2.1 Exhaustivity

The production of additives in affirmative sentences is said to be obligatory if there is a suitable antecedent in the preceding context (cf. Krifka 1998; Zeevat 2003; Sæbø 2004). For example in (2), speaker2 should utter the particle too (2b), since the preceding utterance (2a) is a suitable antecedent. In contrast, omitting too leads to pragmatic oddness.

Bade’s 2016 account (based on Krifka 1998; Sæbø 2004) – henceforth the Obligatory Implicature account – explains this pragmatic oddness by assuming that (2b) gives rise to an exhaustivity implicature (i.e. that Mattia is the only salient individual who finished their PhD) which contradicts speaker1’s utterance. In order to circumvent this markedness, too has to be inserted to block the exhaustivity implicature of (2b). The exhaustivity implicature arises due to the presence of focus – here on Mattia evoked by the contrastive phrase (2a). Focus causes the insertion of an exhaustivity operator (EXH) excluding all alternatives that are not entailed by (2b) making Mattia the exhaustive answer to the Question Under Discussion (QUD Roberts 1996) Who finished their PhD?¹

The degree to which additives were judged to be obligatory has been found to depend on the extent to which exhaustivity is enforced by the context (Bade 2016; Bade & Renans 2021). Bade & Renans (2021) carried out two experiments in Ga (Kwa) and German, in which participants were asked to judge the acceptability of sentences with or without additives. Bade & Renans (2021) manipulated the strength of exhaustivity via context-sentence type (SVO, cleft), whereby exhaustivity should be stronger with cleft constructions (3b) than SVO (3a) structures. Here we give an example of the manipulation in English taken from Bade & Renans (2021):

In line with the Obligatory Implicatures account, Bade & Renans (2021) found that omitting additives for both languages was less accepted in contexts with strengthened exhaustivity (cleft) than in contexts with moderate exhaustivity (SVO). Exhaustivity, and with that the extent to which additives are perceived as obligatory, may additionally be influenced by discourse factors such as the degree to which antecedent and host are similar (Spenader 2002; Amsili et al. 2016) and the distance between antecedent and host (Kim 2015; Chen & Husband 2018) which we discuss below. Thus, while we did not test exhaustivity explicitly, we investigated factors that may influence the strength of the exhaustivity implicature; more specifically, we looked at similarity and proximity between antecedent and host utterance.

2.2 Similarity

In a corpus study using the London-Lund Corpus of Spoken English (LLC), Spenader (2002) found that too mainly served the purpose of signalling parallel information. Similarly, Amsili et al. (2016) found that aussi (French too) signals similarity of the sentence containing aussi – the host sentence – and its antecedent. Use of aussi increases the more similar the host and antecedent are, whereby increased similarity is measured by the presence of ellipsis or anaphora in the host. For example, in one condition the host sentence was identical to the antecedent (see (5a) for the English equivalent), whereas in the more reduced manipulations the post-verbal arguments were replaced gradually by pronouns (5b–5c).

Amsili et al. (2016) found that the more reduced the host sentence was – and arguably more similar to the antecedent – the more aussi was preferred by addressees. Their results are based on the argument that while the full form Paul in (5a) may refer to a second individual named Paul (other than the Paul in (5)), the pronominalised form him in (5b) refers more clearly to the same individual as Paul in (5). Thus, due to pronominalisation, (5b) is more similar to (5) than (5a). Note that this argumentation is slightly different from Kaplan’s (1984) account, who first observed the increased obligatoriness of additives in anaphorically reduced host sentences. According to Kaplan (1984), reduced host sentences introduce greater prominence of contrastive topic than full host sentences, and thereby higher pressure to use additives to emphasise the similarity between antecedent and host. From the speaker’s perspective this would mean that with increasing similarity the pressure to utter additive particles such as too increases.

Winterstein & Zeevat’s (2012) argument proceeds along similar lines whereby the insertion of too depends on argumentative identity. Winterstein & Zeevat (2012) claim that the more similar the antecedent and host are, the more they can be seen as being directed towards the same conversational goal, which increases the pressure to insert too. For example, (6b) seems less felicitous than (6a), since (6a) seems closer to the conversational goal of (6) than (6b). More specifically, for (6b), it is argued that although being almost on time entails being late, (6) credits John with almost achieving timeliness, whereas (6b) gives no such credit to Mary. Assuming that too requires argumentative similarity between host and antecedent, (6b) is degraded because the two sentences involve contradictory predicates.

In the current study, we extend previous findings on anaphorically reduced antecedents by investigating similarity in terms of mostly content-based similarity, in contrast to previous work that has emphasized similarity of surface form between host and antecedent. Including similarity in our production study is crucial to determine in what way similarity plays a role in the speaker’s considerations when contributing to an ongoing discourse in comparison to the effect of similarity on the comprehension or acceptance of linguistic material.

2.3 Turn Distance

Another factor that was found to play a role for the insertion of additives was the distance between suitable antecedents and the host. This factor is related to what Kripke (2009) calls the anaphoric component of presuppositions triggered by additives: additives trigger a propositional alternative that is required to be pre-mentioned (in the form of an antecedent) and additives cannot just be uttered out of the blue. Similar to other anaphoric elements of language, whether content is perceived as a suitable antecedent may be related to locality or distance between antecedent and host.

Kim (2015) found that the comprehension of additives is influenced by the linear distance between antecedent and host² such that comprehenders interpreted material that was most recent to be the antecedent of the additives. For (7f), the sentence (7e) was most frequently chosen as antecedent, yielding the interpretation that Andy bought a croissant and nectarines as opposed to celery, a croissant and nectarines. However, one may argue that while (7c) could in principle be interpreted as the antecedent as well, the usage of usually may endorse an interpretation in which Andy usually buys celery but did not do so today thereby removing “Andy bought celery” as a potential antecedent. Thus, the reason for which (7e) was the most frequent option may not solely have to do with locality.

Chen & Husband (2018) similarly manipulated linear distance between antecedent and host with a binary acceptability judgement task. In contrast to Kim (2015), Chen & Husband manipulated distance within an if-clause:

Chen & Husband also manipulated the context such that the context either satisfied (8/9) or violated (10/11) the presuppositions. They found that participants were more accurate – accepting the sentence in the satisfied condition (8/9) and not accepting the sentence in the violated (10/11) condition – in the near condition than in the far condition.

Both studies illustrate the potential role that proximity between antecedent and host may play in comprehension using written texts. It still remains to be investigated how proximity between a potential antecedent and host as measured by turn distance in dialogue-like structures influences additive production. By looking at mostly content-based similarity and proximity (turn distance), our study looks at two crucial factors that contribute to the structure of a discourse.

