Exploring the effects of rhyme and meter

One aim of the present studies was to explore how L1 and L2 English comprehenders would process and interpret anaphoric ambiguities in the presence of competing cues. To that end, we considered contexts where the subject would normally be the preferred referent; yet, we manipulated the salience of an alternative candidate (object) by having it be a rhymed antecedent in rhyming and metered poem-like texts.

Previous studies have considered other prominence-enhancing devices to manipulate the salience of antecedents such as clefted focus (Cowles et al., Reference Cowles, Walenski and Kluender2007; Kaiser, Reference Kaiser2011) and pitch accents (Schafer et al., Reference Schafer, Camp, Rohde, Grüter, Carlson, Clifton and Fodor2019, Reference Schafer, Takeda, Rohde and Grüter2015). Unlike local cues, little attention has been paid to contextualized, global prosodic features that are activated during silent reading (see Clifton, Reference Clifton, Frazier and Gibson2015 and Breen, Reference Breen2014 for reviews).

End rhyme in verse constitutes a key element of stanza structure; it involves regulated patterning based on the repetition of sound segments found at the end portion of verse-final words; words that rhyme share the same nucleus in the final stressed syllable, optionally codas too including any further unstressed syllable that follows (Fabb, Reference Fabb2015). This repetition of accented syllabic nuclei contributes to the phonological salience of rhymed words (e.g., Fabb, Reference Fabb1999; Obermeier et al., Reference Obermeier, Menninghaus, von Koppenfels, Raettig, Schmidt-Kassow, Otterbein and Kotz2013). Additionally, according to Rickert (Reference Rickert1984, p.1), this sound-based repetition “impinges on the reader’s awareness,” in the sense that “as the rhyme becomes increasingly conspicuous, it commands added attention.” Thus, given this attention-attracting property, rhyme may even induce a “noticing” effect. Related to the above, rhymed words have been found to be predictable (Read et al., Reference Read, Macauley and Furay2014; Read & Regan, Reference Read and Regan2018) and easy to remember (Goldman et al., Reference Goldman, Meyerson and Coté2006; Johnson & Hayes, Reference Johnson and Hayes1987; Király et al., Reference Király, Takacs, Kaldy and Blaser2016).

All these effects are maximized when rhyme is paired with meter in verse as attention is drawn to lyrical properties of language (Goldman et al., Reference Goldman, Meyerson and Coté2006). Whereas rhyme regulates form patterning at a larger timescale across verses, meter structures perceptual input at a smaller timescale within verses (Fabb, Reference Fabb2009; Obermeier et al., Reference Obermeier, Menninghaus, von Koppenfels, Raettig, Schmidt-Kassow, Otterbein and Kotz2013). In metered poetry, repetitive sequences of stressed and unstressed syllables are found in metrical feet that regulate the meter of the verse-line (Fabb & Halle, Reference Fabb and Halle2008). This systematized alternation of syllabic stress promotes recall of linguistic material (Boucher, Reference Boucher2006; Brower, Reference Brower1993) and facilitates language processing by making loci of stress predictable and salient (Kotz & Schmidt-Kassow, Reference Kotz and Schmidt-Kassow2015; Pitt & Samuel, Reference Pitt and Samuel1990; Roncaglia-Denissen et al., Reference Roncaglia-Denissen, Schmidt-Kassow and Kotz2013; Rothermich & Kotz, Reference Rothermich and Kotz2013; Rothermich et al., Reference Rothermich, Schmidt-Kassow and Kotz2012).

Taken together, the phonological and rhythmic regularities found in rhyming and metered poetry promote perceptual (prosodic) fluency (Menninghaus et al., Reference Menninghaus, Bohrn, Knoop, Kotz, Schlotz and Jacobs2015). Once such recurring patterns have been identified, any disruptions to the established, and thereafter, expected structure lead to processing costs (for costs caused by metrical violations see, e.g., Breen & Clifton, Reference Breen and Clifton2011; Breen & Clifton, Reference Breen and Clifton2013; for costs induced by rhyme violations see Hoorn, Reference Hoorn, Kruez and MacNealey1996; Liu et al., Reference Liu, Jin, Wang and Xin2011). However, perceptual fluency does not imply conceptual fluency; rather, a trade-off between the two has been suggested (Menninghaus et al., Reference Menninghaus, Bohrn, Knoop, Kotz, Schlotz and Jacobs2015). This is because overattendance to formal surface elements can result in shallow processing and impact semantic comprehension (Blohm et al., Reference Blohm, Wagner, Schlesewsky and Menninghaus2018; Goldman et al., Reference Goldman, Meyerson and Coté2006; Menninghaus et al., Reference Menninghaus, Bohrn, Knoop, Kotz, Schlotz and Jacobs2015; Wallot & Menninghaus, Reference Wallot and Menninghaus2018).

