Hasil untuk "Women. Feminism"

Anna Duwenig, Kari Eifler, Priyanga Ganesan et al.

This paper aims to determine if membership within the Operator Algebras Mentor Network (OAMN) is beneficial to its members. The OAMN is an international mentoring initiative that offers support in small groups to women and minority genders in the particularly male-dominated field of operator algebras (OA) in mathematics. Expected advantages of membership include raising awareness of the lack of gender diversity in this field, providing advice to mentees by mentors (e.g., pertaining to career or work/life balance), broadening one's network in OA, etc. A questionnaire was sent to OAMN members and a control group of non-members at similar institutions and similar positions to collect their experience with the mentoring initiative and perception of gender dynamics within the OA discipline, together with basic demographics. The initial analysis of the data collected shows that mentoring junior women and other minority genders in the area has a positive effect on mentees' networking ability, self-promotion, and raising awareness of gender issues within OA as a whole.

Apekshya Ghimire, Chandralekha Singh

Collaboration with peers both inside and outside the classroom can be an invaluable tool for helping students learn physics. We investigated the impact of peer collaboration on learning physics by examining the characteristics of women and men who typically worked alone versus those who typically collaborated with peers in their algebra-based introductory physics course when they took the course before and during the COVID-19 pandemic when the classes were on Zoom. Our findings indicate that, on average, students who worked with peers had higher grades and reported greater peer influence on their physics self-efficacy during the pandemic compared to those who worked alone. We also observed that, for both women and men, a larger percentage of students typically worked in groups before the pandemic, while a greater percentage typically worked alone during the pandemic. We discuss these results in relation to students' prior academic preparation, physics grades, self-efficacy and their perception of the effectiveness of peer collaboration on their physics self-efficacy.

Francesca Barigozzi, Pietro Biroli, Chiara Monfardini et al.

This paper introduces a novel, scalable methodology to measure individual perceptions of gaps in mental load -- the cognitive and emotional burden associated with organizing household and childcare tasks -- within heterosexual couples. Using original data from the TIMES Observatory in Italy, the study combines time-use diaries with new survey indicators to quantify cognitive labor, emotional fatigue, and the spillover of mental load into the workplace. Results reveal systematic gender asymmetries: women are significantly more likely than men to bear organizational responsibility for domestic tasks, report lower satisfaction with this division, and experience higher emotional fatigue. These burdens are underestimated by their partners. The effects are particularly pronounced among college-educated and employed women, who also report greater spillovers of family responsibilities than men during paid work hours. The perceived responsibility for managing family activities is more strongly associated with within-couple gaps in time use than with the absolute time spent on their execution, underscoring the relational and conflictual nature of mental load.

P. Pillay, H. N. Galappaththi-Arachchige, M. Taylor et al.

BackgroundGlobally, Africa has the highest HIV, cervical cancer and schistosomiasis prevalence. Female Genital Schistosomiasis (FGS) is hypothesized to be associated with HIV and cervical atypia. Young women aged 15 and above, constituting almost 3 million of the South African population, have limited health care access and are at risk for this triad of diseases. Urinary HPV DNA analysis is a non-invasive sampling method that can assist in evaluating risk among this population. This study compared the analysis of HPV DNA in urine and cervico-vaginal lavage (CVL) samples to cytology Pap smear, Schistosoma microscopy and HIV results.MethodsIn this cross-sectional study, 235 young women aged 16 years and older from rural high schools in KwaZulu-Natal participated. HPV DNA analysis was done in urine and CVL samples. Pap smears were analysed for squamous cell atypia and urine microscopy was used for the identification of Schistosoma ova.ResultsUrinary schistosomiasis was reported in 49 (20.9%) and HIV detected in 49 (20.4%). Urinary and CVL HPV DNA was found in 147 (62.6%) and 177 (75.3%) respectively. Any atypia was detected cytologically among 173 (73.6%). The following associations were found using the Pearson Chi-Square and a Likelihood Ratio test: (a) between HIV positive status and urinary HPV DNA positive cases on both the urine (X2 = 5.007; p-value = 0.025) and (X2 = 4.264; p-value = 0.039) and between HIV positive status and CVL HPV DNA tests respectively (X2 = 5.165; p-value = 0.023) and (X2 = 4.321; p-value = 0.015), and (b) among urine HPV DNA and the CVL HPV DNA tests, where (X2 = 52.966; p-value = 0.001) and (X2 = 50.716; p-value = 0.001). Urine HPV DNA showed a sensitivity of 75.7% and specificity of 77.6% relative to the CVL HPV DNA. There was no statistical association between urinary schistosomiasis and HPV or with any atypia.ConclusionUrine has the potential of being optimized as an alternative and possibly more acceptable sample for HPV detection among young adolescent populations at risk in comparison to CVL samples. An integrated targeted intervention incorporating Schistosoma in addition to HPV and HIV testing needs consideration among young women in this age group from endemic areas.

