This article investigates gender bias in narratives generated by Large Language Models (LLMs) through a two-phase study. Building on our existing work in narrative generation, we employ a structured methodology to analyze the influence of protagonist gender on both the generation and classification of fictional stories. In Phase 1, factual narratives were generated using six LLMs, guided by predefined narrative structures (Hero's Journey and Heroine's Journey). Gender bias was quantified through specialized metrics and statistical analyses, revealing significant disparities in protagonist gender distribution and associations with narrative archetypes. In Phase 2, counterfactual narratives were constructed by altering the protagonists’ genders while preserving all other narrative elements. These narratives were then classified by the same LLMs to assess how gender influences their interpretation of narrative structures. Results indicate that LLMs exhibit difficulty in disentangling the protagonist's gender from the narrative structure, often using gender as a heuristic to classify stories. Male protagonists in emotionally driven narratives were frequently misclassified as following the Heroine's Journey, while female protagonists in logic-driven conflicts were misclassified as adhering to the Hero's Journey. These findings provide empirical evidence of embedded gender biases in LLM-generated narratives, highlighting the need for bias mitigation strategies in AI-driven storytelling to promote diversity and inclusivity in computational narrative generation.
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Narrative structures such as the Hero’s Journey and Heroine’s Journey have long influenced how characters, themes, and roles are portrayed in storytelling. When used to guide narrative generation in systems powered by Large Language Models (LLMs), these structures may interact with model-internal biases, reinforcing traditional gender norms. This workshop examines how protagonist gender and narrative structure shape storytelling outcomes in LLM-based storytelling systems. Through hands-on experiments and guided analysis, participants will explore gender representation in LLM-generated stories, perform counterfactual modifications, and evaluate how narrative interpretations shift when character gender is altered. The workshop aims to foster interdisciplinary collaborations, inspire novel methodologies, and advance research on fair and inclusive AI-driven storytelling in games and interactive media.
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Het woord ‘bias’ komt naar voren in zowel maatschappelijk als wetenschappelijk debat over de inzet van artificiële intelligentie (ai). Het verwijst doorgaans naar een vooroordeel dat iets of iemand vaak onbedoeld heeft. Wanneer dit vooroordeel leidt tot een afwijking in besluitvorming vergeleken met een situatie wanneer dit vooroordeel er niet zou zijn, dan is een bias doorgaans onwenselijk.
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DOEL: Deze studie onderzoekt de mogelijke invloed van gender op de historische dynamiek rond verpleegkundig leiderschap. METHODE: Gebruikmakend van een historische onderzoeksbenadering voert deze studie een bronnenanalyse uit met gender als analytische lens, gericht op de ontwikkeling van het verpleegkundig directeurschap in het Sint Radboudziekenhuis vanaf de oprichting van de medische kliniek (1956) tot de uitsluiting van de verpleegkundig directrice uit de directie (1971). RESULTATEN: Er worden zes gendergaps geïdentificeerd, namelijk verschillen in vermeende capaciteiten en kwaliteiten, werk-privébalans, opleiding, salarisstructuur, ondersteuning en gebruik van retoriek. Dit wijst op betrokkenheid van stereotype denkbeelden bij het vormen van de genderasymmetrie binnen het verpleegkundig beroep en de perceptie ervan op de werkplek en daarbuiten. DISCUSSIE: Een geleidelijke uitsluiting van verpleegkundigen op basis van geslacht op strategisch niveau in directies wordt benadrukt. Deze asymmetrie en vooroordelen creëerden een onevenwichtig speelveld, wat de onderhandelingen over de status van het verpleegkundig beroep bemoeilijkte en belemmeringen opwierp voor verpleegkundig leiderschap. CONCLUSIE: Het zichtbaar en bespreekbaar maken van deze vooroordelen kan het bewustzijn vergroten over de wijze waarop historisch gegroeide ideeën en overtuigingen hedendaags verpleegkundig leiderschap beïnvloeden.
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Hoe ziet de BIAS bij werkgevers eruit ten aanzien van mensen met een minder geprivilegieerde positie op de Nederlandse Arbeidsmarkt?
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It is crucial that ASR systems can handle the wide range of variations in speech of speakers from different demographic groups, with different speaking styles, and of speakers with (dis)abilities. A potential quality-of-service harm arises when ASR systems do not perform equally well for everyone. ASR systems may exhibit bias against certain types of speech, such as non-native accents, different age groups and gender. In this study, we evaluate two widely-used neural network-based architectures: Wav2vec2 and Whisper on potential biases for Dutch speakers. We used the Dutch speech corpus JASMIN as a test set containing read and conversational speech in a human-machine interaction setting. The results reveal a significant bias against non-natives, children and elderly and some regional dialects. The ASR systems generally perform slightly better for women than for men.