2.4 Social convergence/divergence

Considering that dialogues are placed in social settings which in turn influence speakers’ production choices, we investigated the influence of social considerations on additive production. More specifically, the role of similarity and distance on the production of additives may extend to the social level in terms of similarity between speakers and social proximity. Thus, we focused on another possible function of additives that has not been investigated yet – at least to our knowledge – which is social convergence/divergence. More specifically, speakers who utter too may not only signal similarity between their utterance and the previously mentioned antecedent utterance but may also draw parallels between themselves and the antecedent speaker. This line of reasoning builds on Winterstein & Zeevat’s (2012) account of argumentative identity, which we introduced earlier as a way of construing the distance between antecedent and host in terms of whether they are directed towards the same conversational goal.

The concept of social convergence/divergence is introduced first within the framework of Communication Accommodation Theory (e.g. Giles 1973; 1977; 1979). The account is built on the assumption that interlocutors negotiate personal and social identities through linguistic, discursive and non-linguistic tools (Gallois et al. 2005). Thus, interlocutors may adjust their way of communicating to appear more alike (converge) or distinct (diverge) from other interlocutors. A possible motive for speakers to align their communicative behaviour could be the desire for approval (Gallois et al. 2005). In contrast, divergence may result from a speaker’s wish to reinforce their social identity and/or dissociate themself from other interlocutors. Whereas converging speakers are most commonly received as cooperative, the reception of diverging speakers may vary. Divergence may be evaluated negatively, especially when it is judged to threaten social norms, e.g. politeness norms. However, divergence may likewise be received positively when diverging from one speaker entails converging with other interlocutors who share a common, positively valued group membership (Giles & Hewstone 1982).

Converging and diverging are very much intertwined with social norms such as politeness, a concept construed within Politeness Theory as interlocutors’ aim to maintain their positive or negative face (Brown & Levinson 1987). Whereas positive face reflects the interlocutors’ maintenance of a positive self-image, negative face reflects the interlocutors’ freedom to act on their own terms. Face-threatening actions can damage the face of either the speaker or addressee. For example, speakers may aim to converge – e.g. by choosing similar topics as the other interlocutors – to maintain their positive face. In contrast, diverging from someone – e.g. by changing the topic – may maintain the speaker’s negative face but may likewise threaten their positive face, since diverging can come across as impolite.

Applied to additive particles, using too to pick out an antecedent uttered by another speaker seems not only cooperative on the ontological level but also means that speakers converge with the antecedent speaker by signalling similarity between their utterances. This convergence move may come across as particularly strong if both antecedent utterance and host utterance convey values or opinions of both speakers, as in (12). In line with Communication Accommodation Theory, the motive for uttering too instead of leaving it out may reflect a general tendency to converge with speakers that share the same values (Gallois et al. 2005). However, one could also say that convergence is just a by-product of uttering too in obligatory environments. In this sense, uttering too is simply the easiest option to avoid making a controversial or face-threatening discourse move.

The derivation from the default of uttering too may be an instance of divergence. For example, one could assume that speakers, such as Monica in (12d), omit too and avoid acknowledging the parallelism between their utterance and the antecedent utterance (e.g. Rachel’s utterance (12c)) in order to distance themselves from the antecedent speaker (e.g. Rachel). Or to phrase it differently, speakers may choose not to block the contradictory exhaustivity implicature with the insertion of additives, and leave the resulting contrast between their utterance and the antecedent utterance to highlight a contrast on the social level. A possible motive for diverging from the antecedent speaker could involve contrasting values/opinions or that the antecedent’s behaviour threatens politeness norms. In this sense, speakers may wish to maintain their own negative face by not being associated with the antecedent speaker. In our study, we aim to explore whether omitting additives in potentially obligatory environments can be understood as a means to diverge from an interlocutor’s turn. In this way we are able to see the extent to which speakers consider or disregard discourse constraints such as proximity depending on social factors such as politeness.

3.1 Experiment I

The first experiment investigates the production of additives in an open choice paradigm in which participants were asked to type in their response in a text box. We analyse the speaker’s binary choice to include or omit an additive particle as our dependent variable. For the coding of our dependent variable, the first and second authors coded the participants’ responses independently and discussed deviations in their coding together with the third author. Participants’ responses were coded as containing an additive (=1) if participants used the additive in their response to refer back to the antecedent utterance. Thus, we coded responses as not containing an additive (=0) if a response didn’t contain an additive to begin with, or if the additive did not unambiguously refer back to the antecedent utterance, such as in (13) and (14).

We considered the following additives: too, also, as well, same as and another, such as in (15) and (16).³

Besides additive production, participants used other linguistic tools to pick up the antecedent utterance such as in (17) and (18). We considered these instances in a further analysis which is part of Appendix 2.

First, experiment I tests whether our experimental set-up elicits the use of additives and which additives participants produce most frequently. We analyse the speaker’s binary choice to include or omit an additive particle (dependent variable) to see how that choice is affected by Similarity, Turns, and Politeness. In experiment II we used a forced-choice paradigm based on the responses of experiment I.

3.1.2 Design and Materials

Participants were asked to engage with their colleagues and a waiter by typing their responses in a text-field. Half of the critical items (‘order’ items) were about ordering dishes/drinks from a waiter, and half of the critical items (‘talk’ items) were about content related to work or daily life, e.g. the date and time of a meeting. Each of the eight critical items started with an introduction to the upcoming conversation; participants were presented with context pictures together with a question about their content. See Figure 1 for an ‘order’ item picture (always a menu) and Figure 2 for a ‘talk’ item picture (here a planner). In this way, participants were able to familiarise themselves with the visual cues (the menu/planner) they would later need for formulating their response. For example, the ‘order’ item context already prepared participants that they would be asked to order a glass of Chardonnay when it was their turn to order. The visual cues were then presented to participants again (Menu with ‘Chardonnay’ highlighted in Figures 5 and 6). This set-up is an attempt to mimic actual conversation, since interlocutors in an actual conversation do already have some knowledge about what they can contribute about a given topic when listening to the contributions of other interlocutors. It also allowed us to constrain the participant’s message content so that we could test what factors affected how they formulate an utterance about that content.

Figure 1

Example of an ‘order’ item context.

Figure 2

Example of a ‘talk’ item context.