Finally, it is important to note that the effects of rhyme and meter discussed above have mostly been examined with native, rather than non-native speakers. To the extent that rhyme awareness has been tested in the L2, it has mostly been studied at the word level (e.g., rhyme judgment tasks as in Bassetti et al., Reference Bassetti, Mairano, Masterson and Cerni2020), while its role during sentence processing, let alone disambiguation in poetic contexts, has remained unexplored. Regarding meter, some studies have made comparisons between L1 and L2 speakers’ brain responses to metrical structure (Roncaglia-Denissen et al., Reference Roncaglia-Denissen, Schmidt-Kassow, Heine and Kotz2015; Schmidt-Kassow et al., Reference Schmidt-Kassow, Rothermich, Schwartze and Kotz2011); the findings of Roncaglia-Denissen et al. (Reference Roncaglia-Denissen, Schmidt-Kassow, Heine and Kotz2015) revealed that L1 Turkish L2 German speakers did not take advantage of rhythmic regularity as monolingual German speakers did when processing syntactically ambiguous structures. These results are not surprising; the wider literature on prosodic cue sensitivity in the L2 so far suggests that non-native comprehenders may not take into account prosodic cues in the same way as L1 speakers; rather, effects are typically absent, weaker, or delayed in L2 processing (Foltz, Reference Foltz2021; Nakamura et al., Reference Nakamura, Arai, Hirose and Flynn2020; Perdomo & Kaan, Reference Perdomo and Kaan2021; Schafer et al., Reference Schafer, Takeda, Rohde and Grüter2015; Schmidt et al., Reference Schmidt, Pérez, Cilibrasi and Tsimpli2020).

The cause behind the lack or reduction of L2 prosody effects is difficult to pinpoint, and alternative explanations have been entertained in previous literature; these include L2 perceptual limitations, an issue with incorporating prosodic cues into the representations constructed online, or a difficulty in using prosody in conjunction with other types of information (for reviews, see Mennen & De Leeuw, Reference Mennen and De Leeuw2014; Pratt, Reference Pratt, Fernández and Smith Cairns2017). Complicating matters further, it has been observed that L2 participants do not make use of prosodic cues when engaged in certain types of processing, such as memory retrieval (Schmidt et al., Reference Schmidt, Pérez, Cilibrasi and Tsimpli2020) and reference prediction in the L2 (Perdomo & Kaan, Reference Perdomo and Kaan2021), even though they rely on the same or equivalent cues in their L1 to perform these operations. Similar results have also been reported in L2 ambiguity research, which is most relevant for present purposes. Nakamura et al. (Reference Nakamura, Arai, Hirose and Flynn2020) found that in contexts where two referents were available to resolve a type of global ambiguity, namely prepositional phrase attachment, prosodic prominence cues (contrastive pitch accents) did not have an effect on L2ers, unlike in native speakers.

Before proceeding to our hypotheses, it is worth noting that most of the research described above has manipulated overt prosodic information. All this evidence was taken into account and informed our hypotheses regarding effects of implicit prosodic cues during silent reading, which is the focus of the present studies. Henceforth, when discussing prosodic cues, we specifically refer to silent prosody.

Hypotheses

Design

Two web-based self-paced reading experiments were designed to test which of the hypotheses formulated above would enjoy empirical support. In Study 1, native English speakers were recruited; in Study 2, we tested L2 English speakers with a null subject L1, namely Greek, following Cunnings et al. (Reference Cunnings, Fotiadou and Tsimpli2017). To account for individual variability, we selected different tasks to compute comprehender-dependent measures for the two groups.

L1 speakers were assessed on memory-related tasks, a print exposure task and a rhyme judgment task. Because both verbal and non-verbal WM contribute to individual variability in ambiguity resolution (Swets et al., Reference Swets, Desmet, Hambrick and Ferreira2007), we chose to include the Reading Span and the Spatial Span task used in that study. Additionally, we assessed WM in the auditory modality using the Backward Digit Span, formatted and administered in a similar fashion as the Digit Span tasks in the Cambridge Neuropsychological Test Automated Battery (CANTAB)Footnote ² . The Forward Digit Span task was also administered as it taps into phonological short-term memory, and it is thought to be associated with rhyme cue sensitivity (Classon et al., Reference Classon, Rudner and Rönnberg2013). Following Arnold et al. (Reference Arnold, Strangmann, Hwang, Zerkle and Nappa2018) and Langlois and Arnold (Reference Langlois and Arnold2020), we used the ART (Acheson et al., Reference Acheson, Wells and MacDonald2008; for adaptations see Martin-Chang & Gould, Reference Martin-Chang and Gould2008 and Moore & Gordon, Reference Moore and Gordon2015) as a proxy for print exposure. A self-report measure, namely the three-part questionnaire (Reading, Writing, and Comparative Reading Habits) developed by Acheson et al. (Reference Acheson, Wells and MacDonald2008) was also used to derive a composite measure of print exposure which was used in analyses (henceforth Print Exposure composite). Finally, in order to assess whether rhyme awareness influences pronoun interpretative preferences (given the rhyme cue on the nonsubject antecendent in our stimuli), we used a Rhyme Judgement task (Johnston & McDermott, Reference Johnston and McDermott1986) which was modeled on materials used in Frisson et al. (Reference Frisson, Koole, Hughes, Olson and Wheeldon2014) and Zecker et al. (Reference Zecker, Tanenhaus, Alderman and Siqueland1986), while the administration procedure was informed by findings of Classon et al. (Reference Classon, Rudner and Rönnberg2013).

In Study 2, L2 speakers completed the same tasks as specified above; however, for reasons explained under Study 2, L2 speakers did not complete the ART and Spatial Span task. Finally, we assessed proficiency levels of L2 speakers using the English Level Placement Test by the British CouncilFootnote ³ .

