Every Childlike Author needs a Playground.


Female Insecurity

Approximately a month ago, I was fated to come across this article in The Washington Post detailing how “The 10 richest women in the world aren’t entrepreneurs, but heiresses.” Indeed, that is the article’s exact headline. It sparked my curiosity, and caused me to wonder how far down the list of billionaires one had to go in order to find a “self-made” woman—a woman who was both a billionaire and an entrepreneur, rather than the fortunate heiress of a dead rich man. To find out, I went to the unquestioned authority on rich people: Forbes.

After paging through the tiny biographies of more than 500 billionaires consisting of both sexes, I discovered that of those 500 billionaires, only four women could legitimately be termed “self-made,” the first of which only cracked the list at ranking #240 (Chan Laiwa, $6.2B). The second appeared only eight slots later (Jin Sook, $5.9B), yet was co-listed with her husband, Do Won Chang. Dubious as this was, I gave her the benefit of the doubt. Afterwards, the next self-made woman did not appear until #360, and still the next did not appear until ranking #481, respective gaps of 112 and 121 ranking slots between them and the previous self-made female billionaire. The rest of the women in the top 500 rankings were invariably heiresses.

On discovering this, I ruminated on Facebook that there was a seemingly established pattern, that for approximately every one hundred and eight men, there was only one woman who could claim to have an equal measure of talent with the least talented man of the preceding one hundred plus men. Further, I hypothesized that while civilization depended on women, the quality of our civilization depended on men. Outrage ensued, primarily and unsurprisingly from women. Chalk it up to female insecurity.

I was predictably subsequently attacked and vilified for daring to insinuate that women were overall less talented than men. One attack went so far as to attempt to disqualify my observation based on my (relative) youth and apparent lack of success compared to women my age (both of which were not only irrelevant to the subject, but respective examples of ageism and a form of credentialism based on experientialism). Only one of my several attackers managed to address my observation with any intelligence rather than a purely rhetorical knee-jerk emotional reaction. She is to be commended, and it is primarily due to her that I took what little free time I have these days to compile a few of the studies I’ve read in the recent years and which eventually led me to make my controversial observation.

Here I must make a note. Women are not inferior to men or less valuable. I will never assert this position simply because it is not true. Yet I do and will continue to assert that women have naturally inferior skills in certain areas, and vice versa. I do not conflate “all women” and “all men” with women and men in a more general sense. This would be a grave mistake, and if I were to make it I would not blame anyone for discounting anything I might subsequently say on the subject. The fact remains, however, that I have not made this mistake, and therefore am worthy of your attention on this count. What follows is a more detailed defense of my position.

First, I would like you to look around. Note the things in your house, the things in the coffee shop you frequent, the bookstore you go to. Wherever you are at this moment, mentally calculate how many of those items were designed and created by men and how many by women. Obviously we cannot know for sure what was made by a man and what was made by a woman, but it is not too hard to make a guess. I would submit to you that 85% or more are products of men. The computer or phone from which you’re reading this article was created by engineers, a field comprised of 85% men. The walls, surrounding you were created and built by civil engineers and construction crews respectively, the former field comprised of 85% men and the latter comprised of 97% men (the construction field itself is 91%, but construction crews are 97% for obvious reasons). The tables and chairs, couches and sofas, bookshelves and beds which give you comfort everyday were created and designed by carpenters, comprised of 98% men. The dishwasher, electric or gas oven, refrigerator, microwave, blender, air conditioner and heater, the electrical circuitry which lights your home and lets you use all the aforementioned appliances… all designed and installed by men almost without exception. The car you drive, the petrol you purchase, the roads you drive on, the pots and pans and utensils you use for cooking and dining, the food you eat… all produced by mostly men.

Now ask yourself… what would you have without men in the way of comfort and convenience?

Probably Jack. Squat.

The main opposition to this conclusion is that many of these things were being created (furniture goes back hundreds of years, after all) before women began to enter the workforce in significant numbers, or that there is still progress which needs to be made—ergo, if women had been or were currently in the workforce in greater numbers, the credit could not be attributed so definitively to men. Unfortunately, this objection in its myriad forms is absurd, and is statistically and demonstrably false. We could say this for anything: IF X was instead Y, THEN the result of X would be a result of Y. Yet X is not Y, and there is no possible way to test for the purely hypothetical case. It is akin to saying that if men could give birth as women do, then more births would be attributable to men. The argument flies in the face of reality and is therefore dismissed immediately as the pure fantasy it is. And, too, statistically speaking, it simply has not occurred. To show this, I present Exhibit A.

Exhibit A is a study of women’s representation in 60 different occupations from 1972 to 2010, and the study’s results are astounding. Consider the following graph extracted from the study:


Figure 1. Mean percent of women working in 60 occupations as a function of year. doi:10.1371/journal.pone.0095960.g001

Starting from approximately the year 2000, the percentage of women in these 60 different occupations leveled out at around 42.5%, and has stayed there for an entire decade. One who believes women are identical to men in skill and ability will look at these numbers and find them grossly unjust—as half the population, women also ought to make up half the workforce! The Patriarchy is so evil!

