This paper uses large-scale data extracted from a series of Swedish corpora to investigate the factors responsible for conditioning the choice of (optional) embedded V2 in Swedish. Embedded V2 has been argued to represent a more general kind of syntactic optionality found across languages: syntactic structures typically found in matrix clauses, but which are also available in certain types of embedded environments (so called Main Clause Phenomena). While the received view, going back to Hooper & Thompson (
In this paper, we investigate a type of syntactic optionality found across languages: syntactic structures typically found in matrix clauses, but which are also available—although apparently not obligatory—in certain types of embedded environments. Since Hooper & Thompson (
Scandinavian EV2 raises a number of questions for the study of syntactic optionality. While previous work on EV2 has reported judgments pointing to potential semantic-pragmatic factors driving the choice of EV2 vs. V-in situ, consensus has yet to be reached as to what precisely those factors are. One possibility, which we consider in this paper, is that any interpretive correlates are only apparent, and that the choice is in fact primarily driven by extra-grammatical factors. A case of this type involves so-called
Moreover, whatever the interpretive properties associated with EV2 turn out to be, it seems clear that they are not identical to those associated with certain other MCP (see examples in (3)). From the point of view of the syntax-meaning interface, the bigger empirical question is whether all MCP share the same interpretive (or distributional) properties, apart from their restricted occurrence in embedded environments. Studying EV2 in the context of theoretical and empirical claims about MCP is therefore important, as it brings us closer to answering the question of what it means to be an MCP, and what the unifying property is, if any. The same can also be said for studying Swedish EV2 in the context of theoretical and empirical claims about EV2 across languages; at the level of the interface of structure and meaning, is EV2 a unified phenomenon? The availability of large-scale naturally occurring data, makes Swedish EV2 particularly well-suited to address these different questions for a type of construction that is both marked and infrequent in speech.
A popular approach to EV2, going back to Hooper & Thompson’s now classical work, is to argue that embedded clauses with V2 order are
We additionally demonstrate the use of diagnostics to differentiate the various underlying factors which drive syntactic optionality. This is to highlight how the type of usage data presented in this paper can indeed inform our understanding of traditional grammatical representations rather than supplanting them. We argue that not all probabilistic output is a reflection of learned gradient cognitive representations; the type of usage data which has popularly been analyzed as resulting from either gradient underlying structure (
The following sub-sections (§1.2–1.4) provide the theoretical and experimental background. Section 2.1 details the methods of our study. In Section 2.2 we consider a number of potentially relevant usage- or processing-based factors (
Adding to the observation made by Emonds (
(1) | Predicate types that allow MCP: | |
a. | (Non-factive) speech act predicates, e.g. |
|
b. | Doxastic non-factives, e.g. |
|
c. | Doxastic factives (also known as “semifactives”, following |
(2) | Predicate types that do not allow MCP: | |
a. | (Non-factive) response predicates, e.g. |
|
b. | Emotive factives, e.g. |
Classic examples of English MCP include VP-preposing (3a), topicalization (3b), left/right-dislocation (3c).
(3) | Hooper & Thompson ( |
||
a. | i. | Mary plans for John to marry her, and [marry her] |
|
b. | i. | [Each part] |
|
c. | i. | [This book] |
|
ii. | You should go to see it |
The observation made by H&T, illustrated in (4) using VP-preposing, is that MCP appear to be possible in the complements of the predicates in (1), but not embedded under those in (2).
(4) | Mary plans for John to marry her, and… | |
a. | I {say, think, know} that [marry her] |
|
b. | *I {resent, deny} that [marry her] |
For EV2 declaratives,
(5)
a.
Jon
Jon
{sa/trodde/visste}
{said/thought/knew}
att
that
han
he
had
inte
not
sett
seen
filmen.
movie.
‘Jon {said/thought/knew} that he hadn’t seen the movie.’
b.
*Jon
Jon
{förnekade/ångrade}
{denied/regretted}
att
that
han
he
had
inte
not
sett
seen
filmen.
movie.
‘Jon {denied/regretted} that he hadn’t seen the movie.’
(6)
a.
Jon {sa/trodde/visste}
Jon {said/thought/knew}
att
that
han
he
inte
not
had
sett
seen
filmen.
movie.
‘Jon {said/thought/knew} that he hadn’t seen the movie.’
b.
Jon {förnekade/ångrade}
Jon {denied/regretted}
att
that
han
he
inte
not
had
sett
seen
filmen.
movie.
‘Jon {denied/regretted} that he hadn’t seen the movie.’
It’s worth noting, however, that these empirical claims are based on subtle judgments about the acceptability of the relevant sentences, and that their empirical status is still a matter of debate. For instance, regarding the availability of topicalization in English embedded declaratives, Bianchi & Frascarelli (
(7) | Bianchi & Frascarelli ( |
I am glad that [this unrewarding job] |
Here we probe this question in the context of Swedish EV2, which we briefly introduce in the following section.