The results of Study 1 and Study 2 are first discussed separately and then compared in a subsequent section. We decided to analyze the data in this way because we first wanted to examine how individual differences affect performance within each group. Therefore, we decided to first analyze L1 and L2 data separately while taking into account the unique set of comprehender-dependent measures that were computed for each group and then compare between L1 and L2 results in the main self-paced reading experiment that both groups completed.

Participants

Thirty-nine L1 English speakers (21 female, M_AGE = 21.3; SD_AGE = 2.08) participated in the study. Twenty-one of them were UK-born university students recruited through the Prolific platformFootnote ⁴ . The remaining 18 were students at the University of Cambridge, who were born in the UK (N = 17) or Ireland (N = 1). All provided their informed consent to participate in the study and received £15 as payment. The study has received ethical approval by the ethics committee of the Modern and Medieval Languages and Linguistics faculty at the University of Cambridge.

Materials

The critical items were 16 poem-texts which contained anaphoric ambiguity. These items were created in two different conditions (R&M-consistent and R&M-disrupted), and participants were presented with 8 items for each one. An example of the two conditions can be found in Table 1; a list of all items can be found in Appendix A.

Table 1. Example of critical item

Out of the five verses of each critical poem-item, the first two established an expectation for a consistent meter and rhyming scheme. These first two lines remained unchanged across conditions, as did the last two. Importantly, the third line contained two proper names, one being the subject (SUB) and one being the object (OBJ: line-final) of a main clause; either one could be the referent of the ambiguous pronoun found within a dependent clause on the 4^th line. Crucially, in half of the items, the metrical structure and rhyming scheme were invariable across all 5 verses (OBJ: rhyming; R&M-consistent), whereas, in the other half, they were disrupted on the 3^rd line (OBJ: non-rhyming; Condition: R&M-disrupted).

In terms of internal structure, each constituent verse of the poem-items consisted of seven syllables. In the R&M-consistent condition, the 3^rd, 5^th, and 7^th syllable were stressed on all lines, whereas in the R&M-disrupted condition the 3^rd, 5^th, and 7^th syllable were stressed on all but the 3^rd line (disrupted). To make this disruption possible, the two monosyllabic proper names in the R&M-consistent condition were replaced by disyllabic ones in the R&M-disrupted version of the stimuli, while the line-initial adverb of frequency in the former condition was eliminated in the latter.

It should be noted that metrical consistency on the 3^rd line could have been disrupted by changing just one of the candidates between conditions (e.g., by making the non-rhyming OBJ candidate in the R&M-disrupted condition be disyllabic while keeping the same SUB candidate as it was in the R&M-consistent condition). This option was dispreferred as it would have meant that in just one of the conditions the SUB and OBJ would necessarily differ in terms of syllable count, and probably character length too. This could have affected interpretative preferences, as well as the reading time results between conditions.

Furthermore, the rhyming scheme remained invariable across all verses in the R&M-consistent condition (AAAAA), whereas in the R&M-disrupted condition the line-final word of the 3^rd verse did not rhyme with the rest (AABAA). The rhyming words in each poem-text exhibited substantial phonological similarity in the rime portion (near-rhymes were avoided where possible), yet word endings were not always orthographically identical. Importantly, the line-final words on the 3^rd and 4^th verse, where the OBJ disambiguation candidate and the dependent clause verb could be found respectively, exhibited adequate orthographic overlap (e.g., Rose-pose, or minimal difference as in Brooke-cook)Footnote ⁵ . This phonemic and graphemic correspondence between the two words was expected to increase the prominence of the rhyming candidate.

To ensure that the items would be comprehensible and plausible enough given their poetic particularities, the materials were normed by an independent group of native English speakers (N = 38; 33 females) prior to the launch of the main study. These participants were asked to rate 32 items which involved anaphoric ambiguity in terms of plausibility and comprehensibility on a scale of 1 (very implausible/incomprehensible) to 7 (very plausible/comprehensible). Only 16 items that received ratings above 4 for both plausibility and comprehensibility were selected. These items were then further amended and checked again for plausibility and comprehensibility by a native speaker of English with a postgraduate linguistics degree. The rater assigned the maximum value (7) to all items in terms of plausibility; none of the items were rated below 4 for comprehensibility (M = 5.3, SD = 0.6, range = [4, 6]).

Alongside the 16 critical anaphoric ambiguity poem-items, participants in the main reading experiment also read: a) 16 relative clause ambiguity items, b) 32 items which involved local ambiguity and were not metered or rhyming, c) 32 items that contained alliteration (N = 16) and vowel assonance (N = 16), none of which were ambiguous, and d) 16 unambiguous filler items containing iconic and non-iconic “after” and “before” clauses, respectively. Thus, participants read a total of 112 five-line poem-like texts.

After each text, participants were asked to specify which character performed the action described by the dependent clause verb on the 4^th line (see Table 1). Since the verb had the ambiguous pronoun as a subject, they essentially had to indicate which one of the candidates found on the 3^rd line was its referent. Alternatively, they could select the fallback response option “Other(s).” Care was taken to avoid repeating the dependent clause verb in the question as it rhymed with the OBJ candidate in the R&M-consistent condition, and this could have amounted to an imbalanced extra cue; instead, alternative formulations of the questions were opted for, where feasible, to allow comparability between the two conditions.