But don’t be so quick to get upset. A Gallup poll in early 2012 discovered that 14% of women compared to 6% men are stay-at-home parents with children under 18, and 31% women and 24% men have no children under 18 but are still unemployed. These are differences of 8% and 7% respectively, combining to exactly 15 percent, consistent with the percentage of women needed to make up the missing numbers and make the workforce an exact 1:1 ratio of men and women.

This can hardly be a coincidence. Nor could I have gotten better numbers if I had forged them. I would even go so far as to make the prediction that if one were to examine the unemployment rates from 2000 to now, the average breakdown of men and women who are unemployed would have a difference of about 16%, with approximately 58% and 42% of unemployed men and women respectively, and which would also be consistent with the actual make up of the workforce.

The only conclusion one can make from this is that a significantly greater portion of woman are not looking for work, and an equally greater portion of men are looking for work, resulting in a workforce which reflects that status. From it, we can infer that the cultural wars which got women into the workforce to begin with have succeeded as much as they possibly can, and have in fact, stagnated from at least 2000-2010. The first question this raises is, why have they stagnated? The second question is, how does this relate to men and women’s differences in skill sets?

I’m not here to answer the first question. The second question, however, is of vital importance. By the above, we can see that the percentage of women in the workforce has not changed for at least the decade of 2000-2010. In other words, all the women who are either employed or looking for work have already entered the workforce. No more are forthcoming. If this is so, the credit for any work done by this workforce within that time period cannot be readjusted to fit a hypothetical or ideal model. More credit must by necessity go to men, simply for the reason there are more men in the workforce. Men do 58% of the work, and women do 42%.

I now present you with Exhibit B.

Exhibit B is taken from the same study as Exhibit A, and deals primarily with sex segregation within occupations. That is, what kind of jobs do men and women occupy? From the study:

There are undoubtedly other important job characteristics that contribute to sex segregation as well. Two fundamental dimensions of occupational variation that have been much studied by vocational interest and individual difference researchers are the people-things dimension and the data-ideas dimension [14][17]. The first dimension taps the degree to which occupations deal with people and their psychological dynamics versus inanimate things and mechanical systems. The second dimension taps the degree to which occupations entail routine record-keeping and data management versus creative thinking and the use of intelligence. While women and men do not differ much in their preference for ideas-oriented versus data-oriented jobs, they do differ substantially in their preferences for people-oriented versus things-oriented jobs, with women expressing greater preference for people-oriented jobs and men for things-oriented jobs [14], [18]. This suggests that occupations’ positions on the people-things dimension may predict their degree of sex segregation, but occupations’ positions on the data-ideas dimension may not.

Later in the study:

People-things orientation accounted for slightly more variance than status did in 1972 (24 versus 19 percent, respectively). However, by 2010 people-things accounted for more than seven times as much variance as occupational status did (36 percent versus 5 percent, respectively). Thus, as women increasingly entered high-status occupations from 1972 to 2010, job status became an increasingly weak predictor of women’s participation in occupations, while occupations’ people-things orientation became an increasingly strong predictor.

I will not get into a detailed explanation of their methods, as that can be found in the paper itself. What is important for our purposes is the percent of variance which can be used as a predictor in the differences between men and women’s preferred occupations. In 2010, only 5% of total variance was attributed to occupational status. A high status, high paying job was a poor indicator of whether the person working that job was a man or a woman. In contrast, the people-things orientation was a strong indicator. The sex of engineers, machinists, scientists, mechanics, programmers, electricians, welders, construction workers, farmers, and mathematicians were easier to predict because they were usually men. Essentially any job involved in producing material goods, or advancing technology or scientific knowledge were dominated by the male workforce. On the other side of things, the sex of photographers, secretaries, librarians, nurses, receptionists, real estate agents, waiters, hairdressers, school teachers and social workers were more likely to be women.

And no, this is not because of discrimination or negative expectations in those fields (though those both exist to some small degree) and here is the reason why:

Multilevel linear modeling (MLM) analyses showed that women increasingly entered high-status occupations from 1972 to 2010, but women’s participation in things-oriented occupations (e.g., STEM fields and mechanical and construction trades) remained low and relatively stable.

The gender make up of construction crews hasn’t changed much in 40 years. Nor has the make up of workers in STEM fields. With the increasing number of women who were flocking to jobs for the last 40 years, 40 years of, we are told, terrible gender discrimination, there was hardly any increase in women in these fields whatsoever. In contrast, so many women have obtained high status jobs that it’s difficult to predict what gender fills them, when 40 years ago it would have been easy. If women are just like men, having the same talents to equal measure, then there is absolutely no reason to think that women could not break into these fields in the same way they’ve broken into the higher occupational ranks and high status jobs.

And yet they have not. Why?

There is a very simple reason, of course, but no woman really wants to hear it, and some men aren’t particularly keen on it either because they’re both overly invested in the idea that women are equal to men instead of complementary. The simple reason is that women are not as suited to those jobs as men are, and their suitability is derived from their natural state. While I have not absolutely shown that this is the case, I have, I think, made it abundantly clear that my second hypothesis was correct, namely, that our civilization depends on women and the quality of our civilization depends on men. Men produce goods, specifically food and shelter and technological improvements, and women produce children. Neither are inferior to other and neither are as suitable to the other’s natural tasks. The Forbes’ Billionaire list, as surprising as it is unlikely, indicates and supports this very conclusion.

