Article citation: The role of symmetry in attraction to average faces by Benedict C. Jones, Lisa M. DeBruine and Anthony C. Little, Perception & Psychophysics 2007, 69 (8), 1273-1277
Link to article: www.facelab.org/include/download?id=159
This paper studies the extent to which symmetry contributes to the attractiveness of average faces. Average faces are highly symmetric and increasing the symmetry of face images increases their attractiveness. The authors also demonstrated that increasing averageness of 2-D face shape independently of symmetry is sufficient to increase attractiveness. Additionally, they showed that averageness preferences are significantly weaker when the effects of symmetry are controlled for using computer graphic methods than when the effects of symmetry are not controlled for, suggesting that symmetry contributes to the attractiveness of average faces.
Stimuli. Full color, front view face images of 30 young female adults (age: M 5 18.56 years, SD 5 0.72) with neutral expressions were taken with a digital camera under standardized lighting conditions and against the same background. These images were then aligned to a standard interpupillary distance. These 30 face images were then used to manufacture a female prototype face, with the average color and shape information for the sample and representative texture. The methods used to manufacture this prototype were identical in detail to those used to manufacture composites in previous studies of face preferences.
This nugget describes the following experiment. The photographs of 30 young female s were taken and digitally modified to become symmetric. From these images the researchers constructed an average face. An example of face images used the experiments is shown here.
Although here we have emphasized the role of averageness of 2-D shape for female facial attractiveness, it is important to note that averageness is not the only determinant of attractiveness. Indeed, while the “averageness hypothesis” proposed that average faces are optimally attractive (Langlois & Roggman, 1990), other research has demonstrated that many nonaverage facial cues can have positive effects on attractiveness (e.g., DeBruine, Jones, Unger, Little, & Feinberg, in press; Perrett et al., 1998; Perrett, May, & Yoshikawa, 1994). For example, female faces with exaggerated feminine characteristics (e.g., large eyes, full lips) are more attractive than those with more average features (Perrett et al., 1998; Perrett et al., 1994). The relative contributions of average and nonaverage facial characteristics to attractiveness remain to be investigated.
Our findings for stronger averageness preferences when both symmetry and averageness are manipulated than when averageness alone is manipulated suggest that symmetry contributes to the attractiveness of average faces. As such, our findings present converging evidence that facial symmetry is a cue to attractiveness. Additionally, as both symmetry (Cárdenas & Harris, 2006; Gombrich, 1984) and average configurations (Halberstadt & Rhodes, 2000; Winkielman et al., 2006) are also preferred in nonface stimuli, our findings raise the possibility that symmetry may also contribute to the appeal of average patterns generally.
In this nugget, the authors discuss characteristics that make female faces attractive. Average and symmetric faces are considered more attractive but also faces with exaggerated feminine characteristics, such as large eyes, full lips, are considered more attractive.
Article citation:Enhanced female attractiveness with use of cosmetics and male tipping behavior in restaurants, N., Jacob C., J. Cosmet. Sci, 62, 283-290 (May/June 2011).
Link to article: http://nicolas.gueguen.free.fr/Articles/JCS2011.pdf
Previous studies concluded that women wearing makeup were rated as being cleaner, more tidy, more feminine, and more physically attractive. The intent of this paper was to explore the effect of makeup on individual behavior as contrasted with previous research in which impression formation of facial attractiveness was evaluated in a laboratory. In particular, tipping behavior was used to evaluate the impact of cosmetics. Previous studies showed that diners left larger tips for those waitresses who wore flowers in their hair, or those exhibiting larger smiles. This was particularly true for men rather than for women. Based on previous literature, the authors hypothesized that waitresses’ make-up would increase tipping behavior. Three random variables were examined: the frequency of tips, the amount of tips and the attractiveness of the waitress. Samples from these random variables were subjected to statistical analysis and the conclusions of this analysis confirmed that male patrons gave tips more often to a waitress who wore makeup and that when they did so they gave her a larger amount of money. On the other hand no difference was found in tipping by female patrons when tipping the waitress with or without makeup. The study found no significant difference between attractiveness ratings of the waitress by male and female patrons — both sexes found the waitress to be more attractive when wearing makeup.
This nugget describes, in detail, the setup of the experiment. The experiment that the authors conducted involved 112 single male customers, 62 single female customers, one waitress who was serving meals with and without make-up. The experiment took place in one restaurant in France, where tipping is not usual because a service charge of 12% is added to the bill. It had a duration of 30 days. The tips to the waitress were recorded and the patrons were asked to rate the attractiveness of the waitress on the scale 0 to 9. There are some obvious limitations of this experiment. That the authors used only one waitress and one restaurant is the most significant weakness of the experiment. Otherwise, it seems that the authors tried their best in maintaining objectivity of the experiment.
