services).Footnote 3 While works in the Chadwyck-Healey corpora are grouped by publication date, it has become customary to regroup works by authors’ birth dates as it can be assumed that a speaker's idiolect changes less over their lifetime than language itself changes in the same time (cf. e.g. Bailey et al. Reference Bailey, Wikle, Tillery and Sand1991). The resultant grouping is shown in table 3.
Table 3. Historical corpora
b period based on birth dates.
p period based on publication dates.
I used non-tagged plain-text versions of the corpora, as even taggers trained on historical data provide insufficient results, particularly when applied to EEPF (cf. Scherl Reference Scherl2019). Causative verbs were searched with WordSmith Tools version 5 (Scott Reference Scott2008). To account for historical variation, spelling variants listed in the Oxford English Dictionary (OED) online were taken into consideration. Searches specified that the verb had to be followed by *sel* at a maximum distance of three words to the right.Footnote 5 The distance was permitted in order to ensure that tokens with intervening adverbs (e.g. only myself) and those where the reflexive is spelled in two words (e.g. thy self) would not be missed. The former, however, never occurred.
All tokens were then manually sifted to make sure that the verb had a causative reading and that causation was self-directed. Additionally, the caused effect had to be expressed by an infinitive, such as in (1) to (4) in section 1. Any duplicates were deleted. After this step 1,434 tokens remained. Table 4 shows the distribution of the data by period and construction.
Table 4. Tokens per period
3.2 Coding
The restriction to reflexives keeps several transitivity parameters stable, for instance, only nine causer–causees are inanimate or abstract entities. Half of these (e.g. the heart, the Byzantine Empire) stand metonymically for human agents. Thus, there is no need to code for animacy. Overall, the following transitivity parameters are invariant in the data: number of participants, kinesis, aspect (telicity), agency (except for person; see below) and individuation of the object (except for number; see below). We can mostly assume that causation was volitionally initiated. The data was manually coded for the following further transitivity factors. Four of these pertain to what I will refer to as the causative clause (given in bold in (14)) while three relate to the second clause, i.e. the effect clause (underlined in (14)).
(14) He forced himself not to interrupt […]. (NCF2: Charlotte M. Yonge, The Heir of Redclyffe 1853)
Person, i.e. the grammatical person encoded by the reflexive pronoun. This factor was included as a measure of agency. Hopper & Thompson (Reference Hopper and Thompson1980: 273) draw on a ranking by Silverstein (Reference Silverstein, Muysken and van Riemsdijk1986 [1976]) and argue that from first to second and third person, agency decreases. The pronoun use in the data reflects the general distribution of pronouns in novels, where third-person pronouns are the most common, followed by first-person pronouns and then second-person pronouns (cf. Biber et al. Reference Biber, Johansson, Leech, Conrad and Finegan1999: 334).
Number, i.e. singular or plural. This factor was included as a measure of individuation. Singular patients are more individuated than plural patients (Hopper & Thompson Reference Hopper and Thompson1980: 253). Plurals turned out to be rare (71 out of 1,434 tokens; 5 per cent).
Modal. Hopper & Thompson's (Reference Hopper and Thompson1980: 273) parameter of mode (realis vs irrealis) is operationalised as the presence or absence of a modal verb in the causative clause. Any element on Quirk et al.'s (Reference Quirk, Greenbaum, Leech and Svartvik1985: 137) modal gradient, except the main verbs themselves, was coded as ‘modal’. This means that the modal category contains central modals, marginal modals (e.g. ought to), modal idioms (e.g. be to), semi-auxiliaries (e.g. be able to) and catenatives (e.g. seem to). The category is much less diverse than it may appear. The central modals dominate (530 out of 581 modal tokens are central modals); could (n = 378) and can (n = 97) are the most common, followed at quite some distance by the semi-auxiliaries have to (n = 21) and be (un)able to (n = 20).
Negation. This includes the following forms of negation in the causative clause:
Negation in the verb phrase – not, never, nor, without
Negation of the subject noun phrase – e.g. neither X nor Y, nobody
Negation by means of adverbials – e.g. by no effort
Negation of marginal modals, modal idioms, semi-auxiliaries and catenatives – e.g. not able to etc. This exception to the general principle of only counting negation in the causative clause had to be made in order to treat all modals equally even though some appear in a superordinate clause.