Syntactically, EV2 in Swedish involves movement of the finite verb to C.
In Swedish, which is SVO, it is not always clear from the surface constituent order whether a subject-initial clause has undergone V-to-C movement or not. This is because such movement often results in the same surface-order as a clause without movement, as shown in (8).
(8)
a.
Hon
she
gillar
likes
katter.
cats
‘She likes cats.’
b.
In Swedish, there are two common diagnostics for identifying verb movement. The first is the presence of sentence adverb (including negation), occupying the left edge of
(9)
a.
Hon
she
gillar
likes
inte
not
katter.
cats
‘She doesn’t like cats.’
b.
As shown using these diagnostics in (10) and (11), V2 is obligatory in Swedish matrix clauses.
(10)
a.
[Den filmen]
[that movie.
liked
hon t
she
‘That movie, she liked.’ EV2
b.
*[Den filmen]
[that movie.
hon
she
liked
‘That movie, she liked.’ *V-in situ
(11)
a.
Jon
Jon
had
not
sett
seen
filmen.
movie.
‘Jon hadn’t seen the movie.’ EV2
b.
*Jon
Jon
not
had
sett
seen
filmen.
movie.
‘Jon hadn’t seen the movie.’ *V-in situ
While EV2 is possible in certain embedded contexts, as shown in (5)–(6), it is by no means
(12)
Jon
Jon
{sa/trodde/visste}
{said/thought/knew}
att
that
han
he
(
had
not
(
had
sett
seen
filmen.
movie.
‘Jon {said/thought/knew} that he hadn’t seen the movie.’
Next, we turn our focus to the interpretive effects typically associated with EV2, and MCP more broadly.
The received view in the literature going back to Hooper & Thompson (
(13) | a. | The speaker is committed to p; |
b. | The speaker is attempting to add p to the Common Ground [CG] (the set of propositions mutually taken to be true by the discourse participants). |
It is uncontroversial that in uttering either sentence in (14), the speaker is typically asserting something about their beliefs, and not about John.
(14) | a. | I believe the rumor about John. |
b. | I believe that John stole the money. |
There does, however, exist a reading of (14b) on which the speaker is asserting the proposition that John stole the money. On this reading, the matrix clause “I believe…” plays a parenthetical role. As was observed already by H&T, the latter reading can be paraphrased using a slifting construction, as in (15).
(15) | John stole the money, I believe. |
Connecting the availability of MCP to the presence of illocutionary force would then nicely capture both their obligatory occurrence in matrix clauses, as well as their restricted availability in embedded clauses.
One popular way of encoding this connection between the syntax and the pragmatics is to say that MCP involve an extended C-domain that encodes illocutionary force (such as that in (16) from
(16) | Rizzi ( |
[ |
This can be contrasted with clauses that disallow MCP, which involve a smaller, or “impoverished” C-domain, in (17), incompatible with illocutionary force, topicalization and focus, as well as with any movement to their dedicated positions in the left-periphery, including V-to-C.
(17) | [ |
A problem for this perspective arises, however, when we consider factive predicates like
(18) | John discovered that [ |
On the classic view of assertion, given in (13), factive predicates are predicted to disallow embedded assertions, given that factives
In contrast, some authors (e.g.
(19) | a. | Maki, Kaiser & Ochi ( |
*John regrets that this book Mary read. | ||
b. | Hegarty ( |
|
*Mary realizes that this book, John read. |
While the above authors take this to be a general empirical claim about MCP, it has gained less traction in the literature on EV2. To our awareness, the only authors to advance this claim are Truckenbrodt (
In accounting for their observation that the doxastic factives seem to allow MCP, Hooper & Thompson (
(20) | Q. | Where is John? |
A1. | [ |
|
A2. | I think that [ |
As observed by Simons (
(21) | Q. | Where is John? |
A. | I found out that [ |
|
A. | #I’m happy that [ |
The claim advanced by Jensen & Christensen (
This account, however, is problematic for purely empirical reasons. For instance, Wiklund et al. (
(22)
a.
Varför
why
kom
came
han
he
inte
not
på
to
festen?
party.
‘Why didn’t he come to the party?’
b.
