There are political movements on-going in Europe and in the Americas, particularly the United States and Canada, concerning the rights and liberties of women.  In some respects these have resulted in political gains for women that are long overdue, such as the right to vote and hold office.  But in other respects women have been accorded unfair advantage when competing against men for status, power, reward, or position, such as the so-called ‘parity’ testing, wherein the test thresholds for women are lower than those for men. 

In some parts of the world, women are brutally suppressed, not being allowed to show their face or hair, in some cases covered from head to foot.  In some countries, particularly African, girls are systematically subjected to clitorectomies, rendering them unable to achieve sexual orgasm as adults.  In some cultures, and countries, women are refused driving permits, and girls are forbidden schooling.  Transcendent Reality opposes these suppressive activities.

Transcendent Reality takes the position that men and women are of equal value to society, and governance should in generally be gender-neutral, allowing females and males to develop all their skills and abilities without suppression or favor.  Each gender should be free to compete according to their natural abilities and talents for status, power, reward, or position. 

When legitimate and relevant testing criteria are established for a position, the passing thresholds should be the same for men and women.  The key operative words in such testing are ‘legitimate’ and ‘relevant.’  Legitimate means that the testing criterion is not designed to artificially eliminate one gender, and relevant means that the test criteria are significantly correlated to job performance.  Significantly correlated means that the test criteria are statistically correlated to job performance, and that correlation is statistically significant. 

The subject of gender equality must be understood in a statistical manner, as gender is a major differentiator in group behavior, and performance.  Men as a category perform some tasks better than women as a category.  And, conversely, women as a category perform other tasks better than men as a category.  That is how humans evolved.

But having said that, an individual man or an individual woman cannot be pre-judged as to their individual capabilities – both must be individually measured and judged.

That this is so is best demonstrated by example.  In the graphic below are presented the distribution of height in adult men and women of Great Britain.  In this graphic the statistical data has been reduced to a smooth probability density function, and plotted using intervals of 5/100^th of a foot (0.6 of an inch).

The pink line on the graphic is a theoretical distribution of height for adult females in Britain, assuming the data sample represents a homogenous population in the characteristic measured.  The blue line is the distribution of height for adult males in Britain, also assuming the data sample represents a homogenous population in the characteristic measured.  The black dotted line is the composite distribution of height in adults without regard to gender.

There are several noteworthy aspects of this graphic that are representative of gender performance measurements in general:

1) The separate height distribution curves (the pink line and the blue line), are what is known as normal Gaussian curves, which represents the random distribution of the characteristic being measured in the population.  When the distribution is completely random, we say that it is normal.  In this case height appears normally (randomly) distributed in both adult males and in adult females. 

3)  The data from which these curves are derived indicate that the mean height (average) male in Britain is six inches taller than the average female.  The statistical mean is defined as height at which 50% of the population is at or taller.  The average and the mean are often used interchangeably in the laity, though mathematically they have slightly different meanings.  The mean can be derived from the graphic by observing the heights at the peak of the curves.  The peak of the pink curve is at 5.25 feet (5’-3”), which is the mean (average) height for adult British females.  The peak of the blue curve is at 5.75 feet (5’-9”) which is the mean (average) height for adult British males.  The difference between the mean (average) heights for men and women is 0.5 feet (6”). Thus when we say that British men are on the average 6” taller than British women, we don’t mean that every man is six inches taller than his female companion, but only that 50 % of the men are six inches or taller than 50% of the women.

4) The standard deviation, of height for either males or females is 2 inches.  There is a statistical formula for calculating the standard deviation, but it can also be gleaned from a different graphic – the cumulative form of the probability density function, also called the cumulative density function, shown below for our British population of adult males and females.

The standard deviation, s, is graphically the difference between the height for 33.33% of the population and 66.67% of the population.  There could be a different standard deviation for men and for women, but in this case it is the same – two inches for each.

 5) The normal range is a less-used, but still very useful, statistic related to the standard deviation.  It consists of two values – the beginning and ending values for the standard deviation (m +s/2), which for our data for women is a range from a height of 5’2” to 5’-4”, and for men is a range of 5’-8” and 5’-10.”  This would mean that a normal British woman would be between 5’2” and 5’-4” in height, and a normal British man would be between 5’-8” and 5’-10” in height.  The normal range is associated with the population percentages at 33.3%, and 66.67%, or the middle one-third of the population.  (These population percentage limits are not obvious from the formula for standard deviation, and have not been verified for other data sets.)    

5) There is one more important statistic – the ratio of men to women at each height interval.  Few, if any, persons in governance know of this statistic, and it is not a widely used statistic by statisticians.  But it is extremely important as a measure of gender bias in social organization and governance. 

In the table below we extract such ratios from our British data set by dividing the frequency of men by the frequency of women for each height interval, or, dividing the frequency of women by the frequency of men, so that we always get a ratio greater than 1 (to avoid dividing by zero). 

In a social setting where men and women might compete for jobs in which height gives a decided advantage, such as basketball, we would use the above table to determine if the actual ratio of women to men given jobs was within statistical expectations.  Suppose that it was determined that a height of 6.50 feet was a legitimate minimum for a professional basket ball player playing on a British team.  In a nation of 80 million people, approximately 30 million of whom are adult females and approximately 30 million are adult males, we would expect at most only one woman to meet this height requirement (30,000,000/57,345,290 = 0.5, or rounded to 1). 

In reality, height is not the only measurable factor determining success and dominance in professional basketball.  Spatial perception and aggressiveness are also important measurable factors.  All of these attributes tend to be male-dominated, that is, males as a group score higher than women as a group.  If we take all three characteristics into account, we would expect that no women in a nation of 80 million would be playing professional basketball with men.  And that would be within the normal statistical expectation based on the random distribution of relevant characteristics by gender. 