Negation of the Effect Clause, such as in (14) above. Due to the effect clause being non-finite, only verb phrase negation with not or never occurred.
Voice of the Effect Clause. While the reflexive rules out the passive in the causative clause, both active and passive are possible in the effect clause. In the case of a passive effect, the agent causes an unnamed third participant to perform an action on them, as in (15). This means the agent of the causative clause only indirectly causes an effect on themselves; the causation chain is longer and transitivity is therefore reduced.
(15) One night I caused my self to be brought home by a Porter as dead drunk […] (EEPF: Richard Head, The English Rogue 1665)
Process Type of the Effect Clause. This factor gauges how strongly the agent/patient of the causative clause affects the patient of the effect clause. The classification scheme which was adopted for this purpose is Halliday & Matthiessen's (Reference Halliday and Matthiessen2004: 170–1) distinction between material (e.g. follow, curtsy), mental (e.g. hear, concentrate), relational (e.g. be, appear ‘seem’), behavioural (e.g. wake, stand, swallow), verbal (e.g. tell, whisper) and existential processes (not possible in these constructions). Fourteen tokens received no coding as the context provided insufficient information to assess the process type.
4 A comparison of causatives in British English fiction
4.1 Frequency changes
As frequency changes can be an indicator of semantic shifts, we will first compare the usage frequency of the four reflexive constructions over time. The left panel in figure 1 shows that three of the reflexive constructions have increased in frequency over the past 500 years. Yet the frequency changes happened at different points in time: uses of reflexive bring CI already rose steeply in the transition from EModE to LModE. Yet the even steeper increase in reflexive make CI and force CI only followed some 200 years later. Reflexive cause CI, in turn, was in decline, leading to its disappearance from novels by the twentieth century.
Figure 1. Relative frequency of the reflexive causatives as well as the relative frequency of reflexive and non-reflexive uses combinedFootnote 6
Overall, these changes lead to far more reflexive causatives being used in the twentieth century than in the centuries before (see cumulative relative frequencies at the top of the graph). This raises the question whether the increase in reflexive causatives is a reflection of a general increase in the use of analytic causatives. The right panel in figure 1 provides a tentative answer to this question. It shows the combined frequency of reflexive as well as non-reflexive uses of the four constructions under investigation. For force CI and bring CI, comparable non-reflexive data was retrieved with a string which specified that the verb had to be followed by to up to five words to the right (see also Mondorf & Schneider Reference Mondorf and Schneider2016: 447). Due to the multitude of other constructions that make and cause (as a noun) may appear in, such comparison sets could not easily be generated for these verbs. Therefore, frequencies of cause CI and make CI were obtained from Hollmann (Reference Hollmann2003: 171; sixteenth- and seventeenth-century data) and Gilquin (Reference Gilquin2010: 87; twentieth-century data). While Hollmann also uses prose corpora, Gilquin's (Reference Gilquin2010: 33) results are based on spoken language and academic texts and thus need to be compared with caution. The numbers in the margins indicate the share of reflexives.
A comparison of the two panels of figure 1 reveals that the rise in reflexive causatives runs counter to the general development. All four causatives have considerably declined in frequency since EModE. Only force CI is on the rise again. Yet the increase in reflexive uses of force CI is more pronounced than its overall increase in use, so that a quarter of present-day uses of force CI is reflexive, while in EModE only about 2 per cent of uses were reflexive.
In summary, reflexivity is an increasingly more common feature of the analytic causatives bring CI, force CI and make CI. Bring CI leads this change and at 94 per cent reflexive tokens is currently the causative most likely to be used reflexively. In absolute terms, however, by the twentieth century, it is outperformed by reflexive force CI, which by then is almost three times as frequent.
4.2 Reflexive causative variation
This leg of the analysis provides a more in-depth look at variation between reflexive analytic causatives. It determines whether specific (clusters of) factors determine authors’ choices. The results will help to determine whether each causative has a distinct transitivity profile.