After having answered the context question, the conversation started. Each picture had a headline reinforcing the topic of the conversation. For ‘order’ items, the headlines would signify what interlocutors were ordering, e.g. ‘Ordering drinks’; for ‘talk’ items the headline would say what the conversation was about, e.g. ‘Discussion about the time of next week’s meeting’. Each conversation started with Omar’s turn followed by Lee, Amber and Robert, see Figures 3 and 4 for the first three turns. Each conversational turn was displayed separately and participants had to click a button to proceed to the next one. The last turn (Robert) was always displayed together with the visual cue and together with the request for the participants to write their response, see Figures 5 and 6.

Turn Distance was manipulated such that the antecedent utterance either immediately preceded the participants’ turn (0 turn distance, see Figure 3), or the antecedent and participants’ turn were separated by the remaining colleagues (3 turn distance, see Figure 4). Thus, the antecedent speaker for the 0 turn condition was always Robert and the antecedent speaker for the 3 turn condition was always Omar.⁴

Figure 3

Example of the first three turns for an ‘order’ item in which the participant will order Chardonnay with no intervening turn between the antecedent speaker and the participant.

Figure 4

Example of the first three turns for an ‘order’ item in which the participant will order Chardonnay with three intervening turns between the antecedent speaker and the participant.

Figure 5

Example of a last turn for the ‘order’ items in the perfect similarity (‘Chardonnay’ is highlighted), no intervening turn condition. In the reduced similarity condition ‘Pinot Grigio’ would be highlighted.

Figure 6

Example of a last turn for the ‘order’ items in the perfect similarity (‘Chardonnay’ is highlighted), three intervening turns condition. In the reduced similarity condition ‘Pinot Grigio’ would be highlighted.

To manipulate the factor Similarity, the picture cues either encouraged participants to give a response that was perfectly similar or only vaguely similar to the antecedent utterance produced by either Robert or Omar. Taking the ‘order’ items as an example, the drink/dishes we asked participants to order either completely corresponded (perfect similarity) or did not correspond/only partially corresponded to the antecedent order (reduced similarity). For example, in Figures 5 and 6, participants were encouraged to order Chardonnay which perfectly matched Robert’s or Omar’s order. For the reduced similarity condition the participants’ order would have been Pinot Grigio which did not match Robert’s or Omar’s order. This was slightly different for orders in which participants were asked to order two dishes: in the perfect similarity condition, both the highlighted starter and main matched the antecedent order, as opposed to the reduced similarity condition in which only the starter but not the main matched the antecedent order (partial match).⁵ The focus of this study was primarily to investigate the difference between environments in which the additive usage is supposedly obligatory (perfect similarity) versus environments in which it is not (partial/no similarity). However, we briefly discuss how these different kinds of dissimilarities influenced the participants’ use of additives for experiment I in Section 3.1.6 and more thoroughly in Section 3.2.6 for experiment II. We have illustrated the similarity manipulation for the ‘talk’ items in Appendix 1.⁶

We additionally investigated social divergence and manipulated the way the antecedent speakers phrased their orders: either neutrally, see Figure 5, or impolitely, see Figure 7. Participants were randomly assigned to either the neutral or impolite condition. In the neutral condition, all four colleagues behaved neutrally; in contrast, in the impolite condition, the two antecedent speakers (Omar and Robert) would make impolite remarks towards the waiter or colleagues. For this we included impolite material, see the bolded part of (19), to precede the utterance of the neutral condition, see the italic part of (19a) and (19b).

1. (19)
1. a.

1. Item 1, neutral condition:
2. I’d like a glass of Chardonnay.

1.  
1. b.

1. Item 1, impolite condition:
2. Although you served me warm white wine last time, I’d like a glass of Chardonnay.

Placing the impolite material first was a way to keep the neutral and impolite conditions comparable: placing impolite material after or within the utterance I’d like a glass of Chardonnay would have induced more distance between antecedent and participant turn as well as increased the dissimilarity between the turns. However, we do acknowledge that the impolite material increases the complexity of the antecedent turn overall. The antecedent speakers’ impolite behaviour was restricted to the critical items and the attention checks stayed the same for both conditions. This resulted in a 2×2×2 design, with two within-subjects factors (Similarity and Turn Distance) and one between-subjects factor (Politeness). We decided to test Politeness as a between-subjects manipulation to be able to investigate Similarity and Turn Distance in a completely neutral antecedent speaker set-up which more closely resembles what has previously been done.

Figure 7

Example of a last turn for the ‘order’ items in the perfect similarity (‘Chardonnay’ is highlighted), no intervening turn condition in which the antecedent speaker is impolite.

We tested whether interlocutors indeed perceive the added material in the impolite condition as being impolite by running an additional norming study using an independent sample. Participants (N = 30, British English speakers) were asked how they would rate the antecedent speakers’ utterances choosing between the options impolite, neutral or polite. The utterances in question were presented as part of the same four turn dialogue used in the main study with the only exception that both antecedent utterances directly preceded the participants’ task. Our results suggest that our politeness manipulation was successful: utterances in the impolite condition were most frequently judged as being impolite (88.3%) and much less so as being neutral (10.8%) or polite (0.83%). In contrast, utterances in the neutral condition were mostly judged as being either neutral (53.3%) or polite (41.5%) and only infrequently as being impolite (4.16%). The data is available in our OSF repository https://osf.io/az2uf/.

The 8 attention checks were similar to the ‘talk’ items. Participants were introduced to the visual cue, see Figure 8, followed by the colleagues’ turns and their own turn, see Figures 9 and 10. The only difference was that the colleagues’ turns were not manipulated to induce participants to use additive particles. Participants who failed to answer the context question correctly, and also failed to base their conversational contribution on the visual cue, were considered as having failed the attention check.

Figure 8

Example of an attention check context.

The experiment consisted of four blocks, each containing two attention checks, one ‘talk’ item, and one ‘order’ item (block1: drinks, block2: appetizer & main, block3: dessert, block4: drinks). Thus, each participant saw 8 critical items.⁷ Although the item order within each block was randomised, the order of the blocks was always the same.⁸

Figure 9

Example of an attention check: first three turns.

Figure 10

Example of an attention check: last turn.

3.1.6 Results

Participants were above 96% accurate for the attention checks, which suggests that they paid attention during the experiment. When asked, participants indicated that they understood the task (mean = 83, sd = 20.6, mode = 100, median = 90). Overall, participants used the additive particles too, also, as well, another, and same as for target items throughout the experiment (in total 108 times out of 624 responses on target trials), and thus, 17% of the participants’ utterances contained additives. The additive same as was the most frequent choice, see Table 1 for more details.¹²

Table 1

Absolute frequencies of additives for the different item types and overall.