Procedure

A web-based reading experiment was designed which employed the self-paced (line by line) moving-window paradigm (Just et al., Reference Just, Carpenter and Woolley1982). The reading experiment as well as the additional tasks were programmed using the JavaScript library JsPsych (de Leeuw, Reference de Leeuw2015) and then launched online, hosted on a university server. A remote testing method was used (Leong et al., Reference Leong, Raheel, Sim, Kacker, Karlaftis, Vassiliu and Kourtzi2022) which involved participants completing the two-hour study while being on live (audio-only or audio and video) call with the first author and main experimenter.

Once a pre-study form and the three-part questionnaire for print exposure had been completed, participants would start the main reading experiment, after having gone through three practice items. The main reading experiment was split in five blocks. The first four blocks contained 22 texts each, while the last one consisted of 24 texts. After getting through each block, participants had the opportunity to take a short break. Additionally, after the first block, participants would do the Reading Span task; after the second block, they were tested on the Spatial Span task; following the third block, they did the Forward and Backward Digit Span tasks; after the fourth block, they did the ART; finally, upon completion of the fifth block, they did a novel Text Completion task (to be discussed in a future report) and the Rhyme Judgement task. We structured the web-based experimental sessions in this way to prevent participant fatigue and loss of interest caused by the long and repetitive nature of the self-paced reading experiment. In between breaks, participants would rest and also interact with the experimenter to complete the additional tasks, thus ensuring continued engagement throughout the session. Additionally, we decided to keep the order of the tasks fixed so as to streamline the administration and manual scoring of oral responses that were provided to certain tasks; had the order of tasks been randomized, there would not have been sufficient preparedness to complete the above steps efficiently. Importantly, the Rhyme Judgement task came after the final block of the main reading experiment in order to avoid drawing attention to rhyme. Details on what these tasks involved, how they were adapted, administered, and scored can be found in the supplementary material (see Replication Package).

Within the blocks of the main reading experiment, participants read the texts one line at a time; at the beginning of each trial, only dashes would be visible to mask all the lines. Participants had to press a key to reveal only a single line of text each time, making their way from the first to the fifth one with each key press. Subsequently, readers would be directed to the interpretation question which they could answer by pressing a key corresponding to one of the two disambiguation candidates or the fallback option “Other(s).”

The stimuli were counterbalanced and equally distributed across two lists. List assignment and the order in which stimuli appeared was fully randomized. The order of appearance of the response options SUB and OBJ was pseudo-randomized and fixed per item; as such, in each list, for half the stimuli the OBJ would appear in the left-most position of the screen, whereas for the rest the OBJ would appear in the middle position of the screen. The fallback option “Other(s)” would always appear in the right-most position.

Data analyses

Prior to analyses, individual datasets were first checked for accuracy on the unambiguous filler items. Following Fernández’s (Reference Fernández, Heredia and Altarriba2002) methodology, native English speakers who provided an incorrect response to the question that followed the unambiguous filler items in more than 20% of cases were excluded from analyses. As a result, data from three individuals were discarded, yielding a sample size of 39.

Second, trials in which participants had selected the fallback option “Other(s)” as a response to the question for the critical items were excluded (2.2% data loss).

Third, reading time data and reaction times to the interpretation question were checked for normality (the latter were recorded as the time elapsed in milliseconds between the onset of the question trial until a response was provided via a key press and will be referred to as RTs hereafter). As a first step, a combination of winsorizingFootnote ⁶ along with log transformations was used (Nicklin & Plonsky, Reference Nicklin and Plonsky2020). If after transformations had been applied, outliers were identified using Cook’s distance, such cases were discarded (5.7% data loss).

Moreover, as is reported in the Results section, statistical models revealed great participant-level variability in pronoun interpretative preferences and processing rates. It was hypothesized that differences in reading behavior could be associated with individuals’ interpretative preferences. For instance, participants who exhibited a switch in their interpretative preferences from one antecedent to the other depending on the condition they were viewing may have been affected by heightened competition between cues, thus needing more time to process critical information. On the other hand, participants who had fixed preferences may have not considered alternative interpretations, thus needing less time. Additionally, it was deemed important to examine whether WM capacity is predictive of switching tendencies. For instance, switching between referential interpretations may be a sign of higher reading spans, while rigidity may be indicative of reduced sensitivity to formally ambiguous pronouns, a characteristic of individuals with lower spans (Nieuwland & Van Berkum, Reference Nieuwland and Van Berkum2006).

To test these hypothesized associations, a new measure called Switch was created.

This measure involves a dichotomous division (50% threshold) resulting in participants being categorized into distinct groups, namely Biased and Switchers. To explicate, participants who were recorded as Biased exhibited an overall preference (> 50%) for either the SUB or the OBJ candidate in both conditionsFootnote ⁷ . Participants who were recorded as Switchers had an overall preference (> 50%) for either the SUB or the OBJ candidate in only one condition, while in the other condition the overall preference switched to the alternative candidate. Accordingly, 24 of the participants in the L1 group were classified as Biased and 14 as Switchers. One participant who was purely balanced in their preferences (50%–50% distribution between SUB and OBJ in both conditions) was excluded from the analyses that included the Switch measure.

