Are Second Person Masculine Generics Easier to Process for Men than for Women? Evidence from Polish

Abstract

In Polish, it is obligatory to mark feminine or masculine grammatical gender on second-person singular past tense verbs (e.g., Dostałaś list ‘You received-F a letter’). When the addressee’s gender is unknown or unspecified, masculine but never feminine gender marking may be used. The present self-paced reading experiment aims to determine whether this practice creates a processing disadvantage for female addressees in such contexts. We further investigated how men process being addressed with feminine-marked verbs, which constitutes a pragmatic violation. To this end, we presented Polish native speakers with short narratives. Each narrative contained either a second-person singular past tense verb with masculine or feminine gender marking, or a gerund verb with no gender marking as a baseline. We hypothesised that both men and women would read the verbs with gender marking mismatching their own gender more slowly than the gender-unmarked gerund verbs. The results revealed that the gender-mismatching verbs were read equally fast as the gerund verbs, and that the verbs with gender marking matching participant gender were read faster. While the relatively high reading time of the gender-unmarked baseline was unexpected, the pattern of results nevertheless shows that verbs with masculine marking were more difficult to process for women compared to men, and vice versa. In conclusion, even though masculine gender marking in the second person is commonly used with a gender-unspecific intention, it created similar processing difficulties for women as the ones that men experienced when addressed through feminine gender marking. This study is the first one, as far as we are aware, to provide evidence for the male bias of second-person masculine generics during language processing.

Japanese written pseudowords can be conditioned to Japanese spoken words with positive, negative, and active emotions

“…We conducted a cumulative link mixed model (Christensen 2019 ) of two fixed effects of phases (before conditioning (phase 1); after conditioning (phase 2)) and conditions (a pseudoword conditioned to positive words; a pseudoword conditioned to neutral words; and a pseudoword conditioned to negative words), two random effects of participants and words (Baayen et al 2008 ), and one dependent variable (evaluative responses to pseudowords) using “ordinal” (Christensen 2019 ) and “emmeans” packages (Lenth 2022 ) in R (R Core Team 2022 ). We also used “Rmisc” to calculate the means and 95% confidence intervals (Hope 2022 ), “FSA” to calculate medians and first and third quartiles (Q1 and Q3; Ogle et al 2023 ), and “ggplot2” to make a figure of results (Wickham 2016 ) in R (Mangiafico 2015 ; Szuba et al 2022 ). First, we employed the maximal random structure model for the model selection (Barr et al 2013).…”

“…We employed a cumulative link mixed model (Christensen 2019 ) of two fixed effects of phases and conditions, two random effects of participants and words (Baayen et al 2008 ), and one dependent variable (evaluative responses to pseudowords) using “ordinal” (Christensen 2019 ) and “emmeans” packages (Lenth 2022 ) on R (R Core Team 2022 ). We also used “Rmisc” to calculate means and 95% confidence intervals (Hope 2022 ), “FSA” to calculate medians and first and third quartiles (Q1 and Q3; Ogle et al 2023 ), and “ggplot2” to create a figure of results (Wickham 2016 ) as R packages (Mangiafico 2015 ; Szuba et al 2022 ). Regarding the fixed effects, phases included before conditioning (phase 1) as 1 and after conditioning (phase 2) as 2, whereas conditions included a pseudoword conditioned to active words as active, a pseudoword conditioned to neutral words as neutral, and a pseudoword conditioned to passive words as passive.…”

Rating gender stereotype violations: The effects of personality and politics

“…As a result, most of our participants were young women, which raises the question whether participant gender, not the measures used here, would explain the differences (cf. e.g., Szuba et al, 2022). Indeed, as Supplementary Figure S7 shows, our sample was skewed to the liberal end of the political ideology scale.…”