Kristine
Kristine
sa
said
att
that
han
he
was.allowed
inte.
not
‘Kristine said that he wasn’t allowed to.’ EV2
According to Wiklund et al. (
However, noting that the critical judgments are subtle and based on the intuitions of only a few speakers, Djärv, Heycock & Rohde (
(23) | ||||
a. | Q. | Why didn’t Kate come to the party? | [Main Point: |
|
A. | John thinks that [ |
|||
b. | Q. | Why didn’t John invite Kate to the party? | [Main Point: |
|
A. |
Their experiment, which was a judgment study, manipulated Main Point status [matrix clause; embedded clause], predicate type [Speech Act; Doxastic Non-factive; Doxastic Factive; Emotive Factive], and word order (V≺Neg; Neg≺V). They found a main effect of word order such that V3 (subject-adverb-verb order) was rated overall higher than V2 (p < 0.001), as well as a significant effect of predicate type (p < 0.001): speech act predicates and doxastic factives were rated higher than the doxastic non-factives and the emotive factives (in line with corpus results from Danish cited in
These results are problematic for the view that MCP and EV2 are driven by the Main Point status of the embedded proposition. Rather, their results seem more in line with a lexical licensing account, whereby the acceptability of EV2 is driven purely by the type of embedding predicate, such as that advanced by Wiklund et al. (
Finally, recall the first component of assertion, given in (13a); that the speaker is committed to p. We noted above that the Common Ground component of assertion, in (13b), is problematic given factive predicates. A number of authors, however, have argued that what is relevant for the licensing of EV2 is in fact only the criterion in (13a). Truckenbrodt (
(24)
In
in
Berlin
Berlin
snows
es
it
oder
or
in
in
Potsdam
Potsdam
shines
die
the
Sonne.
sun
‘It is snowing in Berlin or the sun is shining in Potsdam.’
The same is also true in Swedish:
(25)
Antingen
either
snows
det
it
i
in
Umeå,
Umeå
eller
or
så
so
shines
solen
sun.
i
in
Skellefteå.
Skellefteå
‘It is ether snowing in Umeå or the sun is shining in Skellefteå.’
Gärtner & Michaelis (
(26) | [[p-V2 or q-V2]] = [ p ∩ CG ] ∪ [ q ∩ CG ] |
Noting however, that their account nevertheless over-generates, in the case of matrix negation and conditionals, neither of which allow V2, they add a so called “progressivity requirement on assertive update”:
“An assertive update CG’ of a common ground CG by an utterance
They further state that “Progressive update captures the intuition that (dependent) root phenomena in general, and V2-declaratives in particular, come with an informativity requirement related to providing “new information”” (
In this section, we discussed different accounts of the type of interpretative effects associated with EV2 (and MCP more broadly). We noted that previously reported (experimental and judgment) data on Swedish EV2 only appears to be compatible with an account, such as that in Wiklund et al. (
Section 2.1 details the methodology for extracting corpus data. Section 2.2 is devoted to testing various processing-based hypotheses, and Section 3 to testing the predictions made by the two types of lexical licensing accounts discussed above. We show that the actual patterns of usage are not compatible with either of these accounts. Neither are they compatible with a processing or usage-based account of EV2. From considering the types of embedded environments in which V2 is licensed, we arrive at a pragmatic licensing account, whereby EV2 is licensed by discourse novelty. This view then, ends up being entirely compatible with that proposed by Gärtner & Michaelis (
We extracted natural language usage data from several very large Swedish corpora (
Rates of EV2 across corpora of varying formality. “Genre” represents a coarse categorization of corpora by source material. “Corpus” is the division provided within BFR. “Sentences” is the total number of sentences extracted from the original sub-corpus. “Proportion Non-ambiguous” represents the proportion of sentences within each subcorpus over which our extraction algorithm is able to apply the diagnostic for estimating EV2 vs. in-situ status. “p(ev2)” is the proportion of such sentences surfacing with EV2 order rather than embedded in-situ. Note that while the proportion of diagnostic cases is more or less steady by corpus, there is a clear effect of genre on the rates of EV2. Formal or more heavily prescriptive content has lower rates of EV2 compared to colloquial and informal material. Even in the most formal styles EV2 is still consistently attested.
Genre | Corpus | Sentences | Proportion Non-ambiguous | p(ev2) |
---|---|---|---|---|
Blogs and Forums | Familjeliv-känsliga | 5971907 | 0.1163 | |
Familjeliv-nöje | 458699 | 0.0809 | ||
Familjeliv-adoption | 77008 | 0.0936 | ||
Familjeliv-expert | 57478 | 0.0966 | ||
Bloggmix | 2713376 | 0.0765 | ||
Flashback-Politik | 2841872 | 0.0972 | ||
Historical | Tidning 1870 | 17084 | 0.06 | |
Tidning 1860 | 58839 | 0.062 | ||
Academic | Sweacsam | 52678 | 0.0736 | |
Humanities | 60931 | 0.0741 | ||
Goverment | Rd-bet | 372054 | 0.0698 | |
Rd-ds | 172657 | 0.0848 | ||
Rd-fpm | 5259 | 0.0686 | ||
Rd-skfr | 81800 | 0.0865 | ||
Accessible | Åttasidor | 8059 | 0.0768 |
Owing to the Zipfian distribution of frequencies inherent to language use (
As the goal is to examine sentences with the potential for EV2 order (regardless of whether or not that was actually realized), we created a subcorpus for analysis according to the following method.