Additive	Item Type	Absolute Freq.	Overall
same as	Order Item	28	47
same as	Talk Item	19
too	Order Item	10	23
too	Talk Item	13
also	Order Item	13	23
also	Talk Item	10
as well	Order Item	12	16
as well	Talk Item	4
another	Order Item	3	3
another	Talk Item	0

There were differences in how frequently additives were used across different types of reduced similarity items. Recall that half of the critical items were manipulated to be a categorical mismatch between antecedent and participant utterance, and the other half was manipulated to be a partial match. Participants would still occasionally use additives when there was a partial match –5% of all partial match trials contained additives – but not when there was no match. In contrast, 31% of all perfect match trials contained additives.

As Figure 11 illustrates, additives were most frequently used when host utterance and antecedent utterance were similar and when there were zero intervening turns. Frequency was reduced when three turns intervened. In contrast, the difference between the neutral and impolite antecedent speaker groups is less clear.

Figure 11

Experiment I: relative frequency of choosing additives in each of the Similarity × Turn Distance conditions, contrasting participants confronted with a neutral (top) versus impolite (bottom) antecedent speaker.

These observations are supported by the outcome of the analysis, see Table 2. Averaging over Turn Distance and Politeness, a change to the perfect similarity condition meant an increase in log-odds of additive production ( $\widehat{\beta }$ = 2.00, CrI:[1.23, 2.78]). Similarly, averaging over Similarity and Politeness, a change to the zero turns condition meant an increase in log-odds of additive production ( $\widehat{\beta }$ = 1.10, CrI:[0.49, 1.77]). Both effects appear reliable, since the credible intervals of both effects do not include zero. However, we did not find reliable evidence that the antecedent speakers’ politeness influenced additive production. In Figure 12, we illustrated the predicted probabilities for speakers to produce additives given our data and model. Speakers are predicted to produce additives most frequently for perfect similarity and when no turns intervene between their utterance and the antecedent utterance and least frequently for reduced similarity when three turns intervene. We found almost identical effects when considering all linguistic tools besides additive particles (such as make that two constructions), see Appendix 2 for the complete model output.

Table 2

Population-level estimates of the logistic regression model in log-odds with the standard errors and 95% credible intervals. In the table the intercept (i.e. the grand mean) is listed first, then the estimates for Similarity, Turn Distance, Politeness and their interactions follow. Similarity is the change in log-odds for perfect similarity (–1 reduced, 1 perfect), Turn Distance is the change in log-odds for no turn (–1 three turns, 1 no turns), and Politeness is the change in log-odds for a neutral antecedent speaker (–1 impolite, 1 neutral). Slope coefficients whose 95% credible intervals do not include zero and are therefore treated as reliable effects are highlighted in bold.

Coefficient Estimates	posterior mean	Est.Error	I-95% CrI	u-95% CrI
Intercept	–3.52	0.73	–4.99	–2.11
Similarity	2.00	0.39	1.23	2.78
Turn Distance	1.10	0.32	0.49	1.77
Politeness	0.23	0.34	–0.42	0.90
Similarity*Turn Distance	0.06	0.32	–0.60	0.69
Similarity*Politeness	–0.02	0.33	–0.67	0.64
Turn Distance*Politeness	–0.18	0.31	–0.82	0.40
Similarity*Turn Distance*Politeness	0.25	0.31	–0.34	0.87

Figure 12

Predicted probabilities of producing additive particles given the model and the data for perfect (left) and reduced similarity (right) and 0 and 3 intervening turns. The figure contrasts the probability of producing additives when faced with a neutral antecedent speaker (blue) versus an impolite antecedent speaker (red).

The credible intervals of all interaction terms include zero which suggests that our three predictors did not interact in a systematic way. We compared the expected log predictive density of the full interaction model to models with reduced interaction terms, a main effects only model and a model that only included Similarity and Turn Distance as predictors. Model comparison was carried out via PSIS-LOO approximation (Pareto smoothed importance sampling leave-one-out approximation; Vehtari et al. (2015; 2017)). The approximation showed that a simple main effects model excluding any interaction terms had the highest predictive accuracy, followed by a model that included all three models as main effects and an interaction between Similarity and Politeness. However, the differences between the models were small, as shown in Table 3.

Table 3

Experiment I: the table shows the difference in the models’ expected predictive accuracy (elpd_diff) and the standard error of the difference in elpd (se_diff) with the preferred model listed first.

	elpd_diff	se_diff
Similarity + Turn Distance + Politeness	0	0
Sim * P + TD	–1.1	1.0
Sim * TD	–1.3	1.4
Sim + TD * P	–1.9	0.8
Sim * TD + P	–4.9	1.7
Sim * TD * P	–6.8	2.1

3.2 Experiment II

The second experiment investigates the use of additives in a forced-choice paradigm in which participants can choose between the bare assertion (20), the assertion plus additive (21), an incorrect response (22) and the option to type their own response (‘other’). Note that Similarity is enforced in the sense that now participants are not only presented with more or less similar content but also formulations that are similar to the antecedent speaker’s turn.

We decided to focus on too, since too was after same as the most frequently produced additive. For this decision we considered the participants’ overall production preference including ambiguous cases in which the additive did not unambiguously refer back to the antecedent utterance.¹³ We initially were interested in presupposition triggers which is why we did not use same as as the pre-determined choice for experiment II. In order to account for participants wanting to use additives other than too or preferring to produce their own utterances in general, we included the participants’ formulated utterances (option ‘other’) in our analysis. We applied the same coding as for experiment I.

The experimental design of experiment II allows us to circumvent issues of scope ambiguity by creating stimuli in which the additive more unambiguously refers back to the antecedent utterance. However, in restricting the participants’ responses, experiment II more closely resembles acceptability judgement tasks which are frequently conducted to analyse the obligatoriness of additives: participants are shown an antecedent utterance and see the direct contrast between a following utterance with or without an additive. Thus, one could argue that this makes our claim about the novelty of our experimental design being a production study less appealing. However, we argue that experiment II contributes additional insights: since participants were explicitly offered to use a host utterance either containing or not containing an additive in the forced-choice paradigm, exhaustivity should be enhanced in experiment II as opposed to experiment I. We therefore expect additives to be chosen more frequently in experiment II than in experiment I. The aim of experiment II was furthermore to replicate the effects of Similarity and Turn Distance and to shed more light on possible interactions between the three factors under investigation by increasing the number of participants as well as the expected number of additive-containing continuations. In addition to investigating Similarity as a binary factor, we take an exploratory look at the distinction between partial similarity and no similarity.