This nugget summarizes the findings of the study. The article confirmed the initial expectation of the authors that male patrons gave tips more often to a waitress when she was wearing makeup than when she did not wore one. Also the tips were larger when the waitress was wearing makeup. The authors also reported that there was no significant difference in tipping by female patrons when tipping the waitress with or without makeup. Both male and female patrons considered the waitress more attractive when wearing makeup. But wearing makeup was positively correlated with frequency of tipping and amounts of tips only for male patrons. For female patrons, wearing makeup and frequency of tipping, and wearing makeup and amount of money tipped, seem to be independent.
In relation to the paper examined in my previous post, Cosmetics: They Influence More Than Caucasian Female Facial Attractiveness, this paper reconfirms, that in the special case of a waitress, wearing makeup can be financially beneficial to women.
Article citation: Relation between facial morphology, personality and the functions of facial make-up in women, R. Korichi, D. Pelle-de-Queral, G. Gazano and A. Aubert, International Journal of Cosmetic Science, 2011, 33, 338–345.
Link to article:
The paper concerns itself by the study of relations between speciﬁc emotional and psychological proﬁles and the use of makeup. In an experiment, sixty-two Caucasian female subjects, that use makeup daily, were divided into two distinct groups depending whether hey use makeup for camouflage (group C) of seduction (group S). Women in group S had high self-esteem, high assertiveness and low anxiety, while women in group C low self-esteem, low assertiveness and high anxiety. The study revealed that women from the group C have a greater asymmetry of the lower face and that this could be related to a possible larger amount of negative emotional experiences. It was observed that women from the group S more extensively changed their facial attractiveness by using a large range of colors. They also spend more time putting on makeup around mouth and lips area than women in group C. The results of this article suggest that make-up is used differently, depending on psychological profiles of women, to manipulate their facial features to enhance their attractiveness.
These findings are in agreement with the paper “Cosmetics: They Influence More Than Caucasian Female Facial Attractiveness” by NASH, REBECCA FIELDMAN, GEORGE HUSSEY, TREVOR LÉVÊQUE and JEAN-LUC PINEAU, that was discussed in my previous post, which concluded that there are monetary and other benefits offered to women who use makeup to enhance their beauty.
Concerning morphological variables, further analyses of our data revealed significant differences in upper vs. lower facial asymmetry (i.e. eyes and mouth) between our two groups. Indeed, group C subjects have significantly greater lower facial asymmetry than ‘S’ subjects, while expressing marginally lower upper asymmetry. Such differences could be related to fluctuating asymmetry (i.e. random differences between two sides, as opposed to the global asymmetry) that have been argued to develop throughout the lifespan of the individual and would represent a sign of the phenotype being subjected to some levels of stress . Interestingly, some studies reveal that lower face was associated with emotions and more specifically with valence-related asymmetries . As lower face asymmetry is greater in women from group C, it could be hypothesized a link between their facial asymmetry pattern and a possible larger amount of negative emotional experiences , especially as negative emotions implies more salient facial features . Interestingly, mouth asymmetry and make-up duration was highly correlated in subject from group S, but not in group C. As mouth and lips have been related to secondary sexual signals , it could be therefore hypothesized that make-up would be used as a tool to adjust visual asymmetry in women from group S, and therefore increase for potential attractiveness. However, the exact relation between facial asymmetry and emotional expression remains to be further examined.
In this nugget the authors observed that most women’s foreheads are more or less symmetric. The authors report on their observation that women with asymmetric faces use makeup more often to conceal their flaws while women with symmetric faces use makeup more often to make themselves more desirable and attractive. In other words, all experimental subjects used makeup to enhance their looks. So the authors experimentally verified that women don’t use makeup to make themselves less attractive (unless, maybe, if they want to rob the bank, but bank robbers were obviously not part of this study ). This nugget supports the main claim of the paper and is consistent with the results of the paper studied in my previous post.
Total duration of make-up, duration of self-observation and duration of make-up for forehead, eyes, cheekbones, cheeks, chin and neck were not significantly different between C and S groups
(P > 0.22). However, as shown in Fig. 3, subjects from group S displayed significantly longer application of make-up on the mouth and lips area compared to group C (t = 2.098; df = 59;
P < 0.0412). Moreover, make-up duration of the mouth was highly correlated with mouth asymmetry (p9p10) in subjects of the group S (r = 0.938; P 0.31).