For technical simplicity, we only consider single, rather than multiple, embeddings (approximately 20% of all sentences with the overt complementizer
This set of embedded complement sentences is diagnosed for EV2 status by considering the relative linear order of the embedded verb and negation (as outlined in Section 1.3). Theoretically, this diagnostic can be applied with any adverb in the embedded clause, however for tractability we limit our diagnostics to negation (
This results in a set of EV2/in-situ sentences which is necessarily a subset of the total instances in the data. However, there is no theoretical reason to expect factors such as non-negation adverbials or multiple embedding to have a profound and significant impact on the realization of EV2. Limiting our search to single-embedded sentences with negation allows technical tractability and high-confidence in the quality of output data while still providing a representative sample of over one million diagnosed sentences.
A range of statistical information was additionally extracted for each sentence and for each lemma overall. This includes frequencies, lexical semantic information such as [H&T] class (see Section 1.2),
At a descriptive level, Table
If we examine the attested likelihood of EV2 order by matrix predicate, we notice a fairly large degree of variation (Table
Sample values of probability of EV2 by predicate. Data from the Flashback-Politik corpus.
Verb | Gloss | p(ev2) |
---|---|---|
‘dream’ | 0.00 | |
‘forget’ | 0.12 | |
‘hear’ | 0.08 | |
‘say’ | 0.07 | |
‘believe’ | 0.03 | |
‘think’ | 0.06 |
Previous accounts of similar data (
We start from the premise that usage statistics need not be the thorn in the side of generative syntactic and semantic theory, but rather an informative window onto the underlying representations; thus flipping an argument typically taken by usage-based linguists (see
Under a usage-based framework, grammar is taken to be simply the cognitive organization of one’s experience with language. As such, factors like frequency of use of particular constructions would be predicted to have an impact on their representation. Bybee (
This psycholinguistic account has been applied to similar cases of “syntactic optionality” such as
In light of this, it is worth evaluating the fit of the same factors in the case of EV2. A processing or usage-based account should predict a connection between the frequency with which matrix predicates introduce embedded clauses (since it should speed up access of subsequent required embedded structure) and rates of EV2. However, as is clear in Figure
Probability of EV2 (X-axis) against the probability of introducing an embedded clause for each matrix predicate. This is limited to verbs which have a minimum frequency of 1000, introduce an EV2 clause at least 5 times, and which have occurred in a diagnostic sentence at least 100 times in the Flashback-politik corpus. There is no significant correlation between embedded clause-taking and the likelihood of EV2 order.
This is confirmed by a linear regression model in which
There is no correlation between likelihood of EV2 order and the probability of the matrix predicate introducing an embedded clause. Nor is there any correlation between likelihood of an embedded verb taking EV2 order and the frequency with which that verb appears in embedded clauses. Analysis is limited to verbs which occurred in a diagnostic sentence at least 100 times in the Flashback-politik corpus.
Dependent | Factor | Estimate | Std. Er. | t-value | P(>|t|) |
---|---|---|---|---|---|
P(EV2|matrix) | P(EC|matrix) | –0.0126 | 0.0201 | –0.627 | 0.532 |
P(EV2|embed) | P(EC|embed) | 9.583e-08 | 2.443e-07 | 0.392 | 0.696 |
P(EV2|embed) | Freq(embed) | –8.922e-09 | 1.593e-08 | –0.560 | 0.576 |
It is still conceivable that an underlying relation is hidden by the fact that the majority of lemmas are never attested with EV2. However, this is not the case; these analyses are robust even if limited only to verbs attested as taking EV2 order at least five times (Table
There is no correlation between likelihood of EV2 order and the probability of the matrix predicate introducing an embedded clause. Nor is there any correlation between likelihood of an embedded verb taking EV2 order and the frequency with which that verb appears in embedded clauses or the frequency of that verb overall. Analysis is limited to verbs which occurred in a diagnostic sentence at least 100 times and occur with EV2 order at least five times in the Flashback-politik corpus.
Dependent | Factor | Estimate | Std. Er. | t-value | P(>|t|) |
---|---|---|---|---|---|
P(EV2|matrix) | P(EC|matrix) | –0.005197 | 0.017014 | –0.305 | 0.76 |
P(EV2|embed) | P(EC|embed) | 1.950e-08 | 2.874e-07 | 0.068 | 0.946 |
P(EV2|embed) | Freq(embed) | –1.495e-08 | 1.760e-08 | –0.849 | 0.397 |
Another possibility is that rates of EV2 are a psycholinguistic by-product of speakers “forgetting” that they’re in an embedded clause, something akin to a speech error or disfluency. It is impossible to directly quantify the degree of disfluency based on text alone, but we can take an estimatable proxy. If a large amount of syntactic material or information content intervenes between the matrix verb and the beginning of the embedded clause, the processing system might be more likely to reset to applying main-clause syntax. If this were the case, we would predict an increase in intervening material before the complementizer to correlate with increased rates of EV2. In practice however, there is no clear relation between intervening material and EV2 (Figure
Length of material (number of words) intervening between the matrix predicate and the complementizer (X-axis) against the rate of EV2 (Y-axis). There is no overall effect of intervening material on rates of EV2, contra the predictions of a sentence production account. Data from the Flashback-Politik corpus.