Now to defend my first observation, that for approximately every one hundred and eight men, there was only one woman who could claim to have an equal measure of talent with the least talented man of the preceding one hundred plus men. Our first order of business on this matter is to push aside the obvious: that men are physically superior to women for nearly all functions except for child birthing and rearing. Any argument against this is futile as it is observably true and easily proven. There is a reason why construction crews are still 98% men, after all.

Our second task is to find out if men are more suited to STEM and related fields than are women. This is not so easily done, but it can be done. To begin doing so, I first present you with Exhibit C.

From a National Bureau of Economic Research (NBER) 2009 study, “An Empirical Analysis of the Gender Gap in Mathematics”:

Figure 1 plots the gender gap on the mathematics and verbal components of the Scholastic Aptitude Test (SAT) – over the past forty years. On the math section, female scores are on average 0.30 standard deviations lower than male scores; on the verbal portion there is no clear gender difference (College Board 2007). 1 An important shortcoming of the SAT data is that the population taking the test is not representative, and sample selection may occur differently across gender. For instance, since college attendance rates are presently higher for females, the female sample of SAT takers may be drawing more heavily from the middle or left tail of the ability distribution. Data from the National Assessment of Educational Progress (NAEP), a nationally representative sample that does not have sample selection problems, also shows boys consistently outperforming girls in fourth and eighth grade over the last two decades, though the magnitude of the gap is smaller (Lee, Grigg, and Dion 2007). The bulk of the evidence in the past 50 years suggests that the gender gap in mathematics does not exist before children enter school, but is large and significant in the middle school years and beyond. For instance, in a meta-analysis of 100 studies with a total sample of more than 3 million students, Hyde et al (1990) found a .29 standard deviation gender gap in math in high school.

Please make note of this statement: “The bulk of the evidence in the past 50 years suggests that the gender gap in mathematics does not exist before children enter school, but is large and significant in the middle school years and beyond.” Many have taken this to mean that boys and girls start out with equal potential with regards to mathematics which is later destroyed via gender-specific expectations and barriers. While that is not necessarily incorrect, I believe there is a more simple explanation: When everybody starts at zero, everybody is equal.

A simple analogy should suffice to make this explanation more transparent. At the beginning of a basketball game, both teams start off at zero points, at equal spots. No one has taken a shot yet. Nothing has happened. One team is made up of slightly shorter, slower players and the other team is made up of slightly taller, faster players. Everything else, shooting skill, ball handling, passing, etc., is equal except for disparity in speed and height. Then the whistle blows, and as the game goes on, the gap in score begins to widen from nothing to a little, to a lot.

This is exactly what happens for men and women with math. As schooling continues, men’s natural proclivities began to widen the gap, from zero all the way to 0.30 standard deviations. In a footnote, the NBER paper further states:

Among elite achievers, these differences are even more pronounced. Men outnumber women by more than two to one above the 99th percentile in SAT mathematics scores (College Board 2007). Males also score four percent higher on AP calculus exams and 6 percent higher on AP science exams (Freeman 2004, College Board 2007).

The paper continues:

The patterns on math tests are especially striking when one considers that females either systematically outperform males or have made enormous gains on many educational dimensions. The high school dropout rate is 28% for females compared to 35% for males (Greene and Winters 2006). As noted by Goldin, Katz, & Kuziemko (2006), in 2003 there were 1.35 females graduating from four-year colleges for every male. In stark contrast, in 1960 there were 1.6 males graduating from 4-year colleges for each female. In 1970, women made up only 9% of combined Medicine, Dentistry, and Law degree recipients. Thirty years later, women accounted for 47% of full time, and 44% of part-time students pursuing such degrees (Freeman 2004). Women make up 45% of all doctorate degrees (Freeman 2004). A 2000 study, commissioned by the U.S. Congress, found that “[t]he large gaps in educational attainment that once existed between men and women have in most cases been eliminated” (Bae et al. 2000).

With such awesome changes in education, how is it possible that science and math are the only areas where females cannot seem to catch up? There is a simple answer, which ironically is just outside the scope of the author’s paper. The emphasis is mine:

Due to limitations of the data, we can test only a subset of the possible socialization theories for the divergent trajectory of girls’ math scores in the early years of school, and none of the biological explanations. Among those hypotheses that we can test, we fail to uncover compelling support for any of them.

Among those possible socialization theories which they tested were: family background, school and neighborhood characteristics, teacher and parent assessments and expectations, parent educational prestige levels, and socioeconomic status. And there was nothing. No compelling support for any of them that would help explain the gender gap in mathematics and science. Conveniently left out of the inquiry, however, was a biological explanation. This concludes Exhibit C.

Finally, I give you Exhibit D.

In this study conducted by the Organisation for Economic Co-operation and Development (OECD), the researchers examine mathematics and reading gaps in different countries in an attempt to determine why girls tend to have better reading scores than boys, and why boys tend to have better math scores. From the Executive Summary:

Reading proficiency is the foundation upon which all other learning is built; when boys don’t read well, their performance in other school subjects suffers too.

Indeed. If reading is the foundation of learning, then why, if girls tend to have better reading scores than boys, do boys still outperform girls in mathematics? The study attempts to explain this by citing “math anxiety” in girls.