3.2.6 Results

Again, participants were above 96% accurate for the attention checks, which suggests that they paid attention during the experiment. Participants also seemed to have understood the task (mean = 85, sd = 19.6, mode = 100, median = 94) and rated the predetermined choices as mostly natural (mean = 79, sd = 20.88, mode = 100, median = 82). Overall, participants used additive formulations throughout the experiment and more often than in experiment I: 32.3% of the participants’ utterances contained additives. ‘Order’ items again elicited more uses of additives (35%) than ‘talk’ items (29%). The option ‘other’ was chosen 73 times (out of 1128). After inspection of the ‘other’ responses, 9 instances were included that contained additives of which too was used 7 times, as well and also 1 time, respectively. There are two observations for which participants used other linguistic formulations to refer back to the antecedent utterance such as I’m with Omar on this, I love Korean food. ‘Other’ responses containing too often entailed further interaction with either a neutral (28a) or impolite (28b–28c) antecedent speaker.

1. (28)
1. a.

1. Great minds think alike Robert. I’ll have the sticky toffe pudding and an expresso too.

1.  
1. b.

1. i’d like a pin of heineken too please. Robert you should’nt speak to the waiter in that way it is disrespectful

1.  
1. c.

1. To waiter: The Breaded brie and king prawn linguine for me too, please. To Omar (once the waiter has left): Omar, are you okay? I think you might have been a bit abrupt with the waiter and that’s not like you.

Figure 13 illustrates that, similarly to experiment I, additives were most frequently used when host utterance and antecedent utterance were similar and when there were zero intervening turns. In contrast to experiment I, participants used additives in the reduced similarity/three intervening turns condition. Moreover, the frequency of additive use seems to be less when speaking after an impolite speaker than after a neutral speaker both for perfect similarity conditions and in the reduced similarity with three intervening turns. The opposite seems to be the case for the reduced similarity condition with zero intervening turns.

Figure 13

Experiment II: relative frequency of choosing additives in each of the Similarity × Turn Distance conditions, contrasting participants confronted with a neutral (top) versus impolite (bottom) antecedent speaker.

These observations are supported by the outcome of the analysis, see Table 4. Holding everything else constant, perfect similarity (as opposed to reduced similarity) between antecedent utterance and host utterance led to an increase in log-odds of additive production ( $\widehat{\beta }$ = 1.32, CrI:[0.53, 2.02]), as did the antecedent utterance directly preceding the host utterance ( $\widehat{\beta }$ = 0.72, CrI:[0.29, 1.16]), and speaking after a neutral antecedent speaker ( $\widehat{\beta }$ = 0.34, CrI:[0.03, 0.69]). Overall, Similarity seems to affect the production of additives to a greater extent than Turn Distance and Politeness. The credible intervals of all effects do not include zero.

Table 4

Population-level estimates of the logistic regression model in log-odds with the standard errors and 95% credible intervals. In the table the intercept (i.e. grand mean) is listed first, then the estimates for Similarity, Turn Distance, Politeness and their interactions follow. Similarity is the change in log-odds for perfect similarity (–1 reduced, 1 perfect), Turn Distance is the change in log-odds for no turn (–1 three turns, 1 no turns), and Politeness is the change in log-odds for a neutral antecedent speaker (–1 impolite, 1 neutral). Slope coefficients whose 95% credible intervals do not include zero and are therefore treated as reliable effects are highlighted in bold.

Coefficient Estimates	posterior mean	Est.Error	I-95% CrI	u-95% CrI
Intercept	–1.42	0.34	–2.09	–0.76
Similarity	1.32	0.37	0.53	2.02
Turn Distance	0.72	0.21	0.29	1.16
Politeness	0.34	0.17	0.03	0.69
Similarity*Turn Distance	–0.14	0.18	–0.50	0.22
Similarity*Politeness	0.02	0.15	–0.27	0.32
Turn Distance*Politeness	–0.23	0.17	–0.59	0.10
Similarity*Turn Distance*Politeness	0.23	0.13	–0.03	0.49

The credible intervals of all interaction terms include zero. The most reliable interaction coefficient is the three way interaction coefficient ( $\widehat{\beta }$ = 0.23, CrI:[–0.03, 0.49]). In fact, the coefficient is 96% likely to be greater than zero predicting an increase in log-odds for perfect similarity, zero intervening turns and a neutral antecedent speaker. A model for which additive usage included all linguistic tools (besides additives) that were used to refer back to the antecedent utterance revealed almost identical results, see Appendix 2. We compared the expected log predictive density of the full interaction model to models with reduced interaction terms, a main effects only model and a model that only included Similarity and Turn Distance and their interaction as predictors. Model comparison was carried out via PSIS-LOO approximation (Vehtari et al. 2015; 2017)) which disclosed that the model including all predictors and their interactions had the highest predictive accuracy, followed by a model that included Similarity and Turn Distance and their interaction plus Politeness as main effect. The model only including Similarity and Turn Distance had the lowest predictive accuracy, as shown in Table 5. This suggests even more that the interactions between the three predictors play a crucial role in the way additives are produced.

Table 5

Experiment II: the table shows the difference in the models’ expected predictive accuracy (elpd_diff) and the standard error of the difference in elpd (se_diff) with the preferred model listed first.

	elpd_diff	se_diff
Similarity * Turn Distance * Politeness	0.0	0.0
Sim * TD + P	–0.2	1.8
Sim + TD + P	–0.4	4.8
Sim + TD * P	–0.6	4.4
Sim * P + TD	–1.9	4.5
Sim * TD	–2.3	4.2

In Figure 14, we illustrated the predicted probabilities for speakers to utter additives given our data and model. Speakers are predicted to produce additives more frequently for perfect similarity and when no turns intervene between their utterance and the antecedent utterance and least frequently for reduced similarity when three turns intervene. There seems to be a more pronounced difference between neutral (blue) and impolite conditions (red) than in experiment I for the perfect similarity conditions such that speakers are predicted to produce additives more frequently when talking to a neutral antecedent speaker as opposed to an impolite antecedent speaker.

Figure 14

Predicted probabilities of producing additive particles given the model and the data for perfect (left) and reduced similarity (right) and 0 and 3 intervening turns. The figure contrasts the probability of producing additives when faced with a neutral antecedent speaker (blue) with an impolite antecedent speaker (red).