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Important gender differences, relating to trauma history, offending and mental health needs are not sufficiently considered in most (risk) assessment and treatment procedures in forensic practice. We developed guidelines for gender-responsive work in Dutch forensic mental health care. The experiences of practitioners and forensic psychiatric patients were collected and analyzed by means of an online survey (n = 295), interviews with professionals (n = 22), female (n = 8) and male (n = 3) patients. Guidelines regarding gender-sensitive (risk) assessment and trauma-informed care were rated as most relevant in the survey. In the interviews we focused on experiences and wishes for trauma treatment and gender-mixed treatment. Practical guidelines were written based on the results of the survey, interviews and literature, and presented in expert meetings with patients and practitioners, and further refined based on their comments. Applying these guidelines may contribute to improved treatment for female patients thereby preventing relapse.
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Chapter 17 in 'Challenging Bias in Forensic Psychological Assessment and Testing - Theoretical and Practical Approaches to Working with Diverse Populations'.
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This chapter applies the theory of symbolic interactionism to present the qualitative analysis of 51 sentencing decisions in domestic violence homicide cases processed in Polish courts. It is argued in this chapter that sentencing, like any other human action, is subject to interpretations at the hands of judges, who engage in the construction and meaning-making process of gender at the sentencing stage. The findings demonstrate the diversely-constructed presence of gendered narratives, which vary in terms of their inclusion of the domestic violence terminology and/or the discussion on the fulfilment of socially-prescribed gender roles. The analysis has exposed a powerful interplay between the judges’ perception of the (abusive) relationship, gender roles, and the defendant’s/victim’s acquiescence to them, which in consequence makes women more likely the subject of double standards of conformity. The chapter offers a qualitative outlook on the topic and invites a new theoretical perspective to shift the attention from the impact of gender – to the meaning of gender – in sentencing decisions.
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Questions we care about (objectives) This study contributes to the body of knowledge of entrepreneurial educators’ strategies to work towards gender inclusion in entrepreneurial education (EE). By illustrating how gender stereotypes and gender bias are constructed and reconstructed in EE. An important insight is taken from the study by (Jones, 2014), this author shows that entrepreneurs are presented in EE as a homogeneous group with similar character traits and an equal 'entrepreneurial mindset' (p. 244). This description portraits a right way to be an entrepreneur which is traditionally been associated with a white western man, masculine behaviour and masculine abilities (Jones, 2014). As a consequence, a paradox in EE appears; training and education reduces the gender gap on the one hand (Cheraghi and Schøtt, 2015), but at the same time it is also the place where the gender gap is maintained because these gender stereotypes are intertwined in this training and education (Korhonen, Komulainen and Räty, 2012). The aim of this paper is to use Social Role Theory in order to better understand the dynamics of gender in EE. This leads to the following research questions: what are the main mechanisms that contribute to gender-inclusive entrepreneurship education (EE) and how are the different mechanisms that contribute to gender inclusive entrepreneurship education (EE) integrated into the current curriculum?Approach In-depth interviews with 12 lecturers that teach/coach in the field of EE from across various faculties in a large University for Applied Sciences combined with newsletters created by one of largest EE programs at this institution (267 pages in 2020) is carried out. A semi-structured questionnaire was used to guide the in-depth interviews. Subsequently, discourse analysis gives insight into gendering in EE at the investigated institution. Results The main findings suggests that when questioned about the topic all respondents stressed the importance of gender equally, only a few seem to be aware of the need to address the issue in their classroom(s) while none of the programs currently adopt a gender perspective while coaching their potential entrepreneurs or when addressing how the entrepreneurial ecosystem functions. Implications These findings and perspectives point to the importance of recognizing that a “one size fits all” approach to curricula may not be appropriate, and that gender-sensitive programming, especially related to dealing with these gender stereotypes and gender bias, are needed. This means that in educational development there are opportunities to create better education and create equal opportunities for male and female students. Value/originalityWomen still form the minority amongst the population of (potential) entrepreneurs and find it more difficult to grow their venture due to a range of (institutional) barriers. This study shows that, thus far, EE insufficiently addresses this topic and points to opportunities for interventions for increasing the gender inclusiveness of the entrepreneurial ecosystem, especially for female ones, instilling in them the awareness and knowledge that as a female entrepreneur starting a business isn’t without gendered challenges. This research therefore adds to the body of knowledge on the construction and reconstruction of gender stereotypes and gender bias in the field of EE.
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