In the large majority of countries and economies that participate in PISA, among high performing students, girls do worse than boys in mathematics; in no country do they outperform boys at this level. In general, girls have less self-confidence than boys in their ability to solve mathematics or science problems. Girls – even high-achieving girls – are also more likely to express strong feelings of anxiety towards mathematics. On average across OECD countries, the score-point difference in mathematics performance between high-achieving girls and boys is 19 score points. However, when comparing boys and girls who reported similar levels of self-confidence in mathematics and of anxiety towards mathematics, the gender gap in performance disappears.

PISA reveals that girls tend to do better when they are required to work on mathematical or scientific problems that are more similar to those that are routinely encountered in school. But when required to “think like scientists”, girls underperform considerably compared to boys. For example, girls tend to underachieve compared to boys when they are asked to formulate situations mathematically. On average across OECD countries, boys outperform girls in this skill by around 16 PISA score points – the equivalent of nearly five months of school. Boys also outperform girls – by 15 score points – in the ability to apply their knowledge of science to a given situation, to describe or interpret phenomena scientifically and predict changes. This gender difference in the ability to think like a scientist may be related to students’ self-confidence. When students are more self-confident, they give themselves the freedom to fail, to engage in the trial-and-error processes that are fundamental to acquiring knowledge in mathematics and science.

It is no secret that stress and anxiety having impairing effects on reasoning, but the OECD stretches its effects when recalling that, (1) as the organization states, “Reading proficiency is the foundation upon which all other learning is built,” and (2) that girls outperform boys in reading by nearly 38 points.

As results from PISA have shown, girls do very well in school, too. In all countries and economies that participated in PISA 2012, girls outperformed boys in reading by an average of 38 score points (across OECD countries) – the equivalent of one year of school – as they have done consistently throughout all the PISA cycles since 2000. Boys, however, continued to outperform girls in mathematics in 38 participating countries and economies by an average of 11 score points (across OECD countries) – equivalent to around three months of school.

Hence, “when comparing boys and girls who reported similar levels of self-confidence in mathematics and of anxiety towards mathematics,” and who subsequently tested equally well on mathematics, the reading gap between girls and boys must also be taken into account—something OECD failed to do. Consider the following:

The data in Figure 6.2 suggest that trends in the gender gap in performance in different subjects are associated. Countries where girls became better readers between 2003 and 2012 are also generally the same countries where girls improved in mathematics during the same period. For example, in Finland, the gender gap in mathematics, in favour of boys, narrowed by 10 score points between 2003 and 2012. Over the same period, the gender gap in reading, in favour of girls, widened by 18 score points. In Greece, between 2003 and 2012, the gender gap in mathematics, in favour of boys, narrowed by 11 score points while the gender gap in reading, in favour of girls, widened by 13 score points. Similarly, in Sweden during the same period, the gender gap in mathematics, in favour of boys, narrowed by 9 score points while the gender gap in reading, in favour of girls, widened by 14 score points. Among partner countries and economies, similar trends were observed in Macao-China and the Russian Federation (Tables 1.2b and 1.3b).

These results, and the evidence developed in the context of Chapters 2 and 3, suggest that, in general, the gender gap in mathematics tends to be narrow when girls are good students in all subjects. But the factors that help to narrow the gender gap in mathematics also tend to enlarge the gender gap in reading, in favour of girls. Are gender gaps a “zero sum game”, in which education systems, schools and families have to choose whether to create an environment that promotes either boys’ performance or girls’ performance; or are there policies and practices that manage to narrow – or eliminate – all gender gaps in performance simultaneously?

From the first paragraph of the above quote, we can see that for each point scored in reading, we can add from 0.56 up to 0.85 points in math. Remember, girls scored on average 38 points higher than boys on reading. This should add anywhere from 21 to 32 points to their math scores. Only, boys still perform on average 11 points better than girls in math. Even when we eliminate “math anxiety” for girls, girls only manage to score on par with boys. By all accounts, they should be outperforming boys by at least 21 points. Yet they are not.

The OECD continues with their assessments:

Results from the PISA 2009 assessment of reading suggest that a large share of gender differences in reading performance may stem from disparities in how much boys and girls read for enjoyment and in how much boys and girls engage in reading activities. Indeed, the assessment found that if boys enjoyed reading to the same extent as girls do their reading scores would be 23 points higher, on average across OECD countries (Figure 2.11 and Table 2.9k).

Add another 13-18 points to boys’ math scores, if they enjoy reading as much as girls. This means boys, if they enjoy reading as girls do, would score 24 to 29 points higher on mathematics taking into account female “math anxiety” and 13 to 18 points higher sans female “math anxiety.”

There is no middle ground here. Boys are naturally better at math. Period. And by extension, they will also be better at math-heavy science and “thinking like a scientist.” The differences in scoring and thinking cannot be explained by the very real female anxiety which exists. The math simply doesn’t add up.

In summary, my initial observations extrapolated from the Forbes list of billionaires has large quantities of supporting evidence behind them. Does only one girl compared to a hundred boys have comparable talents? It is likely an exaggerated ratio due to the nature of billionaires, but the data on hand seems to point that way, and sometimes explicitly.