In this nugget the authors observed that women in group S spend more time putting on makeup around mouth and lips area than women with bigger facial asymmetries. (Mouth and lips are related to secondary sexual signals.) When a good looking women makeups herself into a stunning beauty, man and companies are willing to pay a huge premium for that. This upgrade can be compared to being promoted from a senior management position to a CEO (a significant salary gap between the two). Therefore, it is logical that women will spend more time transforming themselves into a knock-out (which means that they will also spend more time applying makeup to areas associated with secondary sexual signals such as mouth and lips) than women from camouflage group, who merely want to fix their facial imperfections.
I would like to explore the following question: Does wearing a make-up have a positive impact on women’s career, improves her relationship with a partner and boosts her self-esteem?
In my following few blog posts, I will analyse several scientific papers that were published on his topic in reputable journals.
Article citation :Cosmetics: They Influence More Than Caucasian Female Facial Attractiveness, NASH, REBECCA; FIELDMAN, GEORGE; HUSSEY, TREVOR; LÉVÊQUE, JEAN-LUC; PINEAU, PATRICIA. Journal of Applied Social Psychology. Feb2006, Vol. 36 Issue 2, p493-504.
Link to article: http://www.femininebeauty.info/f/makeup.pdf
The primary goal of the paper is to investigate the effect of makeup on the perception of health, confidence, earning potential, and professional class on Caucasian women in their 30’s. Four volunteers aged 31 to 38 were photographed with and without makeup. To make sure that all faces were as similar as possible from the outset, they each wore a white headband to keep their hair away from their face, removed all jewelry, and wore a black bib to mask their clothes. They were also asked to sustain a relaxed, neutral expression while being photographed. 152 men and 171 women were presented with the women’s facial photographs either with or without cosmetics. Women presented wearing cosmetics were perceived as healthier and more confident than when presented without. Participants also perceived women wearing cosmetics with a greater earning potential and with more prestigious jobs than the same women without cosmetics. The study concluded that women can employ cosmetics to manipulate their appearance and reap up possible benefits, such as being successful at a job interview or negotiating higher salary. By wearing makeup they may also benefit from a boost in positive self-perception and well-being that appears to be associated with wearing makeup.
For analysis, the professions allocated to each image were translated to their social class coding. High, Average, Low, and Unemployed. This converted the results into categorical data, and consequently the results were analyzed using chi-square. Analysis of data revealed that wearing makeup had a significant impact on the rating of a woman’s professional class, chi-square (3, N=1,292) 19.981, p=0.000. The percentage allocation of the four employment categories (Figure 1) revealed that women wearing cosmetics were more likely to be assigned a high- or average-status profession than women without makeup (high status: women With Cosmetics=21.1%, women Without Cosmetics=16.3%; average status: women With Cosmetics 54.69%, women Without Cosmetics=39.8%). By contrast, women without cosmetics were more likely to be assigned a low-status job or unemployed professional status than women with cosmetics (low-status: women Without Cosmetics=37.4%, women With Cosmetics=26.8%; unemployed:
women Without Cosmetics=6.5%, women With Cosmetics=5.2%). Splitting the results by participant sex revealed that the significant effect of cosmetics on the perception of Professional Class was generated by male participants, chi-square (3, N=608) 517.645, p=0.001, rather than female respondents, chi-square (3, N=5684) 53.133, p=0.060.
This nugget provides the statistical data from the experiment and informs the reader about the statistics that were employed to analyze the data. The authors also note that a woman wearing a makeup is more likely to be perceived as professional by men than by women.
In accordance with predictions, wearing cosmetics was found to have a significant impact upon participants’ ratings of female confidence. An intriguing question remains as to whether this effect is genuinely caused by the physical change brought about by the application of makeup or as a consequence
of the general increase in positive self-perception women experience when wearing cosmetics. The volunteers within this study did report feelings of enhanced well-being and improved self-worth when prepared by the beautician. It is possible that this change in self-perception is reflected in the photographs despite the retention of a neutral expression. This question could be resolved by using computer image manipulation to investigate whether makeup renders faces more confident while avoiding the potential confound caused by volunteers’ responses to the application of cosmetics by a beautician. Makeup could be applied digitally onto cosmetic-free female faces, rather than directly onto a volunteer.
In this nugget the authors note that the effect of makeup may also be enhanced by the following effect. A woman wearing make up looks more healthy and more attractive, therefore she feels better about herself. These positive feelings translate in her being more confident, which actually makes her healthier and more attractive.
The following nugget is a prognoses for pancreatic cancer, taken from the online publication “Pancreatic cancer.”
“For all stages combined, the 1-year relative survival rate is 25%, and the 5-year survival is estimated as less than 5% to 6%.