What should be made of this lack of processing-level effects on EV2? The fact that we do not find evidence for a connection between frequency or predictability factors and rates of EV2 order are less a failure to replicate past work (
We argue that the consistent by-predicate rates of EV2 do not require speakers to be implicitly sensitive to such probabilities, but rather these stable rates of variation emerge as an interaction between meaning and context. A speaker doesn’t need an internal counter to tell them to utter a particular syntactic variant (EV2 vs. V-in situ) with
In this section we test the predictions of the two types of lexical licensing accounts discussed above. First, in Section 3.1, a set of accounts according to which the derivation of MCP (including V2) is
On the type of account articulated in De Cuba & Ürögdi (
However, as shown in Figure
Rates of V2 under factive vs. non-factive verbs; plot based on data from the Flashback-Politik corpus (2,841,872 sentences).
We also ran a Wilcoxon Rank Sum test (a non-parametric alternative to the two-sample
On the view advanced by Wiklund et al. (
In terms of the distribution of EV2 in the corpus, this account predicts that the relevant factor determining the rates of EV2 is simply membership of a particular lexical class. Moreover, given that pragmatic factors play no explanatory role on this account, we expect that if it were correct, then the rates of EV2 across predicate classes should be essentially constant, both across different discourse types—represented by the different genres of the corpora (see Table
Contrary to the first of these two predictions, we find that, while the distribution of EV2 to some extent varies across predicate classes along the lines predicted by this account (overall higher rates of V2 in the complements of speech act predicates, doxastic non-factives, and doxastic factives), the rates of EV2 across predicate classes varied
Rates of EV2 from three of the BRF-corpora. From top to bottom: Familjeliv-känsliga (family-oriented discussion forum; 5,971,907 sentences), Flashback-Politik (online forum for political discussion; 2,841,872 sentences), and Rd-bet (government texts; 372,054 sentences).
It is also worth noting that in neither corpus do the rates of EV2 straightforwardly track the rates of EV2 found in Jensen & Christensen’s (
Moreover, contrary to the second prediction made by this account, we also found that there was significant variability
Probability of EV2 by lemma within the class of speech act verbs (the x-axis represents the 21 different verbs in this class ordered by proportion of EV2); plot based on data from a corpus of text from a political online forum (Flashback-Politik; 2,841,872 sentences).
We take this as evidence against this type of strong lexical licensing account, whereby membership of a given lexical class is what determines whether EV2 is available or not.
In Sections 3.1 and 3.2, we tested the predictions made by the two types of “selection-based accounts” discussed in Section 1.4 against large-scale data from the BRF corpus: one according to which V2 should not be available in the complements of factive verbs; and one whereby V2 is available, but entirely optional, in the complements of certain predicate types (1), but not others (2). We found that for neither of the two accounts were their predictions straightforwardly borne out. Rather, the distribution illustrated in Figure
To account for the interaction of discourse context and lexical semantics illustrated in Figure
(27) | a. | EV2-clauses have some interpretive effect. The distribution or use of this interpretive effect is influenced both by: | |
i. | the meaning of the embedding predicate; | ||
ii. | the type of discourse context in which the sentence is uttered. | ||
b. | The proposition denoted by an EV2 clause is interpreted as constituting discourse-new information. |
Initial motivation for this proposal comes from considering the kinds of discourse contexts in which the relevant predicate types can felicitously be used. We observe that the different types of predicates vary in their ability to introduce entirely new information into the discourse; essentially, whether or not p has been previously discussed by the speaker and hearer. As shown in (28), this ability appears to correlate with the availability of EV2.
(28) | [Uttered out of the blue:] | ||
a. | John |
✔V2 | |
b. | John |
✔V2 | |
c. | John |
✔V2 | |
d. | #John |
✗V2 | |
e. | #John |
✗V2 |
Like the approach of Jensen & Christensen (
However, the lexical semantics of the embedding predicate is only
(29)
a.
Kan
can
du
you
inte
not
bara
just
slappna
chill
av
out
och
and
acceptera
accept
att
that
socialisterna
socialists.
can
inte
not
vinna
win
alla
all
gånger?
times
‘Why can’t you just relax and accept that the socialists aren’t going to win every time?’
b.