From Exhibit C:

On entry to kindergarten, girls make up 45 percent of the top five-percentiles in math test scores; by the end of fifth grade just 28 percent of the top five percent are female. Girls are underrepresented in the bottom tail of the math distribution in kindergarten, but overrepresented in the bottom tail by fifth grade.

From Exhibit D:

Among the top 10% of students in mathematics performance, the gender gap averages 20 score points; and among the top 10% in science, boys score an average of 11 points higher than girls.

Also from Exhibit D:

PISA finds that while boys outperform girls in mathematics, on average, in many countries and economies the gender gap is much wider among top-performing students than among low-performing students (Table 1.3a). In the large majority of countries and economies, high-performing girls do worse in mathematics compared to boys; in no country do they outperform boys at this level, and the magnitude of the gender gap is much greater than it is among students at an average level of performance.


However, even in science there is a sizeable gap in favour of boys among top-performing students. This is a troubling finding, as some believe it is responsible for the under-representation of women in STEM occupations (Summers, 2005; National Academy of Sciences, 2006; Hedges and Nowell, 1995; Bae et al., 2000).

Ultimately, this is in keeping with the list of billionaires, which is essentially the top performing percentage of the world’s population. Within that top percentage, there will be more men than girls, with wider gender gaps than among low performing members of the population. The cases are identical in nature, simply because it is the nature of men and women. I should add that there is nothing inherently wrong in this state of nature—it simply is.

Or you can chalk it up to female insecurity.

Either way, men have the natural advantage, and I stand steadfastly by my original statements.

The Grief Glass

The Playground hasn’t been so playful as of late, likely due to my recently pressurized life. I have less time and less energy to write than ever before, and as a result the words that get published are flavored by the more serious outlook I’ve been forced to pick up. I find this terribly sad, and as the Childlike Author, I can feel the push from all sides attempting to make me grow up.

But I will not.

For one thing, Peter Pan would be disappointed in me.

For another thing, I would almost certainly go insane.

The nature of children is such that if sufficient grief and hardship is meted out to them, their demeanor becomes overly grim and perhaps irreversibly serious. This is typically referred to as maturation, and it may or may not occur before its time. It can happen all at once, or it can happen gradually. It is rather like glass under a dripping faucet… it will eventually fill up, but if the faucet is opened in full the glass will fill up in little more than an instant.

Everyone has their own grief glass, and tiny drips of grief and hardship will eventually fill it to capacity. Children’s glasses are relatively empty compared to an adult’s simply because their glass has not experienced the passage of time for quite as long. But even this means nothing if their faucet is running rather than dripping.

Currently my own faucet of grief and hardship is a bit more open and my grief glass is filling a bit more quickly than I’ve been accustomed to, but then again, I’m a bit of a cheater…

I may or may not have drilled a hole in its bottom.

Mistaking Success for Blunders

The recent shootings in France have sparked quite the discussion on multiple fronts, including the controversial subject of diversity and its effects on a nation. Ultimately, however, it’s not hard to determine what those effects are on such a large scale. When powerful men with powerful armies and powerful weapons discover their differences are not compatible with other powerful men with powerful armies and powerful weapons, there are only two courses of action left, and they both run parallel to the courses taken by two pre-pubescent brothers sharing a bedroom: either slug it out, or define strictly enforced territorial boundaries which if crossed will result in the first option.

In other words, different nationalities and cultures require their own countries where they can live by their own rules. This is done out of mutual respect for the foreign nation’s (1) ability to inflict great harm or kill many members of your native land, and (2) their desire to live in peace and within their own country. If either of these requirements are not met, then one country will inevitably invade the other, and the game will only end when the stipulations are again met through conquest. The conclusion therefore is that diversity results in violence.

But this is diversity on a giant scale. What happens when it occurs on a different, smaller scale? Within, for instance, business or entertainment? In business, diversity of thought is highly valued when creating new products. In entertainment, diversity of thought is valued for much the same reason as business, but on a more fundamental level since the entertainment industry thrives on one thing and one thing alone: story.

More specifically, most writers of fiction know, at least on a theoretical plane, that story itself is based in the resolution of conflict, but that conflict can only occur when there are opposing sides. The main character must be pitted against another character, entity, force, or unsolved problem or else the reader will lose interest. This is true throughout the entertainment industry. Movies and television must have conflict and the promise of resolution or viewers will not enjoy it. Poetry, too, has conflict, as do even the barest lyrics of popular song, and the best music always evokes some kind of emotion in the listener by relating itself to universal human difficulties. Even a simple news article or television exposé follows the pattern of story writing, albeit with a more rigidly defined and drier set of rules. As such, diversity is necessary for a good story simply because it naturally compels conflict, which in turn must be resolved. Resolution is the drug that keeps us reading and watching.

But zooming in too closely does not particularly help us or give us new insight into the effects of diversity, for we are dealing with stories rather than real life. In real life, we deal with sales, and whether or not something sells depends on what your target market is. For instance, this author at Tor.com writes an article with a specific target audience in mind, one which readily enjoys hearing about Disney’s apparent inability to provide true depictions of equality and diversity. The author asserts that Disney’s more recent princess movies, TangledBrave, and Frozen, all make the same “critical mistake.”

Where are all the periphery female characters in Tangled, Frozen, and Brave?

