Face Gender Research Articles

The Status of Women Among the Tribal Communities of West Bengal, India

The tribal population has been enumerated as scheduled tribe population since 1951 in accordance to the constitution (Scheduled tribe) order, 1950. They are the aboriginal or Adivasi or early settler of India and they are the most backward groups in India. This paper focuses on the status of tribal women in their community with respect to their male counterparts both in general and tribal populations. Four indicators such as sex ratio, literacy rate, the general fertility rate of women and women's work participation rate are taken to assess the status and the gender discrimination among the tribal communities. The modified Sopher’s Disparity Index (1974) of Kundu and Rao (1986) has been used to identify the gender disparity and Pearson’s correlation co-efficient techniques have been used to analyze the correlation among the indicators. It has been found that like any other community in India, tribal women face gender discrimination. They are engaged in different economic sectors as economic assets of tribal households but they are often deprived to get their social rights. This paper also finds out the causes of gender disparity and suggests some measures to mitigate the gender discrimination.

The influence of facial attractiveness and personal characteristics on imitation

ABSTRACT Imitation plays a crucial role in learning and communication, although a little is known whether individuals imitate each other based on particular personality traits. Facial features and personal characteristics are the major components of personal impressions. This study adopted the color paradigm to explore the effect of the two factors on imitation. Experiment 1 examined the effect of facial attractiveness and face gender on imitation. The results showed that woman who appeared attractive drove imitation more than woman who did not. However, men who appeared attractive and unattractive differed insignificantly. Experiment 2 investigated the effect of facial attractiveness and personal characteristics on imitation. The results of Experiment 1 were verified, stating that positive personal characteristics drove imitation more than negative personal characteristics. The study found that facial attractiveness still affected imitation when characteristics information appeared. Regarding negative personal characteristics, individuals who appeared attractive drove imitation more than individuals who did not. The results indicate that imitation is automated, influenced not only by face types but also by personal characteristics.

Real-Time Gender Recognition for Juvenile and Adult Faces

Facial gender recognition is a crucial research topic due to its comprehensive use cases, including a demographic gender survey, visitor profile identification, targeted advertisement, access control, security, and surveillance from CCTV. For these real-time applications, the face of a person can be oriented to any angle from the camera axis, and the person can be of any age group, including juveniles. A child's face consists of immature craniofacial feature points in texture and edge compared to an adult face, making it very hard to recognize gender using the child's face. Real-word faces captured in an unconstrained environment make the gender prediction system more complex to identify correctly due to orientation. These factors reduce the accuracy of the existing state-of-the-art models developed so far for real-time facial gender prediction. This paper presents the novelty of facial gender recognition for juveniles, adults, and unconstrained-oriented faces. The progressive calibration network (PCN) detects rotation-invariant faces in the proposed model. Then, a Gabor filter is applied to extract unique edge and texture features from the detected face. The Gabor filter is invariant to illumination and produces texture and edge features with redundant feature coefficients in large dimensions. Gabor has drawbacks such as redundancy and a large dimension resolved by the proposed meanDWT feature optimization method, which optimizes the system's accuracy, the size of the model, and computational timing. The proposed feature engineering model is classified with different classifiers such as Naïve Bayes, Logistic Regression, SVM with linear, and RBF kernel. Its results are compared with the state-of-the-art techniques; detailed experimental analysis is presented and concluded to support the argument. We also present a review of approaches based on conventional and deep learning methods with their pros and cons for facial gender recognition on different datasets available for facial gender recognition.

A Fully Bayesian Inference with Gibbs Sampling for Finite and Infinite Discrete Exponential Mixture Models

ABSTRACT In this paper, we propose clustering algorithms based on finite mixture and infinite mixture models of exponential approximation to the Multinomial Generalized Dirichlet (EMGD), Multinomial Beta-Liouville (EMBL) and Multinomial Shifted-Scaled Dirichlet (EMSSD) with Bayesian inference. The finite mixtures have already shown superior performance in real data sets clustering using the Expectation–Maximization approach. The proposed approaches in this paper are based on a Monte Carlo simulation technique namely Gibbs sampling algorithm including an additional Metropolis–Hastings step, and we utilize exponential family conjugate prior information to construct their posterior relying on Bayesian theory. Furthermore, we also present the infinite models based on Dirichlet processes, which results in clustering algorithms that do not require the specification of the number of mixture components to be given in advance and selects it in a principled manner. The performance of our Bayesian approaches was evaluated in some challenging real-world applications concerning text sentiment analysis, fake news detection, and human face gender recognition.