Acceptera
accept
att
that
du
you
kan
can
inte
not
älska
love
alla
everyone
men
but
du
you
can
inte
not
hata
hate
alla
everyone
heller
either
‘Accept that you can’t love everyone, but you can’t hate everyone either.’
What appears to be happening in these cases is indeed that the speakers are presenting the embedded propositions (‘the socialists can’t win every time’, and ‘you can’t love everyone, but you can’t hate everyone either’) as new information, in an attempt to update the Common Ground.
If the relevant dimension is truly the discourse status of the embedded proposition, the issue arises of how to test the hypothesis against corpus data, given that there is no direct way of measuring the discourse status of a given proposition in a corpus—especially not in one of this scale. However, it turns out that we
(30) | [Uttered out of the blue:] | |
a. | John |
|
b. | John |
|
c. | #John |
|
d. | #John |
|
e. | #John |
|
f. | #John |
|
g. | #John |
|
h. | #John |
Of course, as has been observed in previous work (e.g.
Based on this observation then, our hypothesis now predicts that the speech act and non-factive doxastic predicates, when negated, should show equally low rates of EV2 as the response predicates and the emotive factives (in both polarities), as shown in (31).
(31) | EV2: predicted distribution (verb type × negation interaction) | ||
a. | John |
✔V2 | |
b. | John |
✔V2 | |
c. | #John |
✗V2 | |
d. | #John |
✗V2 | |
e. | #John |
✗V2 | |
f. | #John |
✗V2 | |
g. | #John |
✗V2 | |
h. | #John |
✗V2 |
Before testing these predictions in the BRF-corpus, we wanted to make sure that this was indeed a robust property of these
The predictions illustrated in (31) are based on the observation that the speech act predicates and the doxastic non-factives, under negation, require their complement to be discourse-old. To make sure that this observation is empirically robust, we ran an experiment probing the effect of negation on whether or not p can be interpreted as discourse-new information under the different predicates types.
The experiment employed the “Guess what” test used above; here, framed in the context of a conversation between two friends, as shown in (32).
(32) | Two friends, Tom and Sue, run into each other. Tom says to Sue: |
To measure the perceived discourse status of p, the participants were asked to complete a statement in which they had to rate on a Likert scale how likely they thought it was that the speaker and the hearer had talked about p before (7 = not likely; 1 = very likely), as shown in Figure
Screenshot of an experimental trial.
Since our predictions were specifically about the interaction of negation with the speech act predicates and the doxastic non-factives, compared to the emotive factives and the response predicates, we did not include the doxastic factives in this experiment. We included three verbs from each lexical class:
(33) | a. | Speech act predicates: |
b. | Doxastic non-factives: |
|
c. | Response predicates: |
|
d. | Emotive factives: |
The experiment included 24 critical items, and 24 fillers, plus two practise items that were excluded from the analysis. Each item consisted of one verb and one (unique) complement clause, with variations in the two polarity conditions: positive (no matrix negation) vs. negative (with matrix negation). Whereas each embedded clause content occurred only in one item, every verb occurred in two items, so that each participant would see all conditions; [speech act vs. doxastic non-factive vs. emotive factive vs. response] × [negative vs. positive], across items, but with the specific content of the embedded clause shown only in one condition, counterbalanced across subjects using a latin-square design. Each subject thus saw each verb twice, once in the negative and once in the positive polarity (with different contents for the interlocutors and embedded clauses). Since there were three verbs per verb class, each participant saw each predicate type six times (three positive and three negative).
We also included baseline floor and ceiling conditions for discourse-old vs. new status, as illustrated in (34). There were eight items of each kind.
(35) | Control conditions: | |
a. | Discourse-new baseline (predict high ratings): | |
b. | Discourse-old baseline (predict low ratings): | |
Additionally, the experiment included eight pure fillers, involving conditionals (35). For these, the participants rated the likelihood of the proposition in the antecedent being old vs. new (here, that Nadine travelled to Asia).
(36) |
Importantly, the
The experiment was implemented in
56 undergraduate students, recruited through the University of Pennsylvania’s Psychology Department’s subject pool (SONA), participated in the study for course credit. They were given a link to the experiment to take it online in their own time. Based on responses in the control conditions, we excluded the responses from five participants who appeared to have reversed the scale, leaving us with the responses from 51 participants.
The data was analyzed in R (version 3.5.0). To test our predictions, we carried out a regression by fitting a linear mixed effects model, using
To identify outliers we created two sets of subjects based on their responses in the two control conditions (34): (a) subjects whose average response were more than one standard deviation below the mean in the discourse-new condition, and (b) subjects whose average response were more than one standard deviation above the mean in the discourse-old condition. We then took the intersection of the two sets, thus giving us only the participants who were outliers for
We predict that matrix negation will interact with predicate type, such that the speech act predicates and the doxastic non-factives receive significantly higher ratings in the positive than in the negated condition. We predict that the response predicates and the emotive factives should receive low ratings in both polarity conditions.