Analyses were performed in R version 4.2.2 using the lme4 package (Bates et al., Reference Bates, Mächler, Bolker and Walker2015). Reading times and RTs were entered as dependent variables into linear mixed effects models. The responses to the interpretation questions were entered into binomial generalized linear mixed effects models. For all dependent variables, analyses were conducted in two steps. First, models with only Condition as a predictor were run to assess effects of the R&M manipulation irrespective of covariates. Then, new analyses were performed which included covariates. For interpretative preferences, the new models included scores on the additional tasks. For reading times and RTs, the new models included scores on the additional tasks and the Switch variable, as well as line character count or word count as predictors if they improved model fit. The results reported are based on the output of the model that best fitted the data (AIC criteria were used for model comparison). In terms of contrasts for factors, deviation coding was used. In cases where significant interactions were detected, post hoc tests were run with Bonferroni p-value corrections using the R lsmeans package. In all of the above models, participants and items were included as random effects (either intercepts only or intercepts and slopes depending on whether they improved the model fit).Footnote ⁸ For model summaries, the R report package was used. Odds ratio and Cohen’s d are reported as effect size indices. The code used and the model output can be found in the supplementary material (see Replication Package).

Effects of the R&M manipulation on pronoun interpretative preferences

The percentage to which the OBJ candidate was selected in each Condition and by each Group is presented in Figure 2.

Figure 2. L1 & L2 percentage of OBJ preference by condition (CI errorbars based on the pooled mean).

In order to examine whether the two groups differed in terms of their interpretative preferences, a logistic mixed model with Condition and Group as predictors was run. Neither predictor proved significant (p’s > 0.05). Thus, in order to draw any conclusions, we rely on the separate models run for each group. To the extent that Condition had an effect, this only applied to L1 speakers, as was demonstrated by the previously reported analyses. In fact, significantly lower odds of choosing the OBJ in the R&M-consistent condition were only estimated for the L1 group; instead, for the L2 group, an increase in the odds was estimated, albeit non-significant.

Effects of the R&M manipulation on reading times and RTs

Line-by-line reading times of the L1 and L2 group are plotted side by side for comparison in Figure 3. In a linear mixed model with Condition and Group included to predict line 3 reading times, the effect of Group was significant; the L2 participants took longer to read critical line 3 (β = 0.58, 95% CI [0.43, 0.73], t(1299) = 7.80, p < 0.001; d = 1.57, 95% CI [1.16, 1.98]). Additionally, the effect of Condition was significant (β = 0.07, 95% CI [0.02, 0.12], t(1299) = 2.84, p = 0.005; d = 0.196, 95% CI [0.05, 0.33]), suggesting that the R&M-consistent condition led to delays when both L1 and L2 participants were processing line 3. In the case of line 4 reading times, Condition was not a significant predictor (p > 0.05). There was only a significant effect of Group, as L2 participants took longer to read line 4 (β = 0.55, 95% CI [0.38, 0.72], t(1301) = 6.33, p < 0.001; d = 1.45, 95% CI [0.98, 1.92]). Importantly, there were no significant interactions in any of the models, indicating that Condition had similar effects in the L1 and L2 group.

Figure 3. Mean reading times by group and condition (SE error bars).

With regard to the RTs to the interpretation question, a significant effect of Group was observed; L2 participants took longer to indicate a preference (β = 0.33, 95% CI [0.19, 0.47], t(1301) = 4.58, p < 0.001; d = 0.75, 95% CI [0.42, 1.08]). Although the effect of Condition was not significant, the interaction between Group (L2) and Condition (R&M-consistent) was statistically significant (β = 0.12, 95% CI [0.02, 0.22], t(1301) = 2.47, p = 0.014). Post hoc comparisons revealed that L2 participants took significantly longer to provide a response in the R&M-consistent condition compared to the R&M-disrupted one (β = 0.06, p = 0.0475; d = 0.153, 95% CI [0.001, 0.303]). There were no differential effects of Condition in the L1 group (p > 0.05).

Hence, the L2ers had a slower reading rate compared to L1 participants. This result is not surprising; L2 participants required more time to read the whole texts, not just the critical lines. Our main interest was to examine whether Condition had the same effect for both groups or whether the two groups behaved dissimilarly when reading the two different versions of the texts. In terms of reading rate, there were no interactions between Group and Condition, suggesting similar processing across the two groups. However, given what was already known based on the separate models for the L1 group and L2 group, the slow-down for line 3 proved to be significant only for the L1 group, not for the L2 group. As such, although the directionality of effects is the same for both groups (positive beta coefficients), the magnitude of the effect differs. In fact, as is shown in Table 3, the L1 participants experienced a 183 ms slow-down on line 3 in the R&M-consistent condition compared to the R&M-disrupted one. In contrast to this, as is shown in Table 7, the L2 participants experienced an attenuated 137 ms slow-down, which was not significant when examined separately.

Moreover, differential effects of Condition were detected in terms of RTs. The significant interaction between Group and Condition was expected given what the separate models for L1 and L2 speakers had estimated. That is, while the L1 comprehenders were only slightly (and nonsignificantly) faster in their response rates in the R&M-consistent condition compared to the R&M-disrupted one (−151ms), the opposite pattern emerged for L2 participants who exhibited a significantly slower response rate in the face of R&M consistency (322ms). Possible explanations to account for this differential effect between groups are proposed in the General Discussion.