Look, we’ve got two main female characters in Tangled (Rapunzel and Mother Gothel), Brave (Merida and Elinor), and Frozen (Elsa and Anna). Tangled features brief, silent, and grave moments from Rapunzel’s true mother, and all of these films show the occasional peasant woman or palace worker. There are female rock trolls that look exactly like male rock trolls in Frozen, and the whole group basically function as a chorus anyhow. There’s a short cameo by a witch in Brave. And outside of these fleeting examples, every single character of note is male. All of them. Literally.

And yes, this is a problem in practically every movie we watch.

Everyone: let it be known. It’s a problem. No, it’s worse. It’s a mistake. Yet apparently this “critical mistake” did not prevent millions of kids (and adults) from liking the three movies. The reason for this is, shockingly, because the background characters are irrelevant. The story is not about the background characters. In a curiously twisted way, however, it is this same quality of irrelevance that draws the author’s attention and on which she pins her argument. I admit, the significance of this escaped me at first, but now I believe I understand.

It is because the author doesn’t actually want a story. The quotes below should shed some light on this.

Concerning Brave:

For example, what if Merida had triplet sisters? They would have been young enough to keep out of the fight between their older sis and Queen Elinor, but it also would have meant that the people Merida felt closest to in her family weren’t all male. She could have had a strong relationship with her young sisters, which actually would have helped to soothe the entirely gendered aspects of the argument she and her mother are having throughout the film. What Queen Elinor really wants is for Merida to accept some responsibility in her life—but when the entire fight gets codified using terms like “ladylike” and “graceful,” Elinor seems like a parent who is disappointed at her daughter for not fitting into the stereotypical gender boxes. It weakens the whole narrative.

Do you see what I see? If not, here’s another one about Tangled:

So… how to counter these female leading ladies and make certain that boys will still find themselves represented into the tale? Surround them with bands of men, of course! When Rapunzel and Flynn leave her tower, they wind up at a tavern filed with a variety of surly guys who want to turn Flynn over to the crown and collect the reward on his head. Rapunzel sings them a song about following your dreams, and the haggard crew reveal that they all have softer sides. Later, they come to Flynn’s rescue so he can run back to his lady love. And the two accomplices to Flynn’s recent crime, stealing the lost princess’s tiara? Two burly twin brothers.


For Tangled’s part, it would have been pretty adorable if Pascal—or Maximus the war horse!—had been lady animals. Or even better, that band of gruff ruffians at the tavern? Women. Just, the whole lot of them. Why not? Or if Flynn had been pulling his heist with twin sisters. And I’m sure someone is saying “But if they were ladies, he would have flirted with them!” But you know, he could have just… not. He doesn’t have to be interested in every age-appropriate female with a pulse just because he’s a scamp.

You see, what if Merida in Brave had had triplet sisters instead of brothers? Just as the author says, it “would have meant that the people Merida felt closest to in her family weren’t all male. She could have had a strong relationship with her young sisters, which actually would have helped to soothe the entirely gendered aspects of the argument she and her mother are having throughout the film.” Meaning, that the mother-daughter conflict that is the essential basis for the story no longer exists. I mean, gee, if Merida had a better relationship with her mother, then she would have never had the witch turn her into a bear, and everything would have been sooo happy!

And in Tangled, what if the crowded tavern had been full of women instead of men? For one thing, the beautiful Rapunzel would not have been able to charm them at all, and would more likely have been met with icy indifference or cruelty by the lesser female beauties such a place would attract. The story may not have halted in its tracks with such a change, but the roles would most assuredly be reversed, with Flynn flirting his way out of a jam instead of Rapunzel, or else physically cowing the women. But then who would have dared save Flynn in the end? Probably not the women—their nature would not lend itself to such an act. Instead, the story would have ended with Flynn’s execution and Rapunzel back in the tower, ergo, no story at all. Nor would it be in Flynn’s nature to avoid totally seducing twin female accomplices, not to mention making for less than terrifying bad guys. Flynn is, above all, a scoundrel, who likes pretty women and probably isn’t intimidated by less than terrifying bad guys.

In other words, the author’s assertion that “It weakens the whole narrative” is not about the story’s narrative. she doesn’t care about the story. She doesn’t want story. What she wants is grey putrescence because real story subconsciously reminds her too much of the greatest story of all. And when she says “it weakens the whole narrative,” what she means is “the story is too strong.” For such a person as the author of the article, forward is backwards and backwards is forward, and a blunder is preferable to success.

Ultimately the fact remains that the peripheral characters are just that: peripheral. They do not make the story. Nor is their gender an issue for children watching the movies, whose focus will be almost solely on the main characters. The peripheral characters genders will not teach children that women matter less or women matter more. After all, when was the last time that a girl said she wanted to be the background character and not the heroine? When was the last time a boy said he wanted to be the nobody instead of the hero? It is only the twisted mind of a twisted adult who replaces success with blunders and prefers ugliness to beauty. If the author had her way, there would be no true diversity in these stories, effectively removing their status as stories. Each character would think and act the same, and telling such a tale would not be a story at all, but a monotonous and never-ending description without conflict and without resolution.

And that would be a hell to be pitied for anyone who had the misfortune of watching or reading it.

Internet Rhetoric

Today I ran across this popular Internet image:

Yes. This meme IS stupid.

