Door IQ thread.
i don't know the formula, but I know the potential conclusion: face > everything else
Face > status/height > race/thugness.
All the rest is cope/betabuxxing.
All the rest is cope/betabuxxing.
What you first need to do is standardize each factor into a measure where over 1 is advantage, under 1 is a disadvantage. Then, the outcome product is compared to 1 as the determinant of what your value is. You could also use 0 as your point of reference but I think that this would overcomplicate the process because we are using products and products are bound to run into sign issues (negative * negative = positive).
Here is a simple example of one standardization:
6 feet tall (72 inches) = 1
5 feet tall and below (60 inches and below) = .1
Thus we can come up with the value of every 1 inch above 60 = 1/12th of the difference between 1 and .1 = 1/12 * .9 = 9/120 = 3/40
So, if you're 5'4'' your value in height is .1 + 4 * 3/40 = .1 + 3/10 = .4
If you're 5'10'' your value in height is .1 + 10 * 3/40 = .1 + 3/4 = .85
If you're 6'2'' your height value is 1 + 2 * 3/40 = 1 + 3/20 = 1.15
Etc.
Of course this measurement is probably inaccurate in that your rating should follow a parabolic scale instead of a linear one, but that is more of a theoretical difference as opposed to an implementation difference. My goal here is to provide a base level structure for such a formula - the actual scales are up to you to decide upon and investigate.
Let's continue by making a similar equation for facial rating.
Let's conservatively say that 5/10 is 1, and 0/10 is .1 for examples' sake. Thus we come up with the value of each point above 0/10 to as .9 * 2/10 = 18/100.
A person whose face is objectively 2/10, their face value is .1 + 2 * 18/100 = .1 + 36/100 = .46.
A person whose face is objectively 5/10, their face value is .1 + 5 * 18/100 = .1 + 9/10 = 1.
A person whose face is objectively 8/10 = .1 + 8 * 18/100 = .1 + 144/100 =.1 + 1.44 = 1.54.
Again, this is an oversimplified linear model. I think one could rightfully argue that the difference between 0/10 rating and 2/10 is lesser in terms of sexual attractiveness than a 6/10 and 8/10. Again, this is a gradient likely based on a parabolic ratio that you would have to settle on, but for the purposes of this simplified model we will stick to the linear.
If we assume for the purposes of this example that the only factors that matter are height and face, we can construct the following formula of attractiveness:
Height * face = attractiveness, with 1 being average male attractiveness
In numerical terms it would be:
Y = height in inches above or at 60 inches = .1
X = face rating above or at 0/10 = .1
A = outcome attractiveness rating
(.1 + y * 3/40) * (.1 + x * 18/100) = a
So for a person with a height of 5'4'' and a face of 8/10 we would have:
(.1 + 4 * 3/40) * (.1 + 8 * 18/100) = (.4) * (1.54) = 616/1000 = .616
This means that this person has 61.6% of the chance of ascending in the same situation as a person who is 6 feet tall and 5/10 face, again based off of our oversimplified model of linear attractiveness for both variables.
What you need to do is settle on appropriate scales for all of the above variables in order to devise a formula with a normalized 1 in each measure. As I suggested above, I don't think it is linear but in the form of x^2 or similar.
Here is a simple example of one standardization:
6 