Finally, new analyses were run with data from both groups considered which included covariates. Our main goal was to test if the same result patterns would emerge for both groups when the Switch variable was added. These new analyses concerned reading time data and RTs to the question (for differences between L1 and L2 Switchers and Biased participants in terms of interpretative preferences, descriptive statistics can be found in Appendix B). Regarding other terms considered for inclusion in models, we allowed for character count or word count but did not include scores on additional tasks as these differed between groups.

Line 3 and 4 reading times as well as RTs by Group, Condition, and Switch are plotted in Figure 4. The new model for line 3 reading times included Group, Condition, and Switch, as well as line 3 character count. As in the previous analyses, significantly longer reading times were estimated in the R&M-consistent condition (p = 0.008) and for L2 participants (p < 0.001). There was also a significant effect of line 3 character count (β = 0.01, 95% CI [0.006, 0.02], t(1233) = 3.44, p < 0.001). Crucially, the interaction between Switch (Switchers) and Condition (R&M-consistent) proved significant (β = 0.13, 95% CI [0.01, 0.25], t(1233) = 2.19, p = 0.029). Post hoc tests revealed that the interaction was driven by Switchers taking longer to read line 3 in the R&M-consistent condition compared to the R&M-disrupted one (β = 0.14, p = 0.008; d = 0.392, 95% CI [0.1, 0.68]). There were no differential effects of Condition for Biased participants (p > 0.05).

Figure 4. Mean reading times for Line 3 (top) and Line 4 (middle) and RTs to the Interpretation Question (bottom) by Group, Condition and Switch (SE error bars).

In terms of line 4 reading times, there was again an effect of Group (L2), as was the case in the previous analysis (p < 0.001). Line 4 word count was also significant (β = 0.07, 95% CI [0.02, 0.12], t(1235) = 2.53, p = 0.011). Importantly, the interaction between Switch and Condition was significant (β = 0.11, 95% CI [0.01, 0.21], t(1235) = 2.20, p = 0.028). Post hoc comparisons revealed that it was again Switchers that took longer to read line 4 in the R&M-consistent condition; yet, this result did not survive Bonferroni corrections (β = 0.079, p = 0.071).

Thus, these results revealed that Switchers took significantly longer to read critical lines 3 in the R&M-consistent condition; a similar effect, although marginal, was detected for line 4. Since there were no interactions with Group, it seems that both L1 and L2 Switchers processed the critical lines similarly in the R&M-consistent condition. The same interaction between Switch and Condition was not observed in the RT data; instead, it was the interaction between Group and Condition that remained significant (p = 0.019), as in the previous model with just Group and Condition as predictors.

Pronoun interpretative preferences

Study 1 and 2 were designed to explore how L1 and L2 English comprehenders would process and interpret anaphoric ambiguities in the presence of competing cues. As far as L1 speakers are concerned, it was hypothesized that the rhyme cue on the nonsubject (OBJ) candidate would influence interpretative preferences; the magnitude of the effect was expected to be small due to the nature of the manipulation and further modulated by comprehender-dependent factors.

We did indeed find an effect of prosodic cues on L1 interpretative preferences. It was observed that the SUB antecedent was interpreted as coreferential with the pronoun to a greater extent in the R&M-consistent condition relative to the R&M-disrupted one. This could be attributed to the manipulation introduced, namely the effect of the rhyme cue: it made the OBJ antecedent blend in with preceding context in the R&M-consistent condition, thus allowing for the otherwise default competitor (SUB) to gain ground. In parallel, the incongruence of the OBJ in the R&M-disrupted condition led to it being marked as a line-final non-rhyming element in the otherwise rhyming context; as a consequence, the OBJ antecedent became prominent and accessible for coreference (Arnold, Reference Arnold2010) to a greater extent compared to when it was a rhymed word in the R&M-consistent condition.

Importantly, the suggestion that the OBJ blended in with preceding context in the R&M-consistent condition does not imply that the rhyming antecedent was perceptually non-salient or inappreciable (see also Carminati et al., Reference Carminati, Stabler, Roberts and Fischer2006 for a similar justification). As will be discussed in more detail later on, the reading time results indicate that having the OBJ be a rhyming antecedent in the R&M-consistent condition caused L1 comprehenders to slow down their reading rate. This is thought to be due to a rhyme noticing effect and/or heightened competition. If that is indeed the case, the finding that the OBJ candidate was dispreferred compared to the SUB, specifically when it was a rhyming element, could be the result of readers inhibiting the OBJ response. It is possible that readers perceived rhyme as an obtrusive or biasing cue which they needed to suppress, although this hypothesis cannot be tested given the scope of the present experimental studies.