Cristina Perales-García, Reinald Besalú, Laura Pérez-Altable et al.

The Spanish general election held on July 23, 2023, was significantly influenced by the discourse on feminism and gender-based violence, issues that all the political parties were determined to address either directly or indirectly. This research paper explores the electorate’s reception of the feminist agenda, evaluating the extent to which the gender perspective is integrated into political discourse and resonates with the general public and investigating the gender-specific perceptions and biases that influence their assessment of political candidates. The responses to a survey administered between July 19 and 21, 2023 to 1,590 Spanish residents aged 18 and above, demographically weighted by gender, age, and geographical location, reflect the profound influence of gender on electoral perceptions and reveal nuanced differences in the evaluation of conservative candidates according to respondents’ gender. Notably, the analysis highlights the critical role of women in moderating the advance of conservative and far-right political narratives. This study contributes to the broader discourse on gender politics by underscoring the complex interplay between feminist policies and political perceptions within the context of the 2023 Spanish general election.

Satyam Mohla, Bishnupriya Bagh, Anupam Guha

Artificial Intelligence with its multifaceted technologies and integral role in global production significantly impacts gender dynamics particularly in gendered labor. This paper emphasizes the need to explore AIs broader impacts on gendered labor beyond its current emphasis on the generation and perpetuation of epistemic biases. We draw attention to how the AI industry as an integral component of the larger economic structure is transforming the nature of work. It is expanding the prevalence of platform based work models and exacerbating job insecurity particularly for women. Of critical concern is the increasing exclusion of women from meaningful engagement in the digital labor force. This issue often overlooked demands urgent attention from the AI research community. Understanding AIs multifaceted role in gendered labor requires a nuanced examination of economic transformation and its implications for gender equity. By shedding light on these intersections this paper aims to stimulate in depth discussions and catalyze targeted actions aimed at mitigating the gender disparities accentuated by AI driven transformations.

Boyu Ning

One of the national treasures, Mahjong, is a strategic card game originating from China, played competitively by constructing and optimizing card hands among four players. In the game, players aim to achieve specific combinations of cards, known as "winning hands," through actions such as drawing, discarding, pung, and kong. Mahjong not only tests memory and strategy but also integrates probability and chance, embodying profound cultural significance and social attributes. However, as Mahjong becomes a widely popular social activity, its impact on personal life has gradually become apparent. In this paper, I delve into the analysis of the effects of playing Mahjong on marital relationships, particularly the three negative effects it brings to women: Time Displacement: The uncertainty of Mahjong playing time leads to a reduction in shared time between spouses. Women may feel neglected due to the lack of companionship, leading to "Mahjong Panic Syndrome." Emotional Conflict: Mahjong playing can result in losses, and men may harbor "resentment from defeat" at the Mahjong table, which could be brought into the household and spark marital disputes. Social Isolation: Women may feel excluded from their partner's social circle if they do not participate in Mahjong activities, experiencing "marginalization at the card table." This study not only reveals the potential negative impact of late-night Mahjong returns on marital relationships but also provides new insights into communication and empathy between spouses from the perspectives of decision trees, time series analysis, and game theory. It also finds the optimal solution through Monte Carlo simulations.