The analysis poses two big challenges for statistics in that (a) we are dealing with a choice between more than two causatives and (b), as we will see below, some of the predictors are correlated. Therefore, I use a Classification and Regression Tree (CART tree; ctree from the party package in R, Hothorn et al. Reference Hothorn, Hornik and Zeileis2006) and later supplement it with random forests (cf. cforest, Hothorn et al. Reference Hothorn, Hornik and Zeileis2006; Strobl et al. Reference Strobl, Boulestreix, Kneib, Augustin and Zeileis2008). These algorithms ‘grow’ trees through recursive binary partitioning of the data, with the aim to create statistically purer ‘branches’, i.e. subgroups of the data (cf. Baayen Reference Baayen2008: 148–9; Strobl et al. Reference Strobl, Malley and Tutz2009). In contrast to other regression approaches, they can handle multinomial outcomes and complex interactions as well as collinear predictors (cf. Tagliamonte & Baayen Reference Tagliamonte and Baayen2012: 161, 171; Levshina Reference Levshina2015: 292). While CART trees rely on a single tree per dataset, random forests grow hundreds of trees using only a random selection of data points and predictors in each tree (cf. Strobl et al. Reference Strobl, Malley and Tutz2009: 15–16; Tagliamonte & Baayen Reference Tagliamonte and Baayen2012: 159).
Figure 2 shows the CART tree. All splits and the resulting terminal nodes (or ‘leaves’) are numbered and the predictor and splitting point are listed for each split. The bar graphs in the terminal nodes show the distribution of outcomes. The highest bar indicates the model's prediction for the leaf. To reduce the complexity of the model, the tree has been ‘pruned’, i.e. it has been prohibited from growing terminal leaves which contain fewer than fifty data points. This simplified the model but did not significantly decrease the number of correct predictions (based on a chi-square test comparing the numbers of correct and false predictions of the standard and pruned models).
Figure 2. CART tree predicting the choice between reflexive analytic causatives. Abbreviations of the dependent variable: b = reflexive bring CI; c = reflexive cause CI; f = reflexive force CI; m = reflexive make CI. Abbreviations of the factor clause type (of the effect clause): be = behavioural; mat = material; men = mental; re = relational; ve = verbal.
The model's overall prediction accuracy is 72.3 per cent. However, models fitted to datasets in which outcomes are very unequally distributed are best assessed by referring to ‘balanced accuracy’ instead (cf. Weihs & Buschfeld Reference Weihs and Buschfeld2021: 5). This is the non-weighted average rate of correct predictions across outcomes. As the four constructions are not equally frequent, this method will be applied to assess the performance of the model in figure 2. Prediction accuracies are 92.4 per cent, 92.3 per cent, 81.4 per cent and 15.5 per cent for bring CI, cause CI, force CI and make CI respectively. This leads to a balanced accuracy of 70.4 per cent, which highly significantly exceeds a 50/50 chance distribution of correct and false predictions (χ2=239.47, df = 1, p < 0.001; rates were converted to absolute numbers of correct and false predictions to fulfil chi-square requirements).
A great benefit of CART trees compared to other types of models is the graphical representation of the data. Figure 2 visualises under which conditions a construction is selected, thereby indicating the most influential predictors and interactions.
The first split in the tree basically separates reflexive cause CI from the other constructions. It creates terminal Node 2 in which cause CI is the predominant causative. The fact that all but three tokens of cause CI are confined to this node indicates that cause CI was restricted to passive effects, such as the one in (16).
(16) I did therefore cause my self to be carried hither; […]. (EEPF: Roger Boyle, Parthenissa 1669)
As noted in section 3.2 above, these kinds of effects are transitivity lowering as the agent of the causative clause does not directly bring about the effect. They constitute 22.2 per cent of the EModE data, but rapidly died out in LModE.
Besides cause CI, Node 2 contains 15 tokens of make CI. There seems to be a division of labour between the two verbs in that reflexive make CI is used with mental verbs in the passive, e.g. be heard, be known, be loved, while reflexive cause CI mostly combines with material verbs, particularly transport verbs, e.g. be carried, be conveyed, be lowered. Thus, patients of cause CI are more physically affected than those of make CI in this context. The tree does not indicate this division as the node is too small to split further.