It is also noteworthy that we observed no categorical subject bias, regardless of Condition. For instance, in Cunnings et al. (Reference Cunnings, Fotiadou and Tsimpli2017) L1 participants selected SUB antecedents as referents of ambiguous pronouns at 87% in subject-biasing contexts and at 66% in object-biasing contexts. In the present study, L1 speakers selected the SUB at 51% in the R&M-disrupted condition and at 58% in the R&M-consistent condition. Importantly, ART performance was not a significant predictor of L1 comprehenders’ interpretative preferences. Although it has been suggested in the literature that greater print exposure contributes to the strength of the subject bias (Arnold et al., Reference Arnold, Strangmann, Hwang, Zerkle and Nappa2018; Langlois & Arnold, Reference Langlois and Arnold2020), the present findings do not suggest such an association. Since no compreheder-dependent measure was predictive of L1 participants’ interpretative preferences, the source of this modest subject preference in the present study remains unclear. It is possible that the poetic contexts designed were successful at maximizing perceived ambiguity or neutralizing biases. Another possibility is that the low subject preference we observed is attributable to the placement of the alternative candidate (i.e., the OBJ) at the end of a line, which is in and of itself “a salient position” (Fabb, Reference Fabb2022, p. 167-168). We thank an anonymous reviewer for pointing this out.

With regard to L2 speakers’ interpretative preferences, we expected any effects our manipulation would have for L1 comprehenders to be absent or attenuated in comparison. The results obtained lend support to this hypothesis. While L1 participants seemed to prefer the SUB interpretation over the OBJ in the R&M-consistent condition, L2 speakers had no such inclination and, arguably, exhibited no clear preference in either condition.

Thus, L2 speakers did not show sensitivity to the prosodic cues introduced like L1 participants did; instead, what seemed to contribute to L2ers’ interpretative preferences was WM. On the one hand, higher Backward Digit Span scores led to a lower probability of choosing the OBJ, irrespective of Condition. This finding is in line with the proposition put forth by Bel et al. (Reference Bel, Sagarra, Comínguez and García-Alcaraz2016), namely that memory-related principles (e.g., recency) contribute to the selection of antecedents for anaphora resolution in the L2; hence, low span L2 participants chose the non-distant OBJ referent more often than high span L2 speakers. Surprisingly, the opposite relationship was detected when Reading Span scores were examined (for dissociations between Reading and Backward Digit Span, see also Farmer et al., Reference Farmer, Fine, Misyak and Christiansen2017). The OBJ candidate was more likely to be selected with better performance in the Reading Span task. This result is more in line with Swets et al. (Reference Swets, Desmet, Hambrick and Ferreira2007) who also observed that high reading span readers preferred local referents of ambiguous relative pronouns. However, this claim was not made for L2 speakers; rather, it applied to L1 participants in their study. The present L1 results do not suggest a similar positive relation between Reading Span and nonsubject preference; instead, higher Reading Span scores were predictive of greater odds of switching between referential interpretations as a function of the textual version (Condition) in the L1 group. Thus, it may be concluded that WM influences pronoun interpretative preferences in both groups, albeit in dissimilar ways; for L2ers, WM interacts with other cues to guide resolution (e.g., recency, subjecthood, etc.), but there is no additional influence of the prosodically differentiated context.

The time course of anaphora resolution

The analysis of reading time data from the L1 group revealed that rhythmic and phonological regularity slowed down reading rate in the region containing the two competing antecedents. There was no effect on the subsequent region containing the ambiguous anaphoric pronoun. These findings may be indicative of a rhyme noticing effect or heightened attention to the rhyming candidate at final position on line 3. It is also possible that readers experienced cue competition in the R&M-consistent condition and, because they expected to be asked about the pronoun’s referent, they spent additional time to process the critical line with the two referents. This may then have led to somewhat speedier interpretation responses, if a commitment to a parse had already been made. Placing these results in a broader theoretical context, the fact that rhythmic and phonological regularity did not lead to a speed-up but a slow-down points toward a semantic/conceptual disfluency cost; that is, the presence of regular prosodic cues may have rendered resolution more effortful and/or increased perceived ambiguity (e.g., Menninghaus et al., Reference Menninghaus, Bohrn, Knoop, Kotz, Schlotz and Jacobs2015; Wallot & Menninghaus, Reference Wallot and Menninghaus2018).

It is noteworthy that this slow-down on line 3 was modulated by individuals’ interpretative biases. Participants who switched interpretative preferences in response to the prosodic cues took longer to process line 3 when R&M was consistent. No differences between conditions in terms of reading rate were detected for participants with fixed interpretative biases. Additionally, the fact that higher Reading Span scores were associated with being a Switcher provides support to Nieuwland and Van Berkum (Reference Nieuwland and Van Berkum2006) assertion, namely that high span readers consider alternative interpretations and integrate multiple types of information during resolution.

Comparisons between L1 and L2 speakers showed that the prosodic cues affected reading rate in the L1 group, but not in the L2 group. Although in the combined analyses of L1 and L2 data it was observed that both groups slowed down in the R&M-consistent condition, this effect was not observed in the L2 group when examined separately. Thus, result patterns are quite complex, allowing for different conclusions to be reached depending on whether the lack of interactions in the combined analyses or the differential effect sizes in the separate analyses are deemed more reliable. Since L2 participants did not slow down to the same extent as L1 readers, we believe this may go some way in explaining why L2 readers experienced delays later on when responding to the interpretation question in the R&M-consistent condition. In more detail, it is possible that L1 speakers followed an expediting strategy: they spent more time early on to encode competing information and decide on one of the two referents; once the interpretation had been determined, this allowed for somewhat speedier RTs to the interpretation question. By contrast, L2 speakers might have followed a delaying strategy; they did not slow down to assess which one of the two competing candidates could become the referent of the upcoming pronoun; as a result, additional time was needed when prompted to arrive at an interpretation at the question stage.