Willy Wonka gives economical advice. So very unusual for a man of his nature.

It is a prime example of Internet Rhetoric, and while it seems simple, it was created by a professional who knows his work. The image does many things, but its primary intention is to elicit an emotional response in the viewer to shape their thinking and direct it to a specific viewpoint. The specific viewpoint in this case is to support a raise in minimum wage from $7.25 to $11.00. This part is obvious considering the “In support of an $11 minimum wage” badge placed clearly in the right corner beneath the first line of text. Yet it is an extremely important part of the rhetoric because the creator wants the viewer to associate their emotion, their sense of sympathy and simultaneous outrage, with the creator’s wares.

In essence, it immediately promises to relieve them of their outrage and their heartbreak by delivering a solution. There is no waiting around for the viewer to think outside the emotional wave. If the viewer is allowed time, then the emotion abates and the creator loses some of his rhetorical advantage. Therein lies the goal of the salesman, the creator of this rhetoric, but how does he obtain the emotional response he needs?

First he must lay the groundwork. He must gain the viewer’s trust and he must show that the minimum wage is not high enough. The perfect way to do both is by flavoring the rhetoric with dialectic. This dialectic is confined almost solely to the statistical numbers presented in the image: 25% and 1120% respectively. But these alone are not enough… the Internet is rampant with false statistics and false stories, and most who visit the world wide web are aware of the pervasive scams located there, to the point where such numbers are disregarded almost without thought. In some ways, the Internet is a massive extension of the state of Missouri, the “Show-me state.” Words in the vein of “Pics or it didn’t happen,” or even the old joke “70% of statistics are made up” become commonplace in the comment sections. This skepticism is healthy, but it can be taken care of rather easily by citing a semi-legitimate source. In this case, the creator of the rhetoric uses CNN.com, a fairly trusted news site.

Now the creator has piggybacked on CNN’s reputation into a position of trust, rather like a virus piggybacks into a computer system on the shoulders of a downloaded file. The user gets the file they wanted, but they also get the virus. Sadly, they won’t know the virus is there until it’s too late. The viewer sees the statistics are from CNN and therefore assumes that the numbers are legitimate. What must be understood however, is that this dialectic is not being used as dialectic… it is being used as a rhetorical device. And now that it has been successfully used as such to gain the viewer’s trust, anything that follows will be taken at relative face value.

Once the salesman clearly establishes in the viewer’s head that the value of the minimum wage is going down and the cost of tuition is going up, only then does he do the rest. “Trust me,” says the salesman, “you care because the poor people earning minimum wage can’t afford an education to help them escape poverty. Isn’t that terrible? Now buy my wares–it’s the solution.”

And that’s how the salesman gets his pay. He has gotten the viewer’s trust and now he kicks them in the gut. Now they’re feeling emotion they didn’t know they had about the subject. What they don’t realize is that the emotion is manufactured and fabricated on the spot. This principle is the same for all rhetoric and good salesmanship, but in this particular case there is a master stroke.

Notice how the creator of the rhetoric uses the “Condescending Wonka” meme generally used to convey sarcasm. In this case, the carefully crafted caption Tell me more about how poverty-wage workers just need to “get an education”? gets flavored by both the quotation marks indicating someone else’s words and the sarcasm associated with the Wonka meme. The effect is threefold.

First, it establishes a link between high tuition costs and minimum wage and why the viewer should care.

Second, it uses the word “poverty” to capture an even greater measure of compassion from the viewer. They immediately think of Oliver Twist levels of poverty, sweet little orphan kids on the street working hard to survive, or some varying degree of this compassion-grabbing scenario.

Third, it instantly disqualifies the opposing viewpoint by depicting it simultaneously as uncaring, unfair, and based outside of statistical and factual evidence.

The first two are ordinary rhetoric. The third is the master stroke. If your opponent cannot argue against you, then you are the victor by default. This is why those who agree with the overall sentiment of the picture will argue almost solely with emotional subject matter using appeals to “fairness” and compassion in order to claim a moral high ground. After all, who can argue against fairness and compassion? The answer is that you can’t argue with it… at least, not by using the more rational dialectical means. The only way you can combat such rhetoric is to meet it on your own terms by refusing to concede the moral high ground, and by using rhetoric to battle rhetoric. The dialectical element will take care of itself as long as you are on the correct side of logic and reason.

That is the rhetorical analysis. Now let us analyze the nearly absent dialectical component.

Since the creator cites CNN.com as his source for the statistics, I went on a little searching spree. I didn’t have to look very hard before I found that the article cited derived some of its information from yet another source: BuzzFeed. In turn, BuzzFeed used Andrew Rossi’s documentary Ivory Tower as the source for their article. I went ahead and started watching the one and a half hour long documentary, and within the first fifteen minutes the statistics in question turned up. I almost stopped right there, but it had been a decently interesting beginning and I wanted to watch the entire thing to make sure I didn’t miss anything important. Unfortunately, what ensued could reasonably be labeled a propaganda piece advocating for free education… and the statistical numbers exhibited in the first quarter of an hour were never cited.

And so I was left wondering. Where did those numbers originate? Where did Andrew Rossi discover that the cost of a college degree had risen 1120% since 1978? And wasn’t that fitting for his documentary, so dramatically convenient, that the number was so unbelievably high?