The next split – at Node 3 – separates modal from non-modal uses of the causatives. It reveals that modal contexts are heavily associated with reflexive bring CI. The four modal Nodes, 16, 17 18 and 19, are all predominantly filled with tokens of bring CI. Successive splits by clause type and negation mean that from right to left these nodes are ever more severely restricted, i.e. they show more complex interactions. At the same time, the level of noise decreases from 42 per cent in Node 19 to 0 per cent in Node 16. The latter represents the threefold interaction of modal–negation–verbal effect and it indicates that in these specific circumstances, authors invariably choose bring CI and that they have done so for the entire LModE period (Node 16 contains only a single EModE token). Examples (17) and (18) are exemplary tokens from this node.
(17) For he was not able to bring himself to utter those few plain words, “Indeed, madam, I cannot tell.” (ECF2: Sarah Fielding, The Cry 1754)
(18) There are things I can't bring myself to confess just yet. (BNC, wridom1)
The final major branch of the tree is the non-modal one which branches to the left after Node 3. Its terminal nodes represent conditions under which speakers prefer to use reflexive make CI or force CI. Note that negation does not appear as a splitting criterion in this branch of the tree. This is due to negation being strongly attracted to modals and therefore mostly confined to the other branch (347 out of 362 tokens with negation occur in combination with a modal, i.e. 95.9 per cent).
Node 6 is the only terminal node in which make CI dominates. It contains non-modal pre-twentieth-century tokens with a relational effect. The most frequent relational verbs with make CI are appear and look, such as in appear foolish, look such a fright or look presentable. In the twentieth century, this context becomes one where newly frequent reflexive force CI takes over, which is evident when Node 6 and Node 7 are compared.Footnote 7 Force CI does not oust make CI, however, and hardly occurs with appear and look. Instead, it prefers copula be. In terms of their transitivity, relational effects, such as appear foolish, often resemble passive effects in that causation is more indirect. Many require a further unnamed participant who perceives the agent of the causative clause in a specific way, for instance as foolish (or at least they require the agent's impression of being perceived in a certain way by others); they are therefore often termed ‘stimulus subject perception verbs’.
Finally, Nodes 10 and 12 show under which conditions speakers strongly prefer reflexive force CI (73 per cent and 72.1 per cent respectively). In terms of transitivity, Node 10 ranks highest among all terminal nodes as it contains constructions which are realis, i.e. non-modal – and therefore hardly ever negated – in which the agent directly affects himself/herself and in which the performed action has at least some physical component.
Splits in a tree are only locally optimal, though, which means that the algorithm is unable to look ahead and consider effects further down the line. Consequently, a predictor which is marginally outperformed but may have ultimately helped to create less noisy terminal nodes may get overlooked. This issue is resolved in random forests, which generate an ensemble of trees, each based on random subsamples of data points and predictors. In this way, splits emerge that may not have been locally optimal had all predictors been considered (cf. Strobl et al. Reference Strobl, Malley and Tutz2009: 331–3). The prediction of the forest is then determined by vote (cf. Tagliamonte & Baayen Reference Tagliamonte and Baayen2012: 161).
Additionally, forests offer a more conservative estimate of model performance. As each tree is based on only a subset of the data and ignores the remainder, these ‘out-of-bag’ observations can be used for cross-validation, by testing whether the model's predictions can be generalized to unseen data (cf. Strobl et al. Reference Strobl, Malley and Tutz2009: 335, 341). Throughout this section, the random forest results given are out-of-bag observations.
For the present study, a separate forest of 1,000 trees was grown for each period to allow for a better assessment of diachronic change. The number of predictors considered per split was restricted to three. Cause CI had to be excluded from the models for the periods 1700–99 and 1800–69. In these periods, it makes up less than 3 per cent of the outcomes, which means that many of the subsamples on which the forests are trained would have contained few or no tokens of cause, giving the models little chance to learn when speakers use this causative (cf. Chen et al. Reference Chen, Liaw and Breiman2004: 2).Footnote 8 Forest performance is evaluated in the same way as the performance of CART trees, i.e. by means of balanced accuracy; see table 5. Yet, in contrast to single trees, forests cannot be visualised. Instead, the variable importance they assign each predictor can be graphically assessed. These importance scores serve to rank the performance of predictors in a model (cf. Strobl et al. Reference Strobl, Malley and Tutz2009: 336; Shih Reference Shih2011: 2). Through these rankings, the most important predictors can be determined and compared across models (cf. Strobl et al. Reference Strobl, Malley and Tutz2009: 336, 342).
