What Makes A Sense Of Encounters Or Experiences You Have Had?

The first four paragraphs of this article provide specific examples of “fat bias.” These examples fit perfectly is the

However, of that 48%, only 24% of them are involved in a STEM field. However, statistics are saying now, more than ever, women are pursuing STEM careers. Yet, what happens behind the scenes while earning your degree? My mother has experienced a prime example of exactly what happens when women attempt to pursue a STEM career. She had decided on taking a programming course in college. Long story short, she got to her assigned computer and began to design her screen like the creative woman she is. Her professor walked up to her found it unrighteous to have her computer screen pink when everyone else's where "manly" colors. He suggested that she goes to the counselor to change courses since technology was "manly" thing. Sadly, she listened along with many other women. I say that because "...nearly a third of women in science, engineering and technology (S.E.T.) fields say they are likely to quit within a year," (Sherbin, ...Bias in Their Labs). It's unfortunate that women all over feel that they are not worthy because of their gender or their lack of "manliness." STEM fields aren't a manly thing, they need to be identified as gender neutral profession, as every profession should

As a student coming from a purely humanities background, the idea that gender discrimination could occur in the field of science as a concept was completely alien to me. However it has come to light that gender discrimination in the field of science is not a myth but in fact a harsh reality for which the reasons remain skewed.

Words were used to describe positive associations or negative associations. The test was based on how people view fat or thin people subconsciously or consciously. Compared to the more personal test regarding racial profiling, this test’s results were not as poignant or one-sided. The general populace in statistics did score that thin people gave a higher positive reaction. However, moderate positive reactions were nearly equal. The absolute neutral position where one feels equal toward either size was high and showed that being fat is becoming more acceptable. The lower end preference of fat over thin was low but it was prevalent enough to record. The test findings were about on par with how society views fat and thin people. With the advent of obesity, tolerance for the obese is becoming acceptable. It is unclear whether this is because this is an emerging social norm due to the rise in obesity or if it is an indication that mainstream media is promoting full-size and plus-size models and outfits that flatter fat people. Regardless, the tests show an increasing tolerance for fat

Upon first glance, Takaki’s evidence seems to be very convincing. He seems to point to population size as a possible confounding variable in public perception. He also says that while Asians may hold high positions in certain companies, this fact may only be because Asians have more education than their peers. He also points out, in an attempt to turn this “stereotype” on its head, that many Asian grocery

The purpose of this study was to determine if there was a significant correlation between subjects' results on the IAT and their responses in the explicit survey. Our survey was designed to measure the same bias that the IAT was measuring. We hypothesized that there would be a correlation between subjects' responses to the explicit surveys and the IAT but that the explicit survey responses would be less biased towards fat people than the results provided by the IAT due to

The force of societal stereotypes is a large part of this gap. Instead of joining STEM careers, the most common careers among women are secretaries, nurses, and elementary and middle school teachers (Mandell). This truly illustrates that when well-rounded, talented women have the choice, they are inclined to delve into the field in which society expects them to belong. In this way, the stereotype of women not being involved in STEM is forcing less women to be involved in these fields. The deficiency of women in technical fields, despite their well-roundedness and ability, can be directly related to unyielding cultural stereotypes that stigmatize women in supposedly masculine fields.

Based on my test, data suggested a slight automatic preference for thin people over fat people. I was semi surprised by these results initially, since I do not like to judge others, especially in regards to how they look.

Concerning the issue of prejudice against Arab Americans, few researches have been done. It is surprising seeing as little attention has been paid to this ethno-religious group whose population rate has tremendously increased after 9/11. However, one study by Park, Felix, and Lee (2007) do give us an idea of how prejudice is expressed, implicitly or explicitly, against Muslim people. In their study, they found that discrimination against Arab Muslims is never shown in an explicit way but rather in a subtle way. They used an Implicit Association

When it comes to weight, I guess I’m neutral about fat and thin people, but carrying out the Implicit Association Test (IAT), the test result suggests that I have a strong automatic preference for fat people compared to thin people.

I decided to take the Gender-Science IAT test. I thought this test would be relevant considering the material so far covered throughout the discussions. My results revealed that I didn’t associate either gender with science or liberal arts. I wasn’t surprised by these results, as I’ve always believed that both genders can study or work within those fields. However, I am aware that I may have that belief and could still have ended up with different results.

I do not necessarily disagree with my score, but I do not think I would consider myself to have a strong automatic preference for thin people over fat people. I believe it is a more moderate preference. I think that a reason for this disagreement between my thoughts and the IAT is due to the wording and order in which the pairs of categories were presented to me. Relatively speaking, the word ‘fat’ has a negative connotation associated with it and the word ‘thin’ has a positive connotation. I think that their choice of these words as opposed to words such as ‘overweight’ and ‘underweight’ might prime the individual towards grouping the categories together without conscious thought.

Hypotheses: Infants and toddlers have an anti-fat bias, that is they prefer a thin person as opposed to a larger person— meaning they have developed an anti- fat prejudice. However, they hypothesized that maternal attitudes toward body shape would be more important for toddlers than for infants.

areas of science, technology, engineering, and mathematics employers are not getting enough women (Pozniak). High school girls only represent 17 percent of computer science Advance Placement (AP) test takers (O'Shea). The most significant group of minorities who are behind in earning computer technology degrees and working in science and mathematical professions are women. “Historically, women’s low representation in science and engineering was said to be due in large part of their lack of ability, interest, or both” (Horning 30). However, this is no longer a true fact according to Ward. Some suggestions to increasing the amount of women in sciences include introducing already present women faculty as mentors. Over the last three decades,

Weight discrimination “generally refers to negative weight-related attitudes toward an overweight or obese individual” (Puhl 1). Obesity numbers started to skyrocket in the 1990s and weight discrimination started to become a problem about five years later. Obese individuals are susceptible to weight discrimination at health care facilities, school, work, and even in personal relationships. Studies have found that the chances of experiencing weight discrimination increase the more an individual weighs. “In our study, 10 percent of overweight women reported weight discrimination, 20 percent of obese women reported weight discrimination and 45 percent of very obese women reported weight discrimination. men were lower, with 3 percent of overweight, 6 percent of obese and 28 percent of very obese men reporting weight discrimination. This finding also tells us that women begin experiencing weight discrimination at lower levels of body weight than men” (Puhl 2). For women weight discrimination is more common than race discrimination.