Sina Sahebi, Sahand Heshami, Mohammad Khojastehpour et al.

Adaptive cruise control (ACC) is a technology that can reduce fuel consumption and air pollution in the automotive industry. However, its availability in Iran is low compared to industrialized countries. This study examines the acceptance and willingness to pay (WTP) for ACC among Iranian drivers. Data from an online survey of 453 respondents were analyzed using the Technology Acceptance Model (TAM) and an ordered logit model. The results show that perceived ease of use and perceived usefulness affect attitudes toward using ACC, which in turn influence behavioral intentions. The logit model also shows that drivers who find ACC easy and useful, who have higher vehicle prices, and who are women with cruise control (CC) experience are more likely to pay for ACC. To increase the adoption of ACC in Iran, it is suggested to target early adopters, especially women and capitalists, who can influence others with their positive feedback. The benefits of ACC for traffic safety and environmental sustainability should also be emphasized.

Jane Dwivedi-Yu, Raaz Dwivedi, Timo Schick

The accurate evaluation of differential treatment in language models to specific groups is critical to ensuring a positive and safe user experience. An ideal evaluation should have the properties of being robust, extendable to new groups or attributes, and being able to capture biases that appear in typical usage (rather than just extreme, rare cases). Relatedly, bias evaluation should surface not only egregious biases but also ones that are subtle and commonplace, such as a likelihood for talking about appearances with regard to women. We present FairPair, an evaluation framework for assessing differential treatment that occurs during ordinary usage. FairPair operates through counterfactual pairs, but crucially, the paired continuations are grounded in the same demographic group, which ensures equivalent comparison. Additionally, unlike prior work, our method factors in the inherent variability that comes from the generation process itself by measuring the sampling variability. We present an evaluation of several commonly used generative models and a qualitative analysis that indicates a preference for discussing family and hobbies with regard to women.

Hasnul Insani Djohar, Willy Oktaviano, Mira Utami

This paper investigates how Kahf’s poetry collection, Hagar Poems (2016), discovers Muslim women or Muslimah leadership by exploring Muslimah leaders, such as Hagar (Hajar), Khadija, and Aisha to undermine reductionist views of Muslim women both in Orientalism and Anglo-American feminism. In doing so, Kahf uses the strategies of juxtaposition, humor, and irreverence by connecting Muslimah ancient leaders to her contemporary speakers who are crisscrossing Islamic traditions and American popular culture. By engaging with postcolonial and gender studies with the frameworks of leadership and Islamic studies, this paper investigates how Kahf’s women juxtapose ancient folkloric tales and American popular cultures, both to establish their multiple identities and leadership and to illuminate contemporary resonances of ancient Muslimah leaders in the eyes of subsequent generations. Indeed, the patterns of Muslimah leadership in Kahf’s poems are represented as engaging with the ideas of creativity, piety, and solidarity; and these patterns work to question the exclusion of Muslimah leadership in both gender and orientalist debates. Thus, Kahf’s Hagar Poems explores the representation of Muslim women from Islamic history who serve as role models, having displayed heroic characteristics through their leadership.

Yuqian Sun, Yuying Tang, Ze Gao et al.

This paper presents "AI Nushu," an emerging language system inspired by Nushu (women's scripts), the unique language created and used exclusively by ancient Chinese women who were thought to be illiterate under a patriarchal society. In this interactive installation, two artificial intelligence (AI) agents are trained in the Chinese dictionary and the Nushu corpus. By continually observing their environment and communicating, these agents collaborate towards creating a standard writing system to encode Chinese. It offers an artistic interpretation of the creation of a non-western script from a computational linguistics perspective, integrating AI technology with Chinese cultural heritage and a feminist viewpoint.