Figures
Response patterns by predicate type and polarity (critical and control conditions). The blue horizontal line shows the overall mean.
Response patterns by predicate and polarity (critical and control conditions). The blue horizontal line shows the overall mean
The R squared values for the data with and without the outliers are given in Table
R squared values for the data set with and without outliers. Marginal R squared values consider only the fixed effects; the conditional R squared values consider both the fixed and the random effects.
Data | Marginal R2 | Conditional R2 |
---|---|---|
Predicate Type: With outliers (n = 56) | 0.67 | 0.71 |
Predicate Type: Without outliers (n = 51) | 0.71 | 0.75 |
Verb Lemma: With outliers (n = 56) | 0.61 | 0.65 |
Verb Lemma: Without outliers (n = 51) | 0.72 | 0.75 |
The linear mixed effects model (based on predicate type, without outliers, n = 51) shows a main effect of predicate type. Relative to the intercept (6.0920; this is the mean of the dependent variable for the two base levels: predicate type = Speech Act and polarity = positive), the model shows that the following conditions are significantly different (p < 0.001) (the numbers represent the model estimated difference relative to the base levels): Doxastic Non-factive (
The model shows the following significant interactions (p < 0.001): the difference between the positive and the negative polarity is greater for the Speech Act predicates than for the other predicate types; Doxastic Non-factives (
These results then are precisely what we predicted (Section 5.1.4). Additionally, the difference between the Speech Act and Non-factive Doxastic predicates is in line with the observation that the Speech Act predicates show the overall highest levels of EV2. By testing acceptability judgements via English translations rather than the original Swedish we have ensured that any lexically-specific behavior of individual English predictes is precisely limited to English. Since the only connection between the English test items and their Swedish counterparts is through their formal semantic properties, we can rest assured that the strong connection we see between discourse-novelty (tested in English) and rates of EV2 (evaluated in Swedish) is robust. We know from this that the connection is due to structural causality rather than something psycholinguistic in nature like learned co-variation.
Having confirmed that matrix negation independently impacts the interpretation of the embedded proposition as discourse-old vs. -new information, for the Speech Act predicates and the Doxastic Non-factives, we were able to test our prediction that the rates of EV2 in the corpus should be notably lower for the negated Speech Act and Doxastic Non-factive predicates, than for their non-negated counterparts. As shown in Figure
Rates of EV2 with the speech act predicates and the doxastic non-factives under negative and positive polarity.
Importantly, this was not due to a main effect of negation, but reflects specifically the interaction of negation and the speech act and non-factive doxastic predicates, as predicted from the experimental results in Section 5. We also predicted that negation should not significantly impact the rates of EV2 for the Response stance predicates and the Emotive factives, as is borne out in Figure
Rates of EV2 with the response stance predicates and emotive factives under negative and positive polarity.
It is also worth pointing out the one place in the current data where our proposal makes clearly different predictions from the type of account discussed in Section 1.4, that takes EV2 to be licensed by the presence of a belief that p (e.g.
The findings presented in this paper support our hypothesis, outlined in Section 4, that EV2 is licensed in contexts where the embedded proposition constitutes discourse-new information. Importantly, this is a pragmatic property of an utterance in context—constrained, but not determined, by the lexical semantics of the matrix predicate. Other factors that play a role include the pragmatic context of the utterance, as well as other grammatical properties of the sentence. Here we investigated the effect of one such factor, namely matrix negation, and showed that certain predicates interact with negation in a way that constrains the potential discourse-status of a sentence. These results then made novel predictions regarding the distribution of embedded verb second in the corpus, which we showed were borne out. Note that while we only looked at the interaction with negation, the naturally occurring sentences in (29), from the BRF corpus, suggest that negation is only one potentially relevant grammatical factor.
In addition to the effect of discourse novelty, we also observed that the rates of EV2 are graded by formality, such that rates of EV2 are much lower in written, formal contexts. This replicates results from Heycock & Wallenberg (
It’s worth noting that while previous work has pointed to both discourse familiarity and negation as factors relevant to the licensing of EV2 and MCP, their effects have been interpreted disjunctively, as evidence for different theoretical accounts. On an account where EV2 is licensed by the presence of a belief-context, the effect of negation on EV2 is taken to follow from the negation of the attitude holder’s belief that p. However, we saw above that this view over-generates. On the kind of lexical licensing approach advocated by Haegeman and colleagues, MCP are claimed to be blocked by “presuppositionality” or “referentiality” (in their terminology). However, they take this to involve all factive verbs, and make no reference to negation. Here, we link the interaction of verb-type and negation explicitly to the discourse status of p, thus getting a unified account of the effect of negation and the role of predicate type. However, neither (speaker or attitude holder) belief, nor factivity plays any explanatory role on our proposal.