As was previously mentioned, using a forced-choice task, we can no longer speak about solely content-based similarity, since presenting participants with formulations also introduces some degree of syntactic similarity. Looking at the relative frequencies of additives in the perfect similarity condition, it seems that syntactic similarity is taken into account by participants. For example, for Order Item 1, see (24), for which participants were asked to order a Chardonnay using the same formulation as the antecedent speaker, participants used additives in 61% of the cases. In contrast, for Order Item 4, see (27), for which the formulation of the pre-determined choices deviated slightly from the antecedent utterance, participants used additives only 47% of the time. We have to leave it for future research to look into the roles that content- versus syntactic-similarity play in additive production.

Again, the focus of this study was primarily to investigate the difference between environments in which additive usage is obligatory (perfect similarity) versus environments in which it is not (reduced/no similarity). This distinction is however coarse, and we looked into differences within the group of non-obligatory environments. As was mentioned above, we ran a further analysis in which we treat the factor Similarity as a three level predictor (perfect similarity, partial similarity, no similarity). By doing so, we are able to look at differences between environments in which the production of additives is obligatory (perfect similarity), optional (partial similarity) or not needed (no similarity) according to the Obligatory Implicature account. We re-ran the same model as before only this time with Similarity as a three level factor which was sum-coded, as shown in Table 6.

Table 6

Experiment II: Contrast coding for the three-level Similarity factor.

	Similarity1	Similarity2
perfect	1	0
dissimilar	0	1
partial	–1	–1

1. (29)

1. Partial Similarity (antecedent speaker: £15 and wine)

1.  
1. a.

1. I gave £15 and some chocolate.

1.  
1. b.

1. I gave £15 too but bought him some chocolate instead.

1.  
1. c.

1. I gave £25 and whisky.

1. (30)

1. No Similarity (antecedent speaker: a pint of Heineken)

1.  
1. a.

1. I’d like a pint of Stella Artois, please.

1.  
1. b.

1. I’d like a pint of Stella Artois too, please.

1.  
1. c.

1. I’d like a Martini, please.

Recall that for previous analyses, the category ‘reduced similarity items’ contained partial similarity and no similarity items. Participants had the option to choose between three utterances: an utterance with too, an utterance without too, and an incorrect response, as shown in (29–30). Partial similarity and no similarity differ from each other in that too can still be felicitously used in the partial condition but not in the no similarity condition.

The output suggests that, averaging over the other effects, perfect similarity led to an increase in log-odds of additive production ( $\widehat{\beta }$ = 1.91, CrI:[1.03, 2.69]), and in contrast, dissimilarity led to a decrease in log-odds of additive production ( $\widehat{\beta }$ = –2.07, CrI:[–2.96, –1.03]), as shown in Table 7. Partial similarity led to an increase in additive production but less so than perfect similarity (approximate increase: 0.16 in log odds). The 95% credible interval for Politeness includes zero and is no longer reliable.

Table 7

Experiment II of Similarity as a three-level factor. Population-level estimates of the logistic regression model in log-odds with the standard errors and 95% credible intervals. In the table the intercept is listed first, then the estimates for Similarity, Turn Distance, Politeness and their interactions follow. Slope coefficients whose 95% credible intervals do not include zero and are therefore treated as reliable effects are highlighted in bold. Similarity1 is the difference between intercept and the perfect similarity condition, Similarity2 is the difference between intercept and the dissimilar condition. The difference between the intercept and the partial similarity condition can be calculated as follows: 1.91 * (−1)+(−2.06) * (−1) = 0.15.

Coefficient Estimates	posterior mean	Est.Error	I-95% CrI	u-95% CrI
Intercept	–2.07	0.35	–2.75	–1.38
Similarity1	1.91	0.42	1.03	2.69
Similarity2	–2.07	0.48	–2.96	–1.03
Turn Distance	0.74	0.26	0.23	1.28
Politeness	0.34	0.22	–0.09	0.79
Similarity1*Turn Distance	–0.17	0.25	–0.67	0.33
Similarity2*Turn Distance	–0.31	0.36	–1.03	0.40
Similarity1*Politeness	0.01	0.24	–0.46	0.48
Similarity2*Politeness	0.07	0.35	–0.61	0.80
TurnDistance1*Politeness	–0.37	0.23	–0.84	0.08
Similarity1*Turn Distance*Politeness	0.36	0.23	–0.09	0.81
Similarity2*Turn Distance*Politeness	–0.37	0.36	–1.10	0.32

4.1 Summary

In line with the comprehension results of Kim (2015) and Chen & Husband (2018), our results suggest that distance influences the extent to which additives are obligatory. Extending prior findings on distance that use measures of textual distance, we found that speakers use additives more frequently as the distance in dialogue turns decreases: They use more additives when their conversational turn immediately precedes the antecedent turn. These results additionally shed more light on how immediately a suitable antecedent has to precede a speaker’s utterance in order for additives to be used felicitously. While it is true that immediately preceding antecedents did elicit a higher rate of additives, speakers still occasionally used additives for an antecedent separated by three intervening turns.

With regards to Similarity, our results are in line with what has been found for comprehension (Amsili et al. 2016): additives were used more in the perfect similarity condition. Taking Turn Distance and Similarity together, additives were most frequently produced when the antecedent directly preceded the host and both were highly similar – which should be a context with the strongest exhaustivity implicature. However, even in this context, the probability of speakers producing additives was rather low: on average only 68% (in experiment II).

Regarding the factor Politeness, in experiment II we found that speakers use additives more frequently when speaking after a neutral antecedent speaker and omit additives more frequently when speaking after an impolite antecedent speaker. This may indicate that omitting additives in contexts that give rise to an exhaustivity implicature can be a strategic way to diverge from other interlocutors. The contrast or contradiction that arises by not blocking the exhaustivity implicature may highlight a contrast on the social level. One explanation for why Politeness was overall the weakest and most inconsistent factor in our study could be due to the way we implemented the politeness factor. As suggested by an anonymous reviewer, by adding impolite material as a subordinate clause or a separate clause preceding for example the order, the additive might simply be avoided because the participant (henceforth Speaker B) does not want the subordinate clause (‘Although you served me white wine last time’) to be part of the presupposition (not because it is impolite but because it is not true). Consequently, a response such as ‘I’d like Chardonnay, too.’ could have been ambiguous between two readings: speaker B is committing themselves or not to the subordinate clause.

