Not all English Resultative Constructions (ERCs) are equal: The acquisition of ERC by Spanish speakers

ABSTRACT

The English Resultative Construction (ERC) is a satellite-framed structure with no identical equivalent in Spanish. In a series of studies, we analyzed and compared recognition (acceptability judgment task) and comprehension (sentence comprehension task) of three ERC subtypes with the English Depictive Construction (EDC) (which has a Spanish counterpart) by Spanish speaker learners of English as a Foreign Language (EFL). Results showed that: 1) EDCs were better recognized than ERCs by L2 learners, but highly proficient participants were closer to English native speakers’ performance, 2) Less proficient EFLs comprehended EDCs better than those ERC subtypes that were further from Spanish (ERC Property and Fake Reflexive). We interpret our findings in terms of an interlinguistic distance gradient, where those constructions present (EDC) or closer (ERC-Path) to L1 are more readily acquired. This effect seems more prominent at lower EFL proficiencies, and fades as proficiency increases, evolving towards a more native-like pattern.

Acknowledgments

We would like to thank Sheri Wells-Jensen, Silvina Montrul and Martine Gallardo for their help with different aspects of this research. In addition, we are particularly thankful to Tania Ioning and two anonymous reviewers for their careful reading of this paper. They are not responsible for any remaining shortcoming.

Disclosure statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Supplementary Information

Supplemental data for this article can be accessed online at https://doi.org/10.1080/10489223.2022.2141634

Notes

¹ Goldberg & Jackendoff (2004) propose another subtype of ERC (that is verbal, not constructional), namely the Verbal Resultatives as in They made Peter angry. In addition, within the constructional subtypes (Path, Property and Fake Reflexive ERC), Goldberg & Jackendoff (2004) propose other special—or marginal—cases. They propose Spit case like Bill spit out of the window; Follow case Path like Bill followed the road into the forest; Intransitive Sound Emission like The trolley rumbled through the tunnel; and Dancing Mazurka as Mark danced mazurkas across the room. In our experiments, we included transitive ERC-Path, ERC-Property and ERC-Fake Reflexive subtypes as they are broader categories of resultatives that hold significant differences among themselves.

² The goal in some of the cited works on complexity (e.g., Palotti 2015) tends to be more ambitious than the one we set out for us here. While Palotti talks about the complexity of a linguistic system (i.e., English) or, for instance, the morphology of a system, we just aim at contrasting the complexity of subtypes of the same construction (ERC) and a construction that shares central grammatical properties (i.e., EDC), as both correspond to secondary predicates.

³ Furthermore, these properties are part of the inventory of any grammatical theory and they are not exclusive of ERC or EDC nor even of English or Spanish. It is the case that the description of a particular property can be theory dependent; yet, we should be able to agree on the underlying phenomenon, whether described in terms of one theory or another.

⁴ A quick search in the COCA corpus (Davies 2015) of the form “walked + preposition” resulted in 56.350 tokens from which 39.558 (70.2%) were undoubtedly Goal/Source introducing prepositions (e.g., “into,” “to,” “onto,” “from,” “away”). The other 30% is distributed among prepositions with unbounded Path meanings (e.g., “towards”) and any other meaning. If unbounded Path prepositions with Goal/Source are included (e.g., “towards”), the percentage rises to 85.68. In sum, the vast majority of the walking event descriptions involve a specification of the Goal/Source.

⁵ Non-lexically licensed DOs are also known as non-argument DOs (since they are not arguments in the semantic of the verb) or as ECM (Exceptional Case Marked) (Wechsler 2005). ECM assumes the claim that they are ‘deep subjects’ of the small clause associated with the AP in ERC-Property or Fake, but receive Case from the matrix verb.

⁶ If we use the causative paraphrase as a test for the presence of causality (van Valin 2005, among others), (1) does not allow it (#The boy caused himself to be in the bedroom) whereas (3) allows it since “Mary caused John to be tired by dancing” captures the basic meaning of (3) even if it does it in a less specific way since the cause does not need to be direct (Shibatani & Pardeshi 2002).

⁷ In terms of RRG, this scope extension is another evidence of a tightest syntactic relation between two predicates: a co-subordinated nuclear juncture (van Valin 2005).

⁸ In the generative tradition, EDC involves just like ERC a small clause and raising from subject of SC to DO of the main clause (Hoekstra 1988; Williams 1997). However, EDC does not need a hidden causative morpheme. In RRG, ERC is a complex predicate whereas EDC is not: AP is a peripheral modifier of the Core of the main Clause (van Valin 2005). Even though our analysis stands from an RRG perspective, both Generative Grammar and RRG reflect differently the contrast in complexity of these structures.

⁹ In fact, most of the ERC-Property examples (twelve (12) out of sixteen (16) items) in our data set correspond to strong instances of ERC-Property, and the four ones that are weak are instances that cannot be mirrored in Spanish as Result is not entailed by the verb. In the case of ERC-Path, most of the items selected codify boundary crossing. In this sense, no experimental ERC item in our data set can be replicated by a mirror image sentence in Spanish.

¹⁰ We acknowledge that one cannot rule out potential differences on the basis of null results. However, the inclusion of subject random effects on mixed models allows control for between-subject sources of variation. In addition, item-level sources of variability are controlled by including item random effects in our models.

¹¹ The same analysis described in this section was conducted later with the full dataset (including these four participants) and inferential results did not differ qualitatively.

¹² We have conducted an EEG experiment on ERC processing by EFL learners and its preliminary analysis strongly suggests that Spanish L1 subjects that process ERCs lexically perform better than those who process it syntactically.

Additional information

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.