Gender-Fair Language in Translation: A Case Study (2023)

Abstract: With an increasing visibility of non-binary individuals, a growing number of language-specific strategies to linguistically include all genders or neutralize any gender references can be observed. Due to this multiplicity of proposed strategies and gender-specific grammatical differences across languages, selecting the one option to translate gender-fair language is challenging for machines and humans alike. As a first step towards gender-fair translation, we conducted a survey with translators to compare four gender-fair translations from a notional gender language, English, to a grammatical gender language, German. Proposed translations were rated by means of best-worst scaling as well as regarding their readability and comprehensibility. Participants expressed a clear preference for strategies with gender-inclusive character, i.e., colon.

## introduction gender in language reflects on an extra-linguistic reality @xcite in the sense that it reflects gender associations and stereotypes of a society. to respect different gender identities, i.e., the sense of self and "who they are" @xcite , it is vital to linguistically acknowledge their existence within and across languages. machine translation (mt) is known to suffer from gender bias, which is problematic for many reasons. for instance, machine-translated online contents are consumed without people being aware that they are mt mediated @xcite . in mt research, the idea to resort to gender-neutral language to avoid gender issues has been proposed @xcite . however, apart from information loss, this might not be the preferred gender-fair strategy by humans. to analyse human preferences, we propose a first survey foot_0 among language professionals of four distinct gender-fair translation strategies from english to german. translation studies has a long tradition of considering gender issues, such as in feminist @xcite and queer translation @xcite . however, gender beyond the binary has so far received little scholarly attention (e.g. @xcite and @xcite ). the same is true for the field of mt, where debiasing strategies focus on a binary conception of gender, with some important exceptions @xcite . gender-fair language, which subsumes gender-inclusive and gender-neutral strategies, is particularly challenging in case of grammatical gender languages, i.e., several word classes require gender inflections. in this case study, ten language professionals rated four gender-fair translations of online magazine articles in direct comparison and regarding their impact on readability and comprehensibility. the four german strategies consist of one genderneutral neosystem, one gender-inclusive neosystem, a gender-inclusive colon with si:er, and the same colon with neopronoun xier. since rating a translation is in general a highly subjective matter, the selected method is best-worst scaling, which allows participants to select and rate their subjectively most (best) and least (worst) preferred trans-lation. in a previous gender-fair mt workshop we conducted with translators, non-binary people, and mt experts @xcite , readability and comprehensibility of gender-fair language strategies were repeatedly named as important factors in the selection process. thus, we decided to include a rating of these two dimensions in the present survey. furthermore, participants were requested to motivate their choice in the form of a free text answer. while the perspective of non-binary individuals and mt experts would be equally interesting, we believe that preferences and considerations of language professionals as producers of (gender-fair) translations are of vital importance to the field of translation studies as well as machine translation. the results of this survey contribute to the discussion on which gender-fair language strategy is preferred in (machine) translating to german and which considerations are particularly important for language professionals. ## related work since the focus of this article is on analyzing gender-fair translation strategies as a first step, this section focuses on work on gender-fair translation. in spite of the recent development of queer translation studies @xcite , research in the field of translation studies rarely addresses non-binary genders @xcite . most research focuses on media translation, e.g. subtitled and dubbed series, and news articles @xcite @xcite . @xcite and @xcite analysed the dubbed and subtitled versions of the netflix series one day at a time in spanish and french. they found that the gender-fair language strategies used varied between the dubbed and subtitled versions as well as from european to latin american spanish. the non-binary character was correctly addressed with non-binary neopronoun elle in the european spanish dubbed version only. in the other cases, they were misgendered with female forms and/or literal translations of english singular they. similarly, in the french dubbed version, non-binary neopronoun ielle was used whereas in the subtitles the character was referred to with indefinite pronoun on (one/we). in their analysis of english tv series translated to polish, @xcite found a systematic omission of the non-binary characters' gender identity. this phenomenon could also be observed in croatian movie translations and articles on sam smith's coming out as non-binary where the third person masculine plural pronoun was generally used @xcite . @xcite represents also one of the few works to include interviews with people, i.e., non-binary individuals, on the topic. recent developments in gender-fair language strategies have been studied in psycholinguistics with a focus on binary genders. for instance, @xcite conducted experiments in swedish and english and tested different strategies to reduce male bias in language, i.e., (i) binary paired forms, (ii) gender-neutral words as well as (iii) gender-fair pronoun hen and english singular they. participants read a description of a candidate for a job position and were asked to select photos of men or women corresponding to the said description. the results suggest that (i) and (iii) actively reduce male bias. in german, empirical research concentrated on the cognitive processing of textual information. @xcite , for example, tested the effect of male generics and two binary gender-fair language forms on memory performance and text intelligibility. no differences in memory performance across strategies were found between men and women. however, as concerns intelligibility, women indicated no preferences, while men indicated a preference for male generics. to the best of our knowledge, this is the first study to consult language professionals regarding their preferences regarding gender-fair language strategies. since language professionals play the important role of producing gender-fair translations, needed to fine-tune mt models, we believe that their perspective is interesting for translation studies and the field of machine translation. ## preliminaries in order to establish the theoretical foundation of the present survey, an introduction to the interaction of gender with language and translation is provided, followed by a brief overview of gender-fair language strategies in english and german. ## method in order to evaluate the perception, readability, and comprehensibility of gender-fair language strategies, two empirical methods targeted to measure subjective impressions were selected, i.e., best-worst scaling (bws) and the likert scale. bws @xcite , a comparative annotation method, was used to select and evaluate the subjectively best and the worst translation strategy, whereas the likert scale @xcite , a rating scale, was used to rate the readability and comprehensibility of the best and worst strategy chosen by the participants. readability refers to whether a text written in a specific gender-fair language strategy is easy and enjoyable to read for the participants of this study subjectively. comprehensibility refers to the ease to understand the message of a text written in a specific strategy for the participants of this study subjectively. the choice to combine these two methods is based on the desire to limit the granularity and inconsistencies that can occur when using solely a rating scale @xcite . ## results after presenting participants' profiles, their preferences regarding the evaluated strategies, ratings for readability and comprehensibility, and overall comments on the topic are detailed. ## discussion one initial assumption of this survey was that the gender-inclusive sylvain system might be preferred on the basis that it follows the grammatical rules of german and thus, might seem more natural than other strategies. however, this strategy was overwhelmingly rated as the worst in the set, appearing unnatural, erroneous, confusing, and overly complex. its ratings on readability and comprehensibility reflect these comments. the overall correspondence between bws ratings and likert scores indicates a tight link between personal preferences for gender-fair translation strategies and their subjective readability and comprehensibility, emphasizing the importance of the two dimensions chosen for this study. however, in future research these dimensions should take the specific needs of people with physical and/or cognitive disabilities into consideration, e.g. by conducting a survey with a more diverse group of participants. the gender-neutral ens system is comparatively easy to use from a grammatical point of view, since it requires no declensions. however, this grammatical simplicity considerably alters the language with a detrimental effect on readability and comprehensibility, as shown by the overall ratings and participants' comments. even its only advocate in the survey doubted the general applicability of a language system without declensions in german. in the set of proposed strategies the colon after the word stem emerged as the clear winner, with a slight preference for its use with the neopronoun xier over introducing another colon in the pronouns as in si:er. since these two strategies, s3 and s4, are the ones closest to the current language use, it can be assumed that familiarity with strategies plays a role in the selection of preferences, which was reflected in a participants' comment. thus, it would be interesting to evaluate whether a thorough introduction including exercises to the other strategies would alter the final selection of preferred strategies. in fact, in a previously conducted workshop @xcite , participants obtained such a thorough introduction and then in exercises opted for the ens strategy (s1). one participant in this case study even remarked on the fact that familiarity, readability, and comprehensibility already increased from the first to the last text, where each of which was very short. this indicates that familiarizing participants with