For a start, we think that there are several reasons to doubt that the preceding ‘although’ clause can be part of this presupposition. If this were to be available, utterances such as ‘Me too’ – uttered by Speaker B after Speaker A’s utterance ‘Although you served me warm white wine last time, I’d like a glass of Chardonnay’ – would in principle also be ambiguous between readings in which speaker B presupposed that speaker A had been served warm white wine last time and one in which speaker B presupposed that speaker B had been served warm white wine last time, which we think is not evident. Moreover, if A were to utter ‘Although speaker B thinks I’ve given up drinking, I’d like a glass of Chardonnay’, for B to utter ‘Me too’ would be paradoxical, which again conflicts with our intuitions. If our judgment on this point is incorrect and the ‘although’ clause can be part of the presupposition of too in our materials, then we agree that speaker B may refrain from using too if they do not endorse the content of the ‘although’ clause. However, in the ‘warm white wine’ example, speaker A is reporting a (claimed) fact in the ‘although’ clause, and it is not entirely clear why speaker B should refuse to endorse this fact other than as an expression of social divergence.

Overall, the effect of Politeness on the production of additives needs further investigation. While the different outcomes of experiments I and II may be due to sparse data in experiment I, replication studies are necessary not only to explore Politeness further but also to shed more light on the possible effect that open versus forced-choice tasks have on production data. Furthermore, we only investigated one potential reason for speakers to diverge from an antecedent speaker, namely when they behave impolitely. There may be other reasons with a potentially greater influence on whether speakers diverge or not such as when the antecedent speaker expounds controversial, false or immoral opinions. However, such reasons are difficult to test in an experimental setting due to ethical considerations.

4.2 Low additive frequency

For both experiments, the additive usage in obligatory environments was rather low even when the antecedent utterance directly preceded the host utterance and both were highly similar in content (experiment I) or content and formulation (experiment II). The low frequency might not be as surprising for experiment I, for which we used a free-text task. Here, participants could use other linguistic means to block the exhaustivity implicature, e.g. phrasing their utterance differently from the antecedent speaker utterance or using lexical items such as and at the beginning of their utterance to flag a similar addition to the dialogue. The relatively low additive frequency in obligatory environments in experiment II contrasts however more directly with predictions of the Obligatory Implicature account. Recall that in experiment II participants were directly presented with utterance choices and offered the use of additives. Thus, in obligatory environments participants saw the antecedent utterance followed by two syntactically and semantically identical response options either containing or not containing too.

We want to briefly address possible reasons as to why additive production may have been relatively low, which might reconcile our findings with the predictions of the Obligatory Implicature account. One potential reason could be the dialogue setting. Bade (2016) claimed that exhaustivity may be reduced in settings in which more than two interlocutors are involved, based on two studies investigating auch (German too). More specifically, in study 1 Bade (2016) investigated the acceptability of sentences containing versus not containing too in a dialogue setting, see (31).

In contrast, in study 2 Bade (2016) tested the acceptability of continuations containing or not containing too following a context sentence, see (32), a setting which could mirror a narrative or the contribution of a single speaker.

Bade found that sentences not containing too were judged less acceptable than sentences containing too in both studies (study 1: mean = 3,62 on a 5-point scale, study 2: mean = 2,1 on a 7-point scale), but most crucially that sentences without too were judged less acceptable in study 2 than study 1. Besides arguing that contradictions between conversational partners are more acceptable than contradictions within a single discourse, exhaustivity may be reduced in dialogue settings because multiple contributions of more than one speaker are expected to be possible partial answers to the QUD.

If the distinction between dialogue contexts and single speaker contribution contexts holds up for production, one would expect higher additive production in studies looking at additive production in narration produced by one speaker – such as in Eckhardt & Fränkel’s 2012 study – than in studies looking at additive production in dialogue like settings – such as in our study. Eckhardt & Fränkel (2012) investigated the production of auch and wieder (German too and again) by asking participants to describe four pictures of a comic strip one after another. The pictures illustrated two protagonists that would occasionally perform similar actions at different times such as brushing their teeth. Participants were either instructed to describe the comic strip as if they were telling a children’s story or they were instructed to describe what happened at specific times, similar to a protocol. Focusing on the relevant narration condition, participants seemingly produced additives and iteratives on average 55% of the time which is similar to the additive frequency of experiment I (∼51% in the neutral antecedent speaker/perfect similarity/0 turn distance condition) and lower than the additive frequency of experiment II (∼67% in the neutral/perfect sim./0 TD condition). Thus, it remains open whether additive insertion is more obligatory in narration or for the contribution of a single speaker versus in dialogue settings. Since the experimental designs of Eckhardt & Fränkel’s 2012 study and the current study differ to a great extent, we leave it to future research to investigate differences in additive production for different contexts.

Another point that is worth highlighting is the role of focus in our experiment. Pragmatically, focused material generally addresses the explicit or implicit Question Under Discussion (QUD). Following Roberts (1996), the QUD corresponds to the current discourse topic. Focus may also be introduced by prosodic stress such that the kind of exhaustivity implicature that arises may depend on which constituent of the host sentence is prosodically stressed and thereby focused (e.g. Rooth 1985). For example, in (33a) too associates with the prosodically stressed ‘I’ making the speaker the exhaustive answer to the QUD Who noted down that she’s due to start in January? In contrast, in (33b), ‘she’ is prosodically marked making ‘her’ the exhaustive answer to the QUD Who’s due to start in January?

We did not provide participants with audio recordings in our experiments. In experiment II with the pre-determined choices, participants therefore would have had to assign any implicit prosody individually, e.g. participant1 may have placed focus on ‘I’ (33a) and participant2 on ‘she’ (33b). Giving rise to different implicatures may have led to different assessments by participants of whether there was a suitable antecedent in the preceding discourse which would in turn induce some variation in additive use between participants.

While the placement of individual focus is possible, we argue that by presenting the overall discourse topic, we reduced such variation to some extent. Recall that in our study we set the discourse topic for each experimental item headlining each picture of a given conversation, such as ‘Ordering drinks’ or ‘Discussion about when the new colleague is starting’ but not an explicit QUD. This might have generated a variety of corresponding QUDs such as Who orders what? In general, QUDs that permit one correct answer lead to a stronger exhaustivity effect than QUDs that permit partial answers or multiple contributions. The majority of possible QUDs in our study do permit partial answers; in fact, partial answers are expected. For example, the possibly generated QUDs Who orders what? for ‘order’ items permits partial answers and multiple contributions. In contrast, for the ‘talk’ items (items 7 and 8) possible implicit QUDs may be associated with one correct answer. Both are about the discussion of when a specific event takes place, which gives rise to implicit QUDs such as When will the new colleague start? (item 7) and At what time is next week’s meeting? (item 8). Just looking at the relative frequencies in Figure 15, however, there is no indication of a trend in the expected direction, i.e. more frequent additive production for items 7 and 8 than for the remaining conversations. In fact, item 7 seems to be an outlier for other reasons, since additive production was lower than for other items.¹⁵

Figure 15

Relative Frequencies (y-axis in proportion) of additive production for experiment II by item (x-axis).