Table 5. Forest performance
Table 5 shows that all forests perform significantly above chance, yet, like the individual tree, they have difficulties finding circumstances in which speakers prefer reflexive make CI. Figure 3 shows the corresponding variable importance scores. They largely confirm the results of the CART tree but add more nuance. Voice of the effect VP – one of the most powerful predictors in EModE – becomes irrelevant in LModE, i.e. once reflexive causeCI is lost or at least no longer in the models. The clause type of the caused effect stays relevant for longer but has lost importance by the twentieth century. For all three centuries of the LModE period, modal is ranked as the most powerful predictor. We now also see that negation affects causative choice (in each period, at least 84 per cent of negated tokens are ones with bring CI) and that the grammatical person of the causer/causee is influential in some models (bring CI attracts first-person pronouns more strongly than the other causatives; as a result, from the eighteenth century onwards, more than half of the tokens with a first-person pronoun in each period combine with bring CI). The final two factors, i.e. number and negation of the effect VP, have hardly any predictive power. These results will be discussed in section 5.
Figure 3. Variable importance scores
4.3 Correlations and configurations
As a last step, we can calculate transitivity scores in order to determine whether the constructions have distinct transitivity profiles. To do so, transitivity-raising features, such as [singular], are scored as 1; transitivity-lowering features, such as [plural], as −1. In the case of the variables person and clause type, which have three or more expressions, those between the extremes are considered neutral and scored as zero (i.e. [2nd person]; [verbal process] and [behavioural process]). As each token is annotated for seven variables, total scores between −7 (very low transitivity) and 7 (very high transitivity) are possible.
In the data, negative scores are rare (only 80 out of 1,434 tokens), and scores below −3 do not occur. Even this low is only reached four times. An example of a −3-rated token is given in (19). If we compare it to (20), which received a score of 7, it appears complex and harder to process.
(19) I know very well […] that Griefs too great don't make themselves at first to be perceived; and I know as well, that Violent Griefs don't continue long. (EEPF: Thomas Brown, Amusements Serious and Comical 1700)
[third person]-1 [plural]-1 [non-modal]+1 [negation]-1 [affirmed effect]+1 [passive effect]-1 [mental process]-1
(20) The shock delayed any panic and I forced myself to walk across to the body and look at the face. (BNC, wridom1)
[first person]+1 [singular]+1 [non-modal]+1 [affirmation]+1 [affirmed effect]+1 [active effect]+1 [material process]+1
Figure 4 shows mean transitivity scores per causative and period as well as 95 per cent confidence intervals. Reflexive bring CI ranks lowest with average scores not even reaching 2. Reflexive force CI, on the other hand, consistently receives average scores between 3.5 and 4 and is thus the most transitive construction of the set in the eighteenth and nineteenth centuries. Reflexive make CI initially receives similarly low scores as bring CI, yet over time scores rise and become increasingly similar to those of force CI. Overall, we see that reflexive bring CI has developed a low-transitivity profile, which begins to contrast with those of make CI and force CI by the nineteenth century.
Figure 4. Mean transitivity scores and 95 per cent confidence intervalsFootnote 9
5 Discussion and conclusion
The analyses have revealed typical usage patterns of the four reflexive analytic causatives: Reflexive cause CI was indeed ‘most dissimilar to the others’ (Gilquin Reference Gilquin2010: 136) as it was almost exclusively restricted to passive effects. As a consequence, the loss of the reflexive construction can be directly linked to the demise of passive effects as complements of analytic causatives when such effects became increasingly expressed with get (e.g. get oneself caught) from the eighteenth century onwards.
Reflexive force CI is characterised by its very strong focus on affirmative, non-modal uses. The analyses show that it has a comparatively high transitivity profile and, until the twentieth century, was thus the reflexive causative closest to prototypical transitivity.