In other words, for professional basketball, there would be no legitimate complaint by women’s rights advocacy groups of unfair treatment.

Ratio of males and females
(statistical expectation)

In the above example, men as a group outperformed women as a group, and in most physical traits, including height, weight, muscle strength, spatial orientation, aggression, men as a group dominate.  From this natural physical gender preference evolved the natural role of human males to provide sustenance and protection to the family unit, and to act as warriors in the greater social unit.  There will be, of course, some role reversals naturally occurring, but they will not be a large percentage of the total.

And, there will always be some women who outperform most men in the measure, so until an individual woman is actually measured, one cannot pre-judge her capability – she must be given opportunity to prove herself.

Female dominated traits

The easy-to-measure traits are physical ones dominated by males.  But we expect that there are other important traits dominated by women.  In fact, Educational Psychology aggressively measures gender performance, and great strides have been made in understanding the differences between male and female processing of identical stimulus – often using different parts of the brain, and for different purposes, indicating gender is an important and prevalent genetic performance determinant.   

Moreover, there are many social settings in which male aggression tends to be disruptive such as some school classrooms.  In those cases, it might be a superior trait to be less aggressive, in which case we might expect females as a group to excel over men as a group. 

In the graphic above we show what a female-dominated trait might look like.  We don’t have a widely available and verifiable specific example for two main reasons:

1) female-dominated traits tend to be much harder to define and to measure, and

2)  One of the academic disciplines fields, sociology,  which should be a lead investigator into gender performance, has been infected and almost overrun with militant feminists who deny that there is any genetic component to dimorphic gender performance, and hold the subject as taboo – not to be spoken of, much less investigated.  It is most unfortunate that such militant women, most of whom are man-hating lesbians, have perverted and disrupted an entire academic field.

In regard to female-dominated traits, and the difficulty in defining and measuring them, consider the following: 

1) Males in general devote their physical prowess to champion a female, often for nothing more than the glance of an eye, or the wisp of a smile.  Males engage in mortal combat with each other, or the female’s enemies, just to win her oft-fleeting favor.

2) Women in general know they have this power over men, and practice in childhood to hone their skill in acquiring their champions.  They do not need their own arm to be strong to be able to wield a sword or a plow, as they can command their champions to do that effort for them.

3) The most effective women ally themselves with powerful men to rise to power and gain superior benefits.  And it is not in their best interests to reveal the nature of that power to men – thus this advantage lies hidden and largely unmeasured.

Thus it is that much work remains to be done in measuring the traits dominated by women.  In order to for the subject of disproportionate gender bias to be fairly evaluated, a fair representation of the traits favorable to each gender, and those that may be gender neutral, is needed.  We need to have a fair idea of the natural ratio of men to women at each level of performance measurement for all those traits.

Domestic violence

One of the more important political issues in gender is that of domestic violence.  The popular press tends to only report instances of male-on-female violence, and ignore those of female-on-male.  Legitimate statistical studies indicate that the rate of occurrence of male-on-female violence is about the same rate as female-on-male, and at about the same level of violence.  This biased reporting results in the misleading public perception that women are always the victims of domestic violence, when in reality they are equally the perpetrators.  Unfortunately, this misleading public perception has often resulted in laws and regulation unduly and unnecessarily favoring women, to the exclusion of men.

This biased public perception comes about because of advocacy from militant women’s rights groups, liberal politicians supporting their unsubstantiated claims, and the liberal media championing their cause.  It is another example of deliberate deception that has no legitimate place in governance.

There are other evils resulting from this domestic violence deception.  State and local governments have built safe houses for battered women in the misguided perception that most women are routinely battered.  That in itself appears to be a noble effort, were it actually true, and battered men also accepted.  But the actual utilization of these so-called ‘battered women’ shelters is by divorce lawyers who routinely send their female clients to such shelters in an attempt to insinuate violence where none has occurred, in the all-too-often-realized hope of gaining larger awards for his female client. 

There is a deliberate effort by divorce lawyers to churn the divorce mill by promising their women clients all the assets of the husband, and a lifetime of substantial financial support.  Many a disaffected wife has been attracted to the prospect of having herself and her boyfriend supported by her ex-husband.  An evil coalition of divorce lawyers, and anti-family, man-hating, lesbian-dominated militant women’s rights groups, along with their sympathetic representatives in governance, have managed to pervert the legal system to accomplish just that.

Under the guise of gender bias and suppression of women, some of which is prevalent in some parts of the world, many western governments have over-reacted to such an extent that the continuance of the basic two-parent family is under severe threat.

Caveats

The example on the heights of Brits assumed a homogeneous population with only randomly distributed population characteristics.  We did this in creating the probability density function from the data, assuming the sample parameters are identical to the population parameters, and all the variance in height is caused only by randomness or gender, which is tantamount to assuming a single ethnic group. 

In reality, Great Britain has numerous ethnic groups which have not intermarried into the general population, and it is highly likely that our assumption of homogeneity results in some error.  Additional error might exist due to non-representative sampling of such ethnic groups within Britain.  The data used for this example had no ethnic category associated with it, so we cannot control for or investigate the effects of ethnicity.  

To illustrate how ethnicity might affect the population distribution of height, consider the Watutsi of Africa.  Adult males routinely reach over seven feet in height.  Adult females may average over six feet tall – far taller than most men in Great Britain.  If there are some Watutsi in Great Britain, it is possible that no Watutsi was included in the sample, or it is also possible that too many Watutsi were included.  Unless ethnic data is included in the sample data, we cannot know.