On a related note, multiple Wh-questions such as Who orders what? may give rise to contrastive topic and focus contours (c.f. Büring 2016; Tomioka 2009). More specifically, for a question such as (34a) I would be marked as a contrastive topic and glass of Chardonnay as focus. The contrastive topic + focus contour leads to the following reading: whereas the focus excludes all possible alternatives (there is nothing else that the speaker would like to order other than a glass of Chardonnay), contrastive topic implies that other speakers might want to order a glass of Chardonnay. Such a reading would make the insertion of additives not necessarily obligatory and could explain the relatively low additive production.

While we can only speculate about why additive production was rather low, this discussion opens up exciting possibilities for future research, e.g. investigating the effect of exhaustivity on additive production in dialogue-like structures by manipulating the number of speakers and QUD-type.

4.3 A speaker model of additive production

The following section aims to introduce a possible way to model the production of additives in dialogue-like structures by emphasising the importance of their (i) anaphoric component and (ii) discourse managing properties. Regarding (i), the processing or comprehension of additives may involve resolving the anaphoric dependency between host and a pre-mentioned antecedent. From the production perspective, the anaphoric component of additives makes the presence of a suitable antecedent necessary and involves keeping track of what material has previously been mentioned. Keeping track of what has been previously mentioned should be effortless when the antecedent directly precedes the speaker’s utterance. However, producing additives may come with a working memory cost, such that keeping track of what information has already been mentioned may be more difficult with increasing conversational turns/time. Note that this may be due to memory decay and/or interference of contributions/sentences between antecedent and host (see Chen & Husband (2018) for an investigation of the processing of additives in terms of cue-based retrieval). Thus, not producing additives may happen unintentionally and may happen more if the turn with the suitable antecedent happened longer ago. The observed effect of Turn Distance seems to corroborate this: speakers more frequently used additives when their turn immediately preceded the antecedent turn.

Independently of the number of turns intervening antecedent and host, based on Obligatory Implicatures, we can assume that further contextual factors (e.g. Similarity, QUD-Type, sentence structure) determine the strength of the exhaustivity implicature and thereby the pressure on speakers to produce additives. However, we argue that (ii) the discourse managing properties should be taken into account to fully capture additive production. By discourse managing properties of additives we mean that additives can be used by speakers to signal ontological control (i.e. the awareness of how content is organised in the discourse). The idea of ontological control is based on Eckhardt & Fränkel (2012)’s study which found that interlocutors more frequently produced additives when writing a story than when writing a protocol. Eckhardt & Fränkel (2012) claimed that the obligatoriness of additives depends to some extent on the contextual requirements for the speaker to signal control over ontology – i.e. speakers are aware of the way the content of different utterances is related and structured in the discourse. Omitting additives in textual environments in which the requirements to signal control over ontology are high, e.g. in narratives, is claimed to lead to utterances which are detached from the preceding discourse and the undertone that the speaker did not plan their narrative beforehand.

One could assume that spontaneous speech does not require the same standard of signalling control of ontology as is necessary for narratives. Instead, engaging explicitly in discourse management in conversation may be seen as an occasional, cooperative effort of interlocutors. For example, to make it easier for the waiter who is noting down the orders, speakers use additives to signal that something similar has been ordered before. Seeing additives as discourse managing tools may explain why additives were not always used in contexts that should give rise to a relatively strong exhaustivity implicature (i.e. when a highly similar antecedent directly preceded the host): speakers might not always deem it necessary to explicitly engage in discourse management.

Regarding the factor Politeness, the use of additives as a cooperative attempt to participate in discourse managing may be perceived as a convergence move that happens by default. Disengaging from this process may be due to a speaker’s attempt to diverge from the antecedent speaker. Thus both Turn Distance and Politeness may account for instances when speakers choose not to produce additives. Whereas Turn Distance may explain unintentional omission of additives, Politeness may explain intentional omission of additives even with contexts usually associated with giving rise to an exhaustivity implicature.

A few responses in experiments I and II suggest that, for some participants, discourse management had priority over diverging from the antecedent speaker by omitting additives: after having formulated an utterance containing an additive, some participants continued to express their disagreement with the antecedent speaker’s behaviour in a second sentence, as seen in (28). In this way participants remained cooperative towards the waiter and the other interlocutors. This way of dealing with an impolite speaker may be one of the reasons for why we did not find an effect of Politeness in experiment I. Since participants formulated their own utterances in experiment I, they were possibly more likely to follow this strategy than participants in experiment II who would most likely choose pre-formulated utterances.

4.4 Limitations and open questions

Potential limitations of our study include the experimental design and sample size. As previously mentioned, we used only a small number of experimental items (eight), and the observed effects could be due to the unique characteristics of these items and may not generalise to other conversational settings and topics. We also used a relatively low number of experimental trials: each participant saw each condition only twice, whereas typically psycholinguistic studies use around four trials per participant per condition. We chose this low number of trials to create a realistic interaction scenario (comprising one coherent conversation) with the aim of gathering data representative of actual language use. We would also argue that the use of a low number of trials increases participant engagement and limits the opportunity for the participants to develop task strategies, which would be detrimental to statistical power (e.g. Arehalli & Wittenberg 2021; Brehm et al. 2021). Recent single-trial experiments (e.g. von der Malsburg et al. 2020; Laurinavichyute & von der Malsburg 2022; 2024; Winter & Duffy 2020; Thibodeau & Boroditsky 2024; Hassemer & Winter 2018) or experiments with low number of trials (e.g. Rohde et al. 2021) combat this issue. However, it must be acknowledged that recent single-trial experiments have typically used appreciably more participants (∼25000 (von der Malsburg et al. 2020), ∼5500 (Laurinavichyute & von der Malsburg 2024), ∼200–300 (Winter & Duffy 2020), ∼185–485 (Thibodeau & Boroditsky 2024), ∼185–345 (Hassemer & Winter 2018) to ∼170 participants (Rohde et al. 2021)). Further research is needed to establish optimal sample sizes for experiments with few items, and hence our results should be interpreted with caution in this regard.