For local disease, the 5-year survival is approximately 20%.
For locally advanced and for metastatic disease, which collectively represent over 80% to 85-90% of individuals, the median survival is about 10 and 6 months, respectively. Without active treatment, metastatic pancreatic cancer has a median survival of 3–5 months; complete remission is very rare.”
As is is clear from the nugget, pancreatic cancer strikes fast and is a deadly disease. It cause about 330,000 deaths worldwide in 2012 and it is the seventh most common cause of deaths due to cancer (fourth in the US). 43,000 people in the US were diagnosed with pancreatic cancer and 37,000 died from it. Pancreatic cancer has one of the highest fatality rates of all cancers. It accounts for only 2.5% of new cases but is responsible for 6% of cancer deaths each year. The disease occurs more often in the developed world, where about 68% of new cases occur. `it is almost never detected in its early stages. Pancreatic cancer often has a poor prognosis, even when diagnosed early. It usually spreads rapidly, which is a main reason of it’s a low survival rates. Signs and symptoms may not appear until pancreatic cancer is in the metastasis stage and is surgically irremovable.
In my previous post, I have discussed ovarian cancer, which is also a very effective killer. Pancreatic and ovarian cancers have lots in common.
Both ovarian and pancreatic cancers are hard to detect. Signs and symptoms are frequently absent in early stages and when they exist they may be subtle. Therefore, these cancers is often misdiagnosed until they are in advanced stages. Most common symptoms include: abdominal or pelvic pain, heartburn, loss of appetite or nausea and vomiting, diarrhea, involuntary weight loss, back pain and tiredness.
For the pancreatic cancer the prognosis was discussed in the nugget.
The five-year survival rate for all stages of ovarian cancer is 47%. For cases where a diagnosis is made early in the disease, when the cancer is still confined to the primary site, the five-year survival rate is 92.7%.
Both cancers are linked to mutations in BRCA2 gene whose mutations also increases risk of breast cancer.
Occurrences of both cancers are effectively through specialized blood tests and CT scans. Until recently these tests were very expensive and therefore rarely used. See here for a recent breakthrough (mentioned also in my previous posts).
The following nugget is from the online publication “How to recognize the symptoms of ovarian cancer”
“Ovarian cancer has been overlooked for a long, long time – it’s been put into the ‘too difficult’ box,’ says Annwen Jones, chief executive of the target Ovarian cancer charity. “There has been a vicious circle: it’s typically diagnosed at a late stage so we have had poor survival rates and, as a result, there’s been little awareness of the disease and therefore very little funding for research. We desperately need to break that circle.”
The main problem is its symptoms: persistent bloating, abdominal or pelvic pain, urinary and/or bowel problems and difficulty in eating.
Taken on its own, each sign could easily indicate some other medical problem. In fact, 30 per cent of sufferers are misdiagnosed with irritable bowel syndrome. It’s only when the symptoms are pieced together that a diagnosis is made easier. For years, ovarian cancer was known as a silent killer, which really frustrates campaigners. “there are clear symptoms,” says Jones. “You just have to know about them.”
Unlike breast cancer, that many are familiar with, only 3% of women in the UK can identify symptoms of ovarian cancer . The symptoms of an ovarian cancer, as described in the nugget above, are often misdiagnosed. One patient notes:
“I thought there was no way it could be cancer – I hadn’t been losing weight, my periods were still regular and I had mistakenly assumed if you had clear smear tests you were fine. It was only later I learned that smear tests will only detect cervical cancer, not ovarian cancer.”
This clearly demonstrates how many women underestimate ovarian cancer. Much of current research is focused on early detection. One promising direction is to focus on so called biomarkers. All diseases have proteins, or concentrations of proteins, specifically linked to them called biomarkers. Identifying biomarkers is a powerful diagnostic tool. Antibodies can be used to test for specific biomarkers because they only bind to specific molecules or groups of molecules. Problems can arise when they bind to groups of similar molecules, leading to false positives and unreliable information.In practice this can be very costly and unreliable method. Jack Andraka delivered a recent breakthrough by finding one particular protein that serves as a biomarker for pancreatic, lung and ovarian cancers and constructing an ingenious testing device for these cancers by utilizing carbon nano-tubes, that is extremely cheap, fast, effective and minimally invasive.