On the one hand, the lack of significant effects when the L2 data were examined separately may suggest “non-native-like,” shallower or otherwise qualitatively distinct behavior in the L2 (Clahsen & Felser, Reference Clahsen and Felser2006; Sorace & Filiaci, Reference Sorace and Filiaci2006); more broadly, they align with previous studies’ findings of reduced sensitivity to prosodic and other form-based cues in the L2 (Foltz, Reference Foltz2021; Martin et al., Reference Martin, Thierry, Kuipers, Boutonnet, Foucart and Costa2013; Nakamura et al., Reference Nakamura, Arai, Hirose and Flynn2020; Perdomo & Kaan, Reference Perdomo and Kaan2021; Roncaglia-Denissen et al., Reference Roncaglia-Denissen, Schmidt-Kassow, Heine and Kotz2015; Schafer et al., Reference Schafer, Takeda, Rohde and Grüter2015; Schmidt et al., Reference Schmidt, Pérez, Cilibrasi and Tsimpli2020). Yet, this may not be a complete picture; a slow-down in the face of R&M consistency did emerge in the L2 group, although in a different measure than in the L1 group, namely in RTs to the interpretation question. This result could be interpreted in line with accounts that do not argue for qualitative, but instead, quantitative differences and “delayed reflexes” in the L2 (Cunnings, Reference Cunnings2017; Hopp, Reference Hopp2006; McDonald, Reference McDonald2006; see also Clahsen & Felser, Reference Clahsen and Felser2018; Sorace, Reference Sorace2011). However, this explanation can be challenged since this slow-down was very much delayed in the L2 group, to the extent that it manifested in a postprocessing measure. Thus, this result may not be indicative of a deterministic, slower-acting effect in the L2, but to preferential reliance on distinct processing strategies between groups (e.g., an expediting strategy in the L1 and a delaying approach in the L2). Yet again, this proposal is not incontestable and it is up for debate whether this dissimilarly expressed effect points toward differential ability or differential utility of processing strategies between groups (see Kaan & Grüter, Reference Kaan, Grüter, Kaan and Grüter2021 for discussion).

Therefore, depending on the result patterns that the reader is inclined to assign more weight to, different conclusions may be reached and findings may be interpreted as providing support to alternative accounts. In our view, it is difficult to identify a single account that can explain all aspects of the data. We believe this is partly because in most prior research emphasis has been placed on L1–L2 comparisons in order to establish to what extent the latter group behaves in a “native-like” way. An implicit assumption within this approach is that there is an L1 “standard” against which the L2 performance is to be evaluated. Yet, as mentioned above, we discovered participant-level variability in L1 speakers, which casts doubt on the existence of this uniform L1 benchmark; this also limits any claims we can make about L2 divergence from L1 norms. For instance, we found that L1 Biased participants (i.e., those who exhibited fixed pronoun interpretative preferences and were characterized by lower WM) were not affected by the prosodic cues during anaphora resolution. This highlights that arguing for a L2-specific difficulty or deficiency may be problematic, since a subgroup of L1 participants also did not exhibit sensitivity to the prosodic cues introduced during anaphora resolution. By pointing this out, we merely wish to highlight that alongside L1–L2 differences, there is value in examining anaphora resolution through an “individual differences” lens, which brings us to our next point.

In terms of individual differences in the L2 group, the critical region containing the two referents was processed faster by L2 comprehenders with higher WM and proficiency level in English. Additionally, as in the L1 group, L2 participants who switched interpretative preferences in response to the prosodic cues also took longer to process critical line 3 in the R&M-consistent condition. However, this result was observed only when both L1 and L2 data were examined together in the same model; when L2 data were examined separately, there was no effect of the Switch measure in the L2 group. This suggests that, even though L2 speakers also switched preferences in response to the prosodic cues just like L1 comprehenders, the slow-down that the L2 Switchers experienced was not as pronounced as in the L1 group. In addition to this, unlike in the L1 group, in the L2 group neither reading span nor any other comprehender-dependent measure proved to be predictive of switching tendencies. This may be because there was not enough variability in the L2 group in relation to the Switch measure. In fact, L2 participants were predominantly Biased, which suggests that interpretative preferences may be more fixed or likely to persist in the L2 (Cunnings et al., Reference Cunnings, Fotiadou and Tsimpli2017; Jacob & Felser, Reference Jacob and Felser2016; Pozzan & Trueswell, Reference Pozzan and Trueswell2016).

Given all the information discussed above, it seems unwarranted to claim that the prosodic cues induced effects only in L1 speakers. Instead, it seems better to conclude that the effects of phonological and rhythmic regularity are reserved for individuals who consider contextual cues and activate alternative referential interpretations, rather than for those with fixed biases. There is reason to believe that this is not something specific to the L1 group. We identified participants who switched interpretative preferences in the L2 group too. However, compared to L1 Switchers, L2 Switchers were fewer and their switching tendencies were not explained by WM or any other measure. Future research is needed to explore what drives switching behavior in L2 speakers and whether similar switching rates exist in L2 groups with different L1 backgrounds and proficiency levels.