different strategies might be feasible in a largescale survey or experimental setting and would be an interesting alternation for future studies on gender-fair translation. due to the multiplicity of proposed gender-fair language strategies in german, we opted for a small selection in this survey in order not to overwhelm participants. this selection was driven by the intention to compare gender-neutral and gender-inclusive strategies. however, for the former we only included one neosystem, where other strategies, such as rewording, are available. for the latter category, three strategies were included, where even for the best strategy a change in typographical character might already impact the responses, i.e., underscore or star instead of colon as well as placement of the character. the colon after the word stem was explicitly chosen to reduce the emphasis on male/female endings. since we only included one gender-neutral option, a subselection of gender-inclusive strategies and a sample limited in size, no conclusions on the preference of either category can be drawn, for which future studies with a different setup are foreseen. however, the importance to be equipped with gender-fair translation strategy that finds acceptance by the general public was emphasized. thereby, common translation problems, such as involuntary or accidental misgendering in the translation, could be mitigated or solved. for instance, if the source text is rather vague on the gender of a character/person in a notional gender language, some gender-fair translation strategies enable equal vagueness in a grammatical gender language. while the best strategy ultimately depends on the context not only in the textual sense but also in the sense of the translation assignment, target group, purpose, etc., some strategies might be easier to use, comprehend, and read than others and might impact the transfer from the source to the target text differently. in terms of implications for translation technologies and in particular machine translation, we believe that this survey reveals how complex and language-specific the topic of gender-fair language and translation truly is. while overall preferred strategies could be identified, individual participants showed different preferences, e.g. one participant clearly preferred the ens strategy. thus, machine translation might need to be able to accommodate different gender-fair language strategies depending on the language, context, purpose, and target audience of a translation. these preferences or requirements might also change with the domain of texts, where in this case study the degree of domain-specificity of media texts is rather low. in this case study, the task was also to select from a set of existing translations. it would be interesting to evaluate the performance and preferences of professional translators when asked to perform gender-fair post-editing of machine translated texts. ## conclusion in order to socially and linguistically include different gender identities, a multiplicity of genderfair language strategies, in particular for grammatical gender languages, has been proposed. the transfer of gender-fair strategies across structurally different languages is challenging for machines and humans. thus, it is interesting to evaluate the position and preferences of language professionals on the topic of gender-fair translation from a notional to a grammatical gender language. in the presented survey results based on best-worst scaling, ten language professionals revealed a preference for the gender-inclusive strategy of colon after the word stem in combination with the neopronoun xier over the gender-inclusive sylvian and gender-neutral ens neosytem. the alternative of colon with si:er was rated only slightly lower than with xier, where participants commented on a preference for pronouns without typographical character that they considered more natural. for both strategies with colon the overall rating on the dimensions of readability and comprehensibility was neutral to positive, whereas ens was considered to negatively impact both dimensions the most. a correspondence between the expression of preferences and the ratings of readability and comprehensibility as well as explicit references to these two dimensions in free text comments confirmed their importance within the context of gender-fair translation strategies. in the present study, a preference for a genderinclusive strategy could be observed, however, with a limited selection of strategies and a small number of respondents. to obtain a general preference regarding gender-neutral or gender-inclusive strategies, a large-scale study with a stronger va-riety of gender-fair language strategies across languages and a larger, potentially more diverse target group would be required. the results indicate that preferences might also vary depending on the participants' degree of familiarity with individual strategies, which is a factor worth investigating in future endeavors. finally, the impact of the level of domain specificity and text type would be interesting factors. nevertheless, with this first study on gender-fair translation among language professionals we hope to have provided a methodological contribution as well as first results on genderfair translation strategies from the perspective of language professionals, a method that can easily be transferred to future studies and even evaluating machine translation results.