Apart from contributing to the empirical picture and the theoretical debate regarding EV2 and Main Clause Phenomena more broadly, the present study also represents a methodological contribution. Syntactic “optionality” is not an inherently unified phenomenon. While (particularly lexical-level) usage rates could potentially result from probabilistic representations, this need not be the case as specific output statistics can emerge from an interaction with context. We need to be careful in our interpretation of usage data and evaluate multiple theories (including both grammatical and psycholinguistic ones) when applicable. Yet, despite these caveats, we are still able to learn a good deal about grammatical representation directly from observational usage statistics.
The additional files for this article can be found as follows:
Corpus usage data by individual predicate; including EV2, frequency, polarity-dependent behavior, etc. DOI:
Raw output data from the “Guess What” discourse status experiment. DOI:
V2 is also possible in other types of embedded environments, including certain types of adverbial clauses. Here, we leave these to the side, but see for instance Wechsler (
Note that this description is likely somewhat simplified. Following Rizzi (
See for instance Platzack (
This is unlike in V2-languages that are SOV, like German and Dutch.
Although see (7) from Bianchi & Frascarelli (
Also cited in De Cuba & Ürögdi (
Also cited in Haegeman & Ürögdi (
Though Truckenbrodt (
There are other interesting and important components to the analyses presented here; for instance, these authors link the “presuppositional” nature of factive clauses to the selection of a “referential” CP (following
According to him, matrix clause V2 additionally requires that the speaker wishes to add p to the Common Ground.
Although note that it’s less clear how their account would deal with V2 in German
(1) Weder neither schneit snows es it in in Berlin, Berlin, noch nor scheint shines die the Sonne sun in in Potsdam. Potsdam ‘It’s neither snowing in Berlin, nor is the sun shining in Potsdam.’
It appears to us that such sentences, which would presumably be interpreted as ¬(ϕ1 ∨ ϕ2), are at odds with their progressive update criterion for EV2. We leave this issue to the side. Thanks to Florian Schwarz, p.c. for this observation.
This estimate comes from the present study; the proportion of sentences with an overt adverb such as negation in the embedded clause.
Code is available open-source at
For example,
A highly frequent but limited set of 108 lemmas was tagged for semantic class based on their classification in previous literature on the topic (
As in Table
The alternation illustrated in (1a) vs. (1b).
(1)
a.
The coach said the players were tired.
b.
The coach said that the players were tired.
What’s more, the availability of lemmas for fast processing can be experimentally manipulated to causally induce the use of passive structures over otherwise equivalent active ones (
Importantly, the # refers to the readings where p is presented to the hearer as discourse new information (as opposed to where the sentence makes a comment about the attitude holder). The same goes for (30) and (31).
It is worth noting that the idea that discourse novelty is relevant to the licensing or availability of EV2 is implicit also in a number of “assertion-based” accounts (e.g.
Note that the notion of discourse novelty that is relevant here is different from that involved in cases of (
(1) a. Bøtene fines. skal shall være be så so store large at that de they ikke not frister tempt innehaveren proprietor. til to å to fortsette. continue ‘The fines should be so large that they do not tempt the proprietor to continue.’ b. *Bøtene fines. skal shall være be så so store large at that de they frister tempt ikke not innehaveren proprietor. til to å to fortsette. continue
However, this point speaks directly to the difference between on the one hand, global accommodation, and on the other, presenting a proposition p
See also Djärv (
The doxastic factives were excluded for the purpose of keeping the experiment size manageable; we had no specific prediction about how they should interact with negation. Note though, that recent work by Djärv (
As an anonymous reviewer points out, it has been noted, for instance by Wiklund et al. (
As an anonymous reviewer points out, the prescription against EV2 is quite explicit in the Swedish educational system at all levels, and is commonly referred to as the “BIFF”-rule. See for instance
A lot of helpful discussion contributed greatly to this work. In particular, we would like to thank Luke Adamson, Ryan Budnick, Anthony Kroch, Florian Schwarz, Besty Sneller, Hongzhi Xu, and Charles Yang. We also thank the audiences at Formal Ways of Analyzing Variation (FWAV 4) at York, Texas Linguistic Society 17 at UT Austin, the Mid-Atlantic Colloquium of Studies in Meaning (MACSIM 7) at Georgetown, Meaning in Flux at Yale, and SelectionFest at ZAS Berlin, along with the members of the SchwarzLab at UPenn.
This research received financial support from NSF-grant BCS-1349009 to Florian Schwarz.
The authors have no competing interests to declare.
Spencer Caplan and Kajsa Djärv authors contributed equally to this manuscript.