As a result of my speculation I decided to check the numbers directly and went straight to the Bureau of Labor Statistics and the National Center for Educational Statistics to look at their figures and use their inflation calculator. Here is what I found…

From 1977-1978 and from 1978-1979 tuition for a full year of college at all institutions was an average of $2,411 and $2,587 respectively. Because a year in college typically spans two calendar years, I took the average of the two to get the tuition from 1978 alone, which is $2,499. Adjusted for inflation, the current value comes out to be $9,051. In 2012, average tuition for a full year of college at all institutions was $20,392 (also adjusted for inflation). But after calculating, this gives us only a 125% rise in tuition, 995% lower than the figure put forth in the original source, Ivory Tower. Even accounting for the two years difference between 2012 and 2014 would not give us a 1,120% rise in tuition from 1979 to 2014, as tuition only rises about $1,000 every three years. Take note as well, that the tuition I am discussing above is inclusive of room and board. In other words, there are no more fees to take into account for a student paying for college courses. The number I calculated is the number. It’s not getting any bigger.

No, I thought, it cannot be. Surely the documentary maker Andrew Rossi was a stand up guy, surely he was forthright and honest. And for all I can tell, he might be. Because what he says in his documentary is that the price of college is 1120% higher. Not the price of obtaining a college degree. Not the price of tuition. The price of college. So, while the context seemingly indicates otherwise, Andrew Rossi may be an honest man after all. I certainly don’t have all the facts necessary to say conclusively that he is dishonest. (As a side note, the curious number of 1120% is also given on affordableschools.net in an article titled “20 Tuition-Free Colleges.” No mention of this article is made on CNN.com, BuzzFeed, or the documentary. It is a bit unclear if this source is the true originator, but I have my guesses. And it can’t possibly be a coincidence that the same outrageously high number is again used in connection with free education, right?)

In 1978, minimum wage was $2.65, which adjusted for inflation is $9.60. Taking 2014’s minimum wage of $7.25 we can calculate that the value is 24.5% lower than in 1978. That’s 0.5% lower than the number on the meme, but it’s close enough, so no problem there unless you really want to be a stickler. After all, what’s a 0.5% difference compared to a 995% difference?

The tuition number is so exaggerated it’s laughable. It’s like shooting a basketball and missing by a whopping margin of eight feet (was that supposed to be a pass?) instead of scoring a basket. Yet it serves to show that the creator of this image could have put almost any number he wished as long as he pretended to cite a semi-legitimate source. This makes it clear that the salesman was not using a dialectic argument, but a purely rhetorical one.

By now it should be apparent that this Internet picture was intentionally being deceptive. Not only does it play upon the viewer’s emotions, but the information included in it is false. Even though the price has increased 125%, the reason for this is not because of minimum wage. In fact, minimum wage is irrelevant. Tuition costs have risen because of separate factors such as government subsidies, the increased availability of student loans from both federal and private sources, the massive business structure of modern day universities and colleges with all their amenities, facilities, and luxury student housing, their bloated administrative branches, and the grotesquely high salaries of  their presidents and provosts—all issues which a single picture on the web cannot possibly discuss properly.

But that is the nature of rhetoric. It readily obscures truth.

The Survival of America

In a May, 2014 post on the website American Renaissance, lawyer and public defender Michael Smith describes how blacks behave in court, and attempts to explain why so many of his clients are black and why they behave so poorly. The description is vivid and sadly unsurprising. His explanation too, is mostly correct. What interests me, however, is his apparent lack of understanding amid such an eye-opening environment. After informing the reader that the majority of his clientele are both black and unemployed (with sociopathic tendencies to boot), he goes on to say this:

I am a liberal. I believe that those of us who are able to produce abundance have a moral duty to provide basic food, shelter, and medical care for those who cannot care for themselves. I believe we have this duty even to those who can care for themselves but don’t. This world view requires compassion and a willingness to act on it.

My experience has taught me that we live in a nation in which a jury is more likely to convict a black defendant who has committed a crime against a white. Even the dullest of blacks know this. There would be a lot more black-on-white crime if this were not the case.

However, my experience has also taught me that blacks are different by almost any measure to all other people. They cannot reason as well. They cannot communicate as well. They cannot control their impulses as well. They are a threat to all who cross their paths, black and non-black alike.

I do not know the solution to this problem. I do know that it is wrong to deceive the public. Whatever solutions we seek should be based on the truth rather than what we would prefer was the truth. As for myself, I will continue do my duty to protect the rights of all who need me.

It is difficult to doubt the words of someone so clearly and intimately acquainted with the subject, yet it astounds me that the author’s welfare worldview is unchanged despite his close familiarity with the results of such a system. In other words, public defender Michael Smith believes that the working population procuring its own food, shelter, and medical care, should also be the serving maids and butlers for “those who can care for themselves but don’t.” This is a far cry from the original tenets used to build America, and the total opposite of the philosophy and policy implemented by another Smith in order to make the initial settlement in the New World a possibility. In the words of Captain John Smith, “He who does not work, will not eat.” Jamestown survived because of this policy, but without it America will not. Instead, we will continue to fund the sociopathic and the criminal who threaten our civilization.


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