What is gender?

We just don’t know.

Lexically speaking, English consistently and traditionally encodes male (he), female (she), a genderless plural (they), and a non-human singular (it). Colloquially, they can also be singular, as can them, although there is plenty of debate around whether it’s truly treated as singular (Foertsch & Gernsbacher 1997, Sanford & Filik 2007, Doherty & Conklin 2017). However, they and them are entirely ambiguous between the singular and traditional plural meanings. I’m investigating themself, which is a nonstandard but (definitively?) singular version of the pronoun. Importantly, as a reflexive anaphor, it must be bound by an antecedent so as an experimenter, I can control what it obligatorily corefers with. This makes it very easy to pair themself (or themselves) with a specific referent whose gender (or gender bias, or lack thereof) can be manipulated. For instance, names, definite and indefinite noun phrases, and indefinite pronouns can be used to test whether different gender biases affect the acceptability of the coreference dependency.

If the Gender Mismatch Effect stems from the genders of two words being incompatible, then we must define what genders are incompatible. Superficially, this is easy because male and female are nice, neat categories, but they aren’t the only genders (and increasingly, are not the only categories). However, if singular they can match in gender with a binary-gender word (either male or female), then we’ve got to be a lot more precise about what we mean when we say the genders of two words match or mismatch, since they is ostensibly gender-neutral. On the other hand, if singular they can’t match in gender with a binary-gender word, but it can match with a gender-neutral word, then maybe we are encoding a third gender category, rather than the absence of gender. This raises the question of how pronouns and gender categories will continue to evolve, if natural gender is gradient but our lexical encoding of it is categorical.

In any case, these are just a few of the possible ways in which gender might be encoded in English, and there is much work to be done.


Influences on resolution of temporary structural ambiguities

Good news! The ethics forms for the project are submitted, I know where the eye-tracker is and I’m applying for a small internal grant to get the pilots going. Everything is moving at a pleasantly fast pace and I’m feeling like it’s all going to be possible. (I really can’t recommend highly enough getting together with a bunch of wonderful colleagues for a regular writing group. It really lifts the spirits!)

In short, the first set of experiments I’m getting of the ground are the ones examining the influence of non-grammatical gender on the parser’s behavior. Van Gompel and Liversedge (2003), for instance, show that gender and number are lexical features that are only checked after a long distance dependency is formed. This is what makes the Gender Mismatch Effect (GMME) such a great tool for real-time sentence processing studies — the mismatch can cause the parser to apparently slow down while it revises or repairs its mistake. What I want to know, though, is how flexible this gender-checking mechanism is. As Frazier et al. (2015) notes, in reference to the possible [un]grammaticality of sentences with ‘gender mismatches’:

[I]t is not unimaginable that a woman might be named Steven, merely very unexpected, and likewise in the context of a costume party, the individual picked out by the referring expression the cowgirl could conceivably be male.

Moreover, there are people who do not identify as men or women, but as some non-binary gender (of which there are many). Thus, the assumptions underlying many studies that use gender mismatch to test, e.g., long-distance dependency formation may rely on a gender binary that is not sociologically or biologically valid. To be fair, a large proportion of Western populations only have experience with cisgender people, thus rarely have occasion to process sentences that contain non-binary pronouns. But, as Frazier and colleague point out, this type of real-life gender mismatch can occur anywhere costume parties occur, which is presumably a much larger proportion of the population than those who are familiar with non-binary gender identities.

So, I will be testing whether the GMME is something that is flexible that can be mitigated with exposure to non-binary and ‘nonstandard’ uses, or whether it is something rigid that is acquired at a young age* and is difficult to adapt to new experiences and knowledge. Both cases could have implications for how to positively change societal treatment of people who want to be referred to with non-binary pronouns. Both cases could also inform theories of how the parser assimilates non-linguistic (or paralinguistic) information during real-time sentence processing.

(*I assume that many to most people who are familiar with non-binary gender identities learned about them well after the critical period, based on the broad societal attitude toward transgender and non-binary/gender-queer people in Western cultures.)

… and I’ve arrived!

After some administrative hoops, several thousand miles of flying, and dozens of miles of walking, I am here, at Newcastle University!

I am now a postdoctoral Research Associate in the School of English Literature, Language and Linguistics. For the next three years, I will be investigating, in collaboration with Dr. Joel Wallenberg, how the real-time representation of syntactic structure is influenced by (at least two) sources of information. Those two sources are: (1) prosody, and in particular, prosodic boundaries that are typically associated with syntactic clause boundaries; and (2) observed, deduced, or assumed information about the gender of human referents in the sentence, in particular exploring variation associated with the comprehender’s (reader’s or listener’s) exposure to and experience with people who are of a nonbinary gender. As these projects progress, I will update my research pages with more information.