Make CI is the only construction in the set which no longer takes the to-infinitive. The present study explored whether this shortening of the construction is iconic in the sense of make CI being used to express more direct causation than the other causatives. Results show that in reflexive contexts this is not the case. Firstly, like its non-reflexive parent construction, reflexive make CI is associated with stimulus subject perception verbs (e.g. appear foolish), which necessitate the involvement of an additional participant, i.e. the experiencer. This means the causation chain is long, indirect and not (totally) under the control of the causer. Additionally, reflexive make CI occurs in many other contexts and lacks a characteristic transitivity profile. Its profile in EModE resembled that of reflexive bring CI, but it has become more transitive over time and by the twentieth century resembles reflexive force CI.
Finally, the general attraction of bring CI to negated and modal contexts seems to have originated in reflexive contexts. From Mondorf & Schneider (Reference Mondorf and Schneider2016: 452–4) we learn that, in EModE, tokens of bring CI were typically still affirmed and non-modal. The present study shows that, in the same period, reflexive uses were already predominantly modal (compare 58 per cent and 39 per cent modal uses in reflexive and non-reflexive contexts respectively) and often at the same time negated (36 per cent versus 12 per cent). The data yields no indications of reflexive bring CI having been pushed out of the more highly transitive contexts by competing constructions. The large numbers of non-modal and affirmed tokens of reflexive make CI and force CI does not appear until the twentieth century, by which time reflexive bringCI is already firmly linked with modal and negated contexts.
The results allow for conclusions concerning the role of transitivity in constructional networks, i.e. they provide answers to the question whether competing constructions differentiate and develop distinct transitivity profiles. Variation between reflexive bring CI and reflexive force CI can be described as a transitivity-based split with reflexive force CI on average covering higher transitivity contexts than reflexive bring CI. Yet we also find splits which are not transitivity-based. Reflexive make CI never had a distinct transitivity profile and reflexive cause CI, while filling a unique niche, was both characterised by high transitivity (e.g. material effects) and low transitivity properties (e.g. passive effects). We would need further analyses to determine whether its retreat from reflexive causation with passive effects can be linked to more general developments of the construction. From the present data, we can conclude that some constructions have specialised transitivity profiles but not all do. Interestingly, the transitivity profiles of reflexive force CI and bring CI have been relatively stable over the past 500 years.
A few relations between the more abstract parents and the reflexive constructions warrant further comment. While particularly reflexive make CI seems to have inherited many properties of its parent construction, such as its strong focus on stimulus subject perception verbs as effects, bring CI seems to have actually influenced its parent – while it still had one. This is a possible interpretation of the early shift of reflexives towards modality and negation discussed above. And in light of the success of force CI as a reflexive causative in the twentieth century and the resulting increased proportion of force CI which is used reflexively (25 per cent), it will be interesting to see whether the reflexives also have an influence on the parent construction.
The results moreover permit some text-linguistic interpretations. Authors appear to avoid sentences which combine many transitivity-lowering properties, while sentences with many transitivity-raising features are being used. In the present case, however, cardinal transitivity cannot be reached as reflexives are inherently transitivity-lowering; all tokens thus fall within a moderate transitivity range. The absence of very low transitivity suggests that certain clusters of low transitivity properties may be rare and consequently stylistically marked. In conclusion, it may not only be the upper end of the transitivity spectrum is rare (cf. Thompson & Hopper Reference Thompson, Hopper, Bybee and Hopper2001: 27, 37) but also the lower one.
Furthermore, it transpired that twentieth-century novels contain far more reflexive analytic causatives than novels which predate them. The stylistic options offered by reflexive causatives may offer some explanation for this. They provide background on a character's inner struggles or their stance towards an action. This means that they give narrators the possibility to report a character's ‘subjective experiences’ (Verhagen Reference Verhagen, Barlow and Kemmer2000: 279), either in the first person as free direct thought and direct speech or in the third person as part of a free indirect style (cf. Rundquist Reference Rundquist2014). During an analysis of Dutch causatives, Verhagen notes that ‘this kind of subjectivity … has become very prominent in literary narrative especially since the rise of the modern novel’ (Verhagen Reference Verhagen, Barlow and Kemmer2000: 280). The increase in reflexive causation may therefore be seen as an indicator that changes in story telling are taking place, leading to reflexive causation playing a more central role in subjective narrative styles.
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