An Empirical Study of Motivational and Driving Factors on Women Entrepreneurship Venturing in India

Globally, the rate of women entrepreneurship has been growing at more than 10% each year. In fact, women have started to open their own business. Women entrepreneurs create job for themselves as well as for others too. Women in India are gaining importance in the era of economic, liberalisation, privatisation and globalisation. The institutional policy and framework for developing entrepreneurial skills and providing training and education to the women have opened the door for economic development, as well as in empowering the women. One can see a plethora of successful women entrepreneurs successfully venturing in India both in social as well as economic fields. There are number of schemes started by government of India to uplift women. Such schemes are such as National Skill Development Policy, Mudra Yojna Schemes, National Skill Development Mission, Mahila Udyam Nidhi Scheme, Stree Shakti Package, Annapurna Scheme and many more. Women entrepreneurship can be regarded as one of the most important tools to empower women in India. Still the women face gender base problem in starting and growing their venture. This article generally explores the motivational and driving factors that help women entrepreneurs to venture in India. Random sampling techniques have been used on 80 women entrepreneurs while conducting the research. The researcher has used Pearson correlations and Regression Analysis for testing the hypothesis. The overall result of this article depicts that there is a significant effect of pull motivation factors and marginal effect of push motivational factors on women entrepreneurs who are venturing their business in India.

Women in coaching: What are the problems and probable solutions?

Sport coaching faces gender inequality and tackling it may not be simple. There are far too few women coaches in the coach workforce around the world. The aim of this paper is not an exhaustive literature review of this topic but an essay with a scope to describe the problem of underrepresentation of women in coaching, outline reasons for its presence and put forward recommendations for tackling it. With stronger commitment, greater focus, purposeful coordination and partnership, as well as sound leadership the required step change could be made to change the status quo that has persisted for women in coaching since the beginning of the Olympic ideals. Such a significant change is in line with recent calls that have been made for greater focus on diversity, inclusivity, and equity in coaching by key sport stakeholders around the world.

Impediment to Leadership Opportunities for Female Doctors - Gender Disparity in Pakistani Healthcare System -SHORT REPORT.

Gender disparity, that is the unequal attitude and treatment of people due to their gender, is found in many fields including the medical profession. Not only it is present in developed countries but is also a major concern in developing countries like Pakistan. According to data, Pakistani female doctors face gender discrimination that negatively impacts their workplace performance and has proven to be a hindrance to them taking up leadership roles. The patriarchal mindset of society, workplace harassment, and lack of basic facilities in the hospital for working mothers are just a few of the factors that compel women to leave their careers. Even if they continue to work, women have to perform the duties of a mother and homemaker along with their jobs, and that negatively impacts their skills as doctors and as leaders. Efforts need to be taken to encounter all the problems that are negatively affecting leadership roles of female doctors such as providing equal opportunities, arranging awareness campaigns about creating a workplace environment that is favorable to all genders, and creating policies that will help working mothers by forming daycare centers and giving paid maternity leaves. This will help in alleviating the gender disparity in the healthcare system and will increase the chances of female doctors proving themselves good doctors and leaders.

LEGISLATIVE INSTRUMENTS: MECHANISMS FOR ADVANCING WOMENS HUMAN RIGHTS

This paper examines the applicability and relevance of status of women human rights and their developmentby improving their position who are experiencing violations of their rights to seek redress for alleged violations, calling for treatment of womens issuesby improving their status and assisting in their sustainable development, growth, and the accomplishment of all the millennium development goals. Women often face discrimination and gender inequalities because of factors such as race, sex, language, or religion. The economic, social, political, and environmental participation and empowerment are fundamental to strengthen their rights and allowing them to have control over their lives and exert influence in society generating just and equitable societies. The researcher concluded that unless women are empowered and gender equality is achieved, the nation will not achieve sustainable development with the recognition of only mens participation in all potential areas. Hence, this paper calls for the strong onus on the government to empower women and addressing gender-based discrimination and providing specific protections for womens rights to attain secure and sustainable livelihoods after all, human rights are about ensuring dignity, equality, and security for all human beings.