In this inquiry blog am going to focus on types of cancer that are specific for women (such as breast, cervical and ovarian cancer) but I will also try to cover other types of cancer (pancreatic, colon, prostate, blood, bone , skin, etc). Cancer is the second largest cause of death in both men (24.4%) and women (22.1%)in the US, trailing closely behind deaths caused by heart diseases and is number one killer in some subcategories (for instance, cancer in a leading killer in Asian men). While heart diseases are mostly a consequence of unhealthy lifestyles (they are almost absent in poorer countries), cancer is a worldwide killer. Everyone I know, including myself, has a relative or a friend that lost a battle with cancer. I decided to call cancer the silent killer, because symptoms of cancer usually do not appear until it’s too late. In this blog, I hope to bring to the attention of the readers the most common types of cancer. I would especially like to focus on early detection and the latest breakthroughs in treating cancer. There are two recent inspirational videos that I would like to share with you. One is that of Angelina Jolie speaking about her double mastectomy (you are probably familiar with this one already) and the second one is about a high school student who discovered a cheap way to test for early stages of pancreatic, lung and ovarian cancers. (I really hope you will watch this one as it is one of the most empowering videos I have ever watched.) These are my two tesserae with which I am kicking off my research project.
Here are three articles that are relevant to my research that I will incorporate later in the project.
1) Ovarian Cyst. Ovarian cyst is a cyst that has a chance to develop into malignant tumor. Even though that does not happen often. The article discusses early detection, symptoms, tests and treatment of ovarian cancer.
2) U.S. Breast Cancer Statistics. Here we learn some statistics about breast cancer in the USA. About 1 in 8 U.S. women (just under 12%) will develop invasive breast cancer over the course of her lifetime. In 2013, an estimated 232,340 new cases of invasive breast cancer were expected to be diagnosed in women in the U.S., along with 64,640 new cases of non-invasive breast cancer.
3) Genetics and breast cancer. In this article we learn about genetic deviations that cause breast cancer and about choices that one can make to reduce the risk of developing the disease.
Call for response
1) Do you have a friend or family member that has cancer, died of cancer or has been cured from cancer?
2) Is cancer research underfunded?
5,529 people with an AIDS diagnosis died in 2010 in the USA. During 2014, the USA government will spend over $23.2billion for AIDS/HIV research and domestic treatment and additional $6.2 billion for global treatment. 580,350 people with cancer diagnosisdied in 2013 in the USA. In 2013, USA government budget for cancer research and treatment (government provided funding for National Cancer Institute) was $4.9 billion. Thus, about 100 times more people died from cancer than from AIDS/HIV but AIDS/HIV research/treatment received 5 times more money than cancer research/treatment. That means 500 times more money was spend on AIDS/HIV than on cancer per death.
Note: AIDS is not even on the list of 15 most common causes of death in the USA.
When I am thinking, my heartbeat goes up. After few seconds my brain overheats and I develop a splitting headache. The world in front of me starts spinning. I have to blast my favorite music full volume to keep myself from going insane.
Just kidding! This only happens when I think about MATHEMATICS. If I think about other topics, I am mostly just fine. As Dr Vannevar Bush writes in his article, nothing is permanent in our memory. And he is certainly correct in my case. Somehow thinking again and again about certain situation can change the way I remember it. My thinking tends to be visual. I see images and change them into other images. But is this really thinking? Shouldn’t thinking be associated with a logical process? Is it true that by thinking, one should derive consequences from known facts using logical rules? A brief search on the internet produces:
“Thinking can refer to the act of producing thoughts or the process of producing thoughts. In spite of the fact that thought is a fundamental human activity familiar to everyone, there is no generally accepted agreement as to what thought is or how it is created.”(http://en.wikipedia.org/wiki/Portal:Thinking)
Now I need to look-up what is a “thought” in order to understand what is “thinking.
“Thought can refer to the ideas or arrangements of ideas that result from thinking, the act of producing thoughts, or the process of producing thoughts. Despite the fact that thought is a fundamental human activity familiar to everyone, there is no generally accepted agreement as to what thought is or how it is created. Thoughts are the result or product of spontaneous acts of thinking.” (http://en.wikipedia.org/wiki/Thought)
Thus, thinking is the act of producing thoughts and a thought is an idea that results from thinking. I hope you guys can make some sense of it but the only sense I make of it is a picture of a cat spinning faster and faster in a perfectly round circle hoping that when she reaches the ultimate speed she will be able to catch her tail. But alas. This is impossible. According to the theory of relativity, objects moving with a speed close to the speed of light will become shorter (not longer), and therefore, the cat will never be able to catch her tail.
When we say that a machine is thinking we expect a logical process. But it seems to me that we, humans, can be not logical and still call this mental process thinking. Is this a double standard? Maybe. Are we the only animals that think?
Are they thinking?
Our Chihuahua thinks how to get tasty food all the time.