Mikko Kytö, Saila Koivusalo, Heli Tuomonen et al.

Gestational diabetes (GDM) poses a growing health risk to both pregnant women and their offspring. While telehealth interventions for GDM management have proven effective, they have traditionally relied on healthcare professionals for guidance and feedback. Our aim was to explore self-tracking in GDM with wearable sensors from self-discovery (i.e., learning associations between glucose levels and lifestyle) and user experience perspectives. We conducted a mixed-methods study with women diagnosed with GDM, utilizing continuous glucose monitor and three types of physical activity sensors (activity bracelet, hip-worn sensor, and electrocardiography sensor) for a week. Data from the sensors was collected, and participants were later interviewed about their experience with the wearable sensors. Additionally, we gathered maternal nutrition data through a 3-day food diary and recorded self-reported physical activity using a logbook. We discovered that continuous glucose monitors were especially valuable for self-discovery, particularly when establishing links between glucose levels and nutritional intake. Challenges associated with using wearable sensors data for self-discovery in GDM included: (1) Separation of glucose and physical activity data in different applications, (2) Missing key trackable features, such as light physical activity and non-walking activities, (3) Discrepancies in data, and (4) Differences in perceived versus measured physical activity. The placement of sensors on the body emerged as a critical factor influencing data quality and personal preferences. To conclude, an app where glucose, nutrition, and physical activity data are combined is needed to support self-discovery. This app should enable tracking of essential features for women with GDM, including light physical activity, with data originating from a single sensor to ensure consistency and eliminate redundancy.

Jessica McClearn, Rikke Bjerg Jensen, Reem Talhouk

In this paper we explore the digital security experiences of marginalised populations in Lebanon such as LGBTQI+ identifying people, refugees and women. We situate our work in the post-conflict Lebanese context, which is shaped by sectarian divides, failing governance and economic collapse. We do so through an ethnographically informed study conducted in Beirut, Lebanon, in July 2022 and through interviews with 13 people with Lebanese digital and human rights expertise. Our research highlights how LGBTQI+ identifying people and refugees are scapegoated for the failings of the Lebanese government, while women who speak out against such failings are silenced. We show how government-supported incitements of violence aimed at transferring blame from the political leadership to these groups lead to amplified digital security risks for already at-risk populations. Positioning our work in broader sociological understandings of security, we discuss how the Lebanese context impacts identity and ontological security. We conclude by proposing to design for and with positive security in post-conflict settings.

Rejoice Chipuriro

This paper focuses on strategies deployed by women and discourses of women’s collective action in the #BeatThePot strike which took place alongside popular protests against Mugabe and the failures of ZANU-PF led government in Zimbabwe. Using Judith Butler’s ideas on “bodies in alliance and the politics of the street,” I theorize how women as gendered “bodies congregate, move, speak and strike together as they claim public space into political spaces” (2015, 70). I interrogate women’s use of embodiment as a strategy involving the metaphor of both the “labouring mothering body” and as “bodies that strike,” which demonstrates how women in Zimbabwe confronted violent political, economic, and socio-cultural limits imposed on their bodies. In this strike, women challenged the silencing of women’s public political work and refused to be relegated to the invisible margins of domesticized and undervalued reproductive labour. Thus, through the #BeatThePot protest, I demonstrate how women in Zimbabwe have engaged in body work to a confront violent regime and how they have borne on their bodies violent reprisal through sexual attacks, abductions, incarcerations, torture, and even loss of life. The paper concludes that the feminized body is a site of violent struggle for autonomy and that through collective action women in Zimbabwe have sought to confront and transform the repressive state.

F. Haug, Erica Carter

Anna Guitart, Afsaneh Heydari, Eniola Olaleye et al.