Career Barriers in Ghana: Evidence from Female Civil Servants

Ghanaian civil service is a classic example of a gender pyramid where top positions tend to be occupied by men, while women (more than 50%) face gender discrimination. Gender stereotypes about women are a major barrier to womens career advancement in Ghanaian civil service. Based on a series of in-depth interviews with women in the Ghanaian public authorities, we identified the main problems women face in the Ghanaian civil service, such as patriarchal practices, gender discrimination, and harassment, including sexual harassment. Our study aims to show the practitioners why it is hardly possible to call public service a comfortable job for women in Ghana.

How Infants Learn From a World of Faces: Implications for Racial Biases and Mask-Wearing

Faces are special to infants from birth, and experiences with faces in infancy are critical to developing brain circuits that support face processing skills through adulthood. Infants learn to extract rich information from faces, including recognizing people, tracking their gaze and expressions, and lip-reading. As infants learn to interact with the people around them, their responses to and understanding of these communicative facial cues become more connected to their social understanding and reflect their developmental context. Infants’ face perception is particularly responsive to experience, with some degree of plasticity present through middle childhood. Opportunities to interact with people from diverse racial backgrounds in infancy may help prevent perceptual and social biases toward different groups. Variations in experience with faces beyond face race and gender, such as the use of face coverings, may impact how and what infants learn from faces.

Using body mapping to explore gender with adolescents in Uttar Pradesh

ABSTRACT Young women and girls in Uttar Pradesh (UP), India, face gender inequalities, which threaten their health and well-being. This study used body mapping, a visual participatory research method, to learn from adolescents ages 15 to 17 living in Lucknow slums about how gender norms affect their daily experiences. Forty adolescents participated in body mapping. Their body maps and narratives about those maps demonstrate that starting in adolescence, family and community members strongly enforce divergent gender norms for girls and boys. Girls face restrictions on their clothing, mobility, and education, whereas boys have comparative freedom in these domains. Girls experience persistent public harassment by boys and men, severely constraining their ability to move freely in public spaces. In contrast, the school was a setting where adolescent girls and boys experience more relaxed gender norms. Overall, this study describes the link between gender norms, health, and well-being for adolescents. It also illustrates the value of participatory and adolescent-friendly research methods for exploring gender norms among adolescent boys and girls in India. Finally, it indicates that multi-system approaches are needed to address gender-related inequalities in health and well-being.

Facial Gender Confirmation Surgery: The Lower Jaw. Description of Surgical Techniques and Presentation of Results.

Of the primary procedures associated with facial gender confirmation surgery, those involving the mentomandibular complex have received the least attention in the literature. The authors present their experience with 837 trans feminine patients operated on for facial gender confirmation surgery who underwent mandibular bone contouring procedures, including bone contouring, chin and mandibular body and angle ostectomies, and osteotomies to reposition the chin. The authors describe the surgical techniques and materials used, and present a customized lower border-supported cutting guide designed by their team and used with 205 patients. A femininity perception score was calculated preoperatively and 12 months postoperatively, and satisfaction with the results was measured 12 months postoperatively. The postoperative follow-up ranged from 12 to 110 months. The mean femininity perception score increased from 47.86 preoperatively to 76.41 at 12 months postoperatively (p < 0.001). No emergency surgical operations were required. In no case was there any permanent damage to the mental or inferior dental nerve. The reoperation percentage because of problems detected during the postoperative period was 2.63 percent (22 patients). With facial gender confirmation surgery of the jawline and chin, it is possible to modify the transverse and vertical components of the jaw; soften the gonial angles; change the format, bone volume, and position of the chin; and harmonize the entire mandibular line. The facial feminization achieved high satisfaction scores regarding the results and feminine gender appearance 12 months after surgery. The future of mandibular bone contouring techniques includes planning with virtual software and surgical support with patient-specific cutting guides.

The “Fat Face” illusion: A robust adaptation for processing pairs of faces

Converging evidence has demonstrated our remarkable capacities to process individual faces. However, in real-life contexts, we rarely see faces in isolation. It is largely unknown how our visual system processes a multitude of faces. The current study explored this question by using the “Fat Face” illusion: when two identical faces are vertically aligned, the bottom face appears bigger. In Experiment 1, we tested the robustness of this illusion by using faces varied by gender and race, by recruiting participants from different countries (Canadian, Chinese, and French), and by implementing different task requirements. We found that the illusion was stable and immune to variations in face gender or face race, perceptual familiarity, and task requirements. Experiment 2 further indicated that binocular vision was essential for this visual illusion. When participants performed the task with one eye covered, the previously robust illusion completely disappeared. Together, these findings revealed a visual adaptation for processing multiple faces in the environment: the face at the top is perceived as more distant from the viewer and appears smaller in size than the face at the bottom. More broadly, overestimating the size of the bottom face may represent a fundamental mechanism for social interactions, ensuring the deployment of attention to those closest to self.

Age and Gender Representation on German TV

Television offers an enticing glimpse into the world, but its perspective is often skewed. When societal groups are systematically excluded from appearing on the screen, they lose the chance to represent their characteristics and interests. Recipients may then form distorted perceptions and attitudes towards those groups. Empirical research on the prevalence of such biases - especially across stations, time, and genre - has been limited by the effort of manual content analyses. We develop and validate a deep-learning based method for measuring age and gender of faces in video material. An analysis of approximately 16 million faces from six years of German mainstream TV across six stations is fused with existing program metadata indicating timing and genre of broadcasts, including advertisements. Multilevel regression models show a consistent and temporally stable discrimination against women and elderly people, along with a double discrimination of elderly women. A significant amount of variation across genres and systematic differences between public and private broadcasters furthermore indicate previously undocumented heterogeneity in the representation of societal groups on TV. We discuss potential implications of a genre-specific differentiation against the backdrop of societal trends.

Klasifikasi Jenis Kelamin Wajah Bermasker Menggunakan Algoritma Supervised Learning

The human face is an example of the unique biometric data that each person has. The human face contains a lot of information, including face shape, skin color, eye shape, nose shape, mouth shape, and some additional attributes such as beard, mustache, hair, and eyebrows. This biometric information can be used to obtain further information regarding the human identity itself. In this study, sample data of human faces aged 20 to 30 years were used. The purpose of this study is to classify gender in human facial images using masks, while the algorithm used uses supervised learning. The research process carried out was collecting human face sample data, conducting training stages which included face resizing, storing data in arrays, feature extraction using faceNet, training data and gender models. Perform testing stages which include video data acquisition, video extraction into frames, video frames, face detection, facial image resixing, storing data in arrays, feature extraction using faceNet and prediction of gender determination. The benefits of this research can provide information in determining the gender of human faces with masks, apply the application of supervised learning algorithms to processing human face images and can be applied to face detection on highways, public areas and shopping centers. Based on testing using the K-NN method, the train accuracy value is above 87% and the test accuracy is above 96%. Testing using the SVM method obtained train accuracy above 99% and test accuracy above 98%. Tests using the random forest method obtained 100% train accuracy and test accuracy above 88%.

Gender-specific Facial Age Group Classification Using Deep Learning

Facial age is one of the prominent features needed to make decisions, such as accessing certain areas or resources, targeted advertising, or more straightforward decisions such as addressing one another. In machine learning, facial age estimation is a typical facial analysis subtask in which a model learns the different facial ageing features from several facial images. Despite several studies confirming a relationship between age and gender, very few studies explored the idea of introducing a gender-based system that consists of two separate models, each trained on a specific gender group. This study attempts to bridge this gap by introducing an age estimation system that consists of two main components. The first component is a custom-built gender classifier that distinguishes females and males apart. The second is an age estimation module that consists of two models. Model A is trained only on female images, while model B is trained only on male images. The system takes an input image, extracts the facial gender then passes the image to the appropriate model based on the predicted gender label. Our age estimation models are based on the Visual Geometry Group (VGG16) networks and have been modified to fit the nature of our problem. The models produce accuracies of more than 85% individually, and the system achieves an overall accuracy of 80%. The proposed system is trained and tested on the UTKFace dataset and cross-validated on the FG-NET dataset to validate the performance on unseen data.

SOCIO-ECONOMIC STATUS OF WORKING WOMEN: A SOCIOLOGICAL STUDY

The socio-economic status of women is an indicator of the development and progress of any society and country. There was a time when women's life was confined within the boundary of the house but like the idea of women's freedom, equality, functionality spread, there was a continuous improvement in their condition. Women became empowered and started contributing in almost all fields like Education, business, administration, office work. So there is a vast change in the status and role of women and now women are becoming more working but their traditional expected roles didn't change with the same intensity. Role conflict of the double burden of working as well as domestic tasks has a bad effect on their mental and physical conditions. Despite being working they have to face gender discrimination and due to patriarchal thinking, there is not much change in their status. As a result, working women have to face different types of problems related to the family and workplace. Out of these, some women who belong to the middle and lower class, are facing much greater difficulties. Therefore, the present research work is based on 100 respondents of Roorkee city. An attempt has been made to analyse the socio-economic status of working women and their major problems based on primary data.

Facial Gender Surgery: Systematic Review and Evidence-Based Consensus Guidelines from the International Facial Gender Symposium.

Increasing societal acceptance of transgender people has led to broader availability of gender surgery and rapid growth in transition-related operations. Facial gender surgery aims to modify patients' facial features to be more congruent with their physical expression of gender, reducing gender dysphoria and improving quality of life. Growth in research and technique evolution has not kept pace with growth in clinical volume. Therefore, the first International Facial Gender Symposium was held at Johns Hopkins University in 2019, convening surgeons who perform facial gender surgery to share ideas and assess the state of clinical evidence. To review the literature on facial gender surgery, the authors developed a search strategy for seven electronic databases (PubMed, PsycINFO, Embase, CINAHL, Web of Science, Cochrane, and Gender Studies) through May of 2019, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review guidelines. Based on the English language literature and clinical experience, the authors suggest guidelines for screening, management, and appropriate surgical technique for patients undergoing facial gender surgery. They highlight facial gender surgery as a medically necessary intervention and identify shortcomings in current guidelines. Facial gender surgery represents a complex array of craniofacial and soft-tissue procedures that require application of advanced skills and decision-making. Facial gender operations are not cosmetic, are medically necessary, and require development of new CPT codes specific to facial gender surgery. It is imperative to create educational programs and methods to define sufficient training for facial gender surgery surgeons. Research priorities include better procedural outcomes data, more quality-of-life studies, and insight into variation in both patient and procedural subgroups.

How facial aging affects perceived gender: Insights from maximum likelihood conjoint measurement.

Conjoint measurement was used to investigate the joint influence of facial gender and facial age on perceived gender (Experiment 1) and perceived age (Experiment 2). A set of 25 faces was created, covarying independently five levels of gender (from feminine to masculine) and five levels of age (from young to old). Two independent groups of observers were presented with all possible pairs of faces from this set and compared which member of the pair appeared as more masculine (Experiment 1) or older (Experiment 2). Three nested models of the contribution of gender and age to judgment (i.e., independent, additive, and saturated) were fit to the data using maximum likelihood. The results showed that both gender and age contributed to the perceived gender and age of the faces according to a saturated observer model. In judgments of gender (Experiment 1), female faces were perceived as more masculine as they became older. In judgments of age (Experiment 2), young faces (age 20 and 30) were perceived as older as they became more masculine. Taken together, the results entail that: (a) observers integrate facial gender and age information when judging either of the dimensions, and that (b) cues for femininity and cues for aging are negatively correlated. This correlation exerts stronger influence on female faces, and can explain the success of cosmetics in concealing signs of aging and exaggerating sexually dimorphic features.

Swapping Gender is a Snap(chat)

In May 2019 the photographic cellphone application Snapchat released two company-generated image filters that were officially dubbed “My Twin” and “My Other Twin,” though users and media labeled them as feminine and masculine, respectively. While touted in most commentary as a “gender swap” feature, these digital imaginaries represent a unique opportunity to consider what features contribute to classification of faces into binary gender buckets. After all, the commonly considered “male” filter makes various modifications—including a broader jaw and addition of facial hair—to whichever face is selected in the photograph. It does not ask and cannot detect if that face belongs to a man or woman (cis- or transgender) or to a non-binary individual. Instead, the augmented reality that it offers is a preprogrammed algorithmic reinscription of reductive gendered norms. When interacting with a novel face, humans similarly implement algorithms to assign a gender to that face. The Snapchat “My Twin” filters—which are not neutral, but rather human-designed—offer an analyzable projection of one such binarization, which is otherwise rarely articulated or visually recreated. Here I pair an ethnographic exploration of twenty-eight transgender, non-binary, and/or gender diverse individuals’ embodied experiences of facial gender legibility throughout life and with digital distortion, with a quantitative analysis of the “My Twin” filter facial distortions, to better understand the role of technology in reimaginations of who and what we see in the mirror.