Inaugurele rede voor de Universiteit van Maastricht met als onderwerp publieke gesprekken over gender en biotechnologie.
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The moment of casting is a crucial one in any media production. Casting the ‘right’ person shapes the narrative as much as the way in which the final product might be received by critics and audiences. For this article, casting—as the moment in which gender is hypervisible in its complex intersectional entanglement with class, race and sexuality—will be our gateway to exploring the dynamics of discussion of gender conventions and how we, as feminist scholars, might manoeuvre. To do so, we will test and triangulate three different forms of ethnographically inspired inquiry: 1) ‘collaborative autoethnography,’ to discuss male-to-female gender-bending comedies from the 1980s and 1990s, 2) ‘netnography’ of online discussions about the (potential) recasting of gendered legacy roles from Doctor Who to Mary Poppins, and 3) textual media analysis of content focusing on the casting of cisgender actors for transgender roles. Exploring the affordances and challenges of these three methods underlines the duty of care that is essential to feminist audience research. Moving across personal and anonymous, ‘real’ and ‘virtual,’ popular and professional discussion highlights how gender has been used and continues to be instrumentalised in lived audience experience and in audience research.
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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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The aim of the study is to investigate the influence of gender and gender pairing on students’ learning performances and knowledge elaboration processes in Computer-Supported Collaborative Learning (CSCL). A sample of ninety-six secondary school students, participated in a two-week experiment.Students were randomly paired and asked to solve several moderately structured problems concerning Newtonian mechanics. Students’ pretest and posttest performances were analyzed to see whether students’ gender and the gender pairing (mixed or single-gender) were significant factors in their problem solving learning in CSCL. Students’ online interactions were also analyzed to unravel the dynamic process of individual knowledge elaboration. The multilevel analyses revealed that a divergent pattern of knowledge elaboration was a significant predictor for students’ learning achievement, and in mixed-gender dyads students’ knowledge elaboration processes were more inclined to diverge from each other. Moreover, females in single-gender dyads significantly outperformed females in mixed-gender dyads. But this was not the case for male students.
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Affective teacher–child relationships have frequently been investigated in school settings, but less attention has been devoted to these relationships in after-school care. This study explored caregiver- (N = 90) and child-informed reports (N = 90) of the affective caregiver–child relationship (N = 180 dyads) in Dutch after-school care, exploring gender differences at caregiver and child level and the relationship with a gender match between children and caregivers. The caregivers and children reported relatively high levels of closeness and relatively low level of conflict and dependency/autonomy support, irrespective of gender. Multilevel regression analyses revealed that a gender match between child and caregiver was associated with teacher-reported closeness: levels were highest in female-girl dyads and lowest in male-boy dyads. Further, boys indicated the highest levels of autonomy in male-boy dyads, whereas girls indicated the lowest levels in female-girl dyads. Masculinity of staff was associated with more child-reported autonomy support, whereas femininity predicted caregiver-reported closeness in the relationship.
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Background In Dutch engineering education, female students outperform male students.Using an interactionalist framework, this study explores factors that contribute to this gender-based difference.Purpose This study aims to answer two questions: Do female and male students differ in background characteristics, engagement factors, and academic success? Are differences in the relationships among background characteristics, engagement factors, and academic success gender-specific?Design/method Data on male and female engineering undergraduate students from five Dutch universities were subjected to linear structural modeling to compare potential gender differences in the relationships among the focal variables. Two structural models were considered.Results Female students spent more time on independent study, reported more social inte- gration, completed more credits, and were more likely to stay in engineering than were male students. Academic integration and intention to persist were important for comple- tion of credits for both genders. Social integration was only important for men’s academic success. Females seemed to benefit less from good preparation through active learning during secondary education, and the effect of a high grade point average on math was neg- ative for females but positive for males.Conclusions Interactionalist concepts can explain academic success, but the relationships among concepts vary by gender. Males’ intentions to persist in engineering are an outcomeof engagement processes during the first year, whereas females’ intentions to persist in engineering are manifest at the start of the first year.
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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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Substance abuse is an important risk factor for offending, but is mostly studied in males. The aim of this multicentre study is to gain insight into possible gender differences in substance abuse history and offending behavior in forensic psychiatric patients. Files were analyzed of 275 women and 275 matched men who have been admitted between 1984 and 2014 to one of four Dutch gender-mixed forensic hospitals. Risk assessment ratings were related to registered violent incidents during treatment for both women and men and to official recidivism data after discharge for a subgroup of 78 women. Substance abuse history was coded as a risk factor for more than half of the women (56.7%), but significantly more often for men (68.4%). Men were more often diagnosed with substance dependence and more frequently committed the index-offense whilst intoxicated. Prediction of violent incidents during treatment was more accurate for men. A history of substance abuse was not a significant predictor for recidivism after discharge in the subgroup women. It is concluded that there are gender differences in substance abuse history and that the relationship with offending behavior seems stronger for men. These differences have implications for substance use treatment in forensic mental health services.
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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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