Maternal and child mortality is a public health problem that disproportionately affects low- and middle-income countries. Every day, 800 women and 6,700 newborns die from complications related to pregnancy or childbirth. And for every maternal death, about 20 women suffer serious birth injuries. However, nearly all of these deaths and negative health outcomes are preventable. Midwives are key to revert this situation, and thus it is essential to strengthen their capacities and the quality of their education. This is the aim of the Safe Delivery App, a digital job aid and learning tool to enhance the knowledge, confidence and skills of health practitioners. Here, we use the behavioral logs of the App to implement a recommendation system that presents each midwife with suitable contents to continue gaining expertise. We focus on predicting the click-through rate, the probability that a given user will click on a recommended content. We evaluate four deep learning models and show that all of them produce highly accurate predictions.

Amirhosein Bodaghi

This study examines Olympic champions characteristics on Instagram to first understand how age and gender affect the characteristics and their interrelations and second to see if the future changes in those characteristics are predictable. We crawled Instagram data of individual gold medalists in Rio2016 Olympic for a period of 4 months and utilized a content analytic method to analyze their photograph posts. The cross-sectional analysis shows as the champions get older, the rate of follower engagement decreases in both genders, but men increase their pure self-presentation posts while women extend their circle of followings. In its approval, the longitudinal analysis shows when the higher rate of engagement is achieved, then men and women champions lose their tendency in increasing self-presenting posts and number of followings respectively. These findings in the light of relative theories and the previous literature contribute to a better understanding of athletes cyber behavior in social media. Moreover, the findings serve as a guide for sport researchers seeking to grasp the ways that aid athletes to better interact with their followers and build the personal brand, which involves sponsorship and other promotional opportunities.

Tanja Säily, Eetu Mäkelä, Mika Hämäläinen

We study neologism use in two samples of early English correspondence, from 1640--1660 and 1760--1780. Of especial interest are the early adopters of new vocabulary, the social groups they represent, and the types and functions of their neologisms. We describe our computer-assisted approach and note the difficulties associated with massive variation in the corpus. Our findings include that while male letter-writers tend to use neologisms more frequently than women, the eighteenth century seems to have provided more opportunities for women and the lower ranks to participate in neologism use as well. In both samples, neologisms most frequently occur in letters written between close friends, which could be due to this less stable relationship triggering more creative language use. In the seventeenth-century sample, we observe the influence of the English Civil War, while the eighteenth-century sample appears to reflect the changing functions of letter-writing, as correspondence is increasingly being used as a tool for building and maintaining social relationships in addition to exchanging information.

Weidong Huang

The standard methods to calculate the Total Fertility Rate require the reliable age-specific fertility rate including birth data and the related age-specific women's population data. Historically, the number of births was often not counted according to the age of the mother, so it is difficult to estimate the historical total fertility rate with the standard methods. Many empirical methods have been proposed, but their application is limited to specific period and place. This paper deduces a new method for calculating the total fertility rate from the number of birth and the population of women at childbearing age, can be applied to most of cases. The relative error is usually less than 5%. It is easier to calculate TFR, and may be applied to obtain more TFRs for the history.

Vítor Albiero, Kai Zhang, Kevin W. Bowyer

Deep learning methods have greatly increased the accuracy of face recognition, but an old problem still persists: accuracy is usually higher for men than women. It is often speculated that lower accuracy for women is caused by under-representation in the training data. This work investigates female under-representation in the training data is truly the cause of lower accuracy for females on test data. Using a state-of-the-art deep CNN, three different loss functions, and two training datasets, we train each on seven subsets with different male/female ratios, totaling forty two trainings, that are tested on three different datasets. Results show that (1) gender balance in the training data does not translate into gender balance in the test accuracy, (2) the "gender gap" in test accuracy is not minimized by a gender-balanced training set, but by a training set with more male images than female images, and (3) training to minimize the accuracy gap does not result in highest female, male or average accuracy