BY Lyn Mikel Brown

For some time, reality TV, talk shows, soap-operas, and sitcoms have turned their spotlights on women and girls who thrive on competition and nastiness. Few fairytales lack the evil stepmother, wicked witch, or jealous sister. Even cartoons feature mean and sassy girls who only become sweet and innocent when adults appear. And recently, popular books and magazines have turned their gaze away from ways of positively influencing girls' independence and self-esteem and towards the topic of girls' meanness to other girls. What does this say about the way our culture views girlhood? How much do these portrayals affect the way girls view themselves?

In Girlfighting, psychologist and educator Lyn Mikel Brown scrutinizes the way our culture nurtures and reinforces this sort of meanness in girls. She argues that the old adage “girls will be girls”—gossipy, competitive, cliquish, backstabbing— and the idea that fighting is part of a developmental stage or a rite-of-passage, are not acceptable explanations. Instead, she asserts, girls are discouraged from expressing strong feelings and are pressured to fulfill unrealistic expectations, to be popular, and struggle to find their way in a society that still reinforces gender stereotypes and places greater value on boys. Under such pressure, in their frustration and anger, girls (often unconsciously) find it less risky to take out their fears and anxieties on other girls instead of challenging the ways boys treat them, the way the media represents them, or the way the culture at large supports sexist practices.

Girlfighting traces the changes in girls' thoughts, actions and feelings from childhood into young adulthood, providing the developmental understanding and theoretical explanation often lacking in other conversations. Through interviews with over 400 girls of diverse racial, economic, and geographic backgrounds, Brown chronicles the labyrinthine journey girls take from direct and outspoken children who like and trust other girls, to distrusting and competitive young women. She argues that this familiar pathway can and should be interrupted and provides ways to move beyond girlfighting to build girl allies and to support coalitions among girls.

By allowing the voices of girls to be heard, Brown demonstrates the complex and often contradictory realities girls face, helping us to better understand and critique the socializing forces in their lives and challenging us to rethink the messages we send them.

New York; London: NYU Press, 2003. 259p.

By Cindy D. Ness

In low-income U.S. cities, street fights between teenage girls are common. These fights take place at school, on street corners, or in parks, when one girl provokes another to the point that she must either “step up” or be labeled a “punk.” Typically, when girls engage in violence that is not strictly self-defense, they are labeled “delinquent,” their actions taken as a sign of emotional pathology. However, in Why Girls Fight, Cindy D. Ness demonstrates that in poor urban areas this kind of street fighting is seen as a normal part of girlhood and a necessary way to earn respect among peers, as well as a way for girls to attain a sense of mastery and self-esteem in a social setting where legal opportunities for achievement are not otherwise easily available.
Ness spent almost two years in west and northeast Philadelphia to get a sense of how teenage girls experience inflicting physical harm and the meanings they assign to it. While most existing work on girls’ violence deals exclusively with gangs, Ness sheds new light on the everyday street fighting of urban girls, arguing that different cultural standards associated with race and class influence the relationship that girls have to physical aggression.

New York; London: NYU Press, 2010. 198p.

By Muhammad Amien Ibrahim, Samsul Arifin and Eko Setyo Purwanto

Social media moderation is a crucial component to establish healthy online communities and ensuring online safety from hate speech and offensive language. In many cases, hate speech may be targeted at specific gender which could be expressed in many different languages on social media platforms such as Indonesian Twitter. However, difficulties such as data scarcity and the imbalanced gender-based hate speech dataset in Indonesian tweets have slowed the development and implementation of automatic social media moderation. Obtaining more data to increase the number of samples may be costly in terms of resources required to gather and annotate the data. This study looks at the usage of data augmentation methods to increase the amount of textual dataset while keeping the quality of the augmented data. Three augmentation strategies are explored in this study: Random insertion, back translation, and a sequential combination of back translation and random insertion. Additionally, the study examines the preservation of the increased data labels. The performance result demonstrates that classification models trained with augmented data generated from random insertion strategy outperform the other approaches. In terms of label preservation, the three augmentation approaches have been shown to offer enough label preservation without compromising the meaning of the augmented data. The findings imply that by increasing the amount of the dataset while preserving the original label, data augmentation could be utilized to solve issues such as data scarcity and dataset imbalance.

United States, Journal Of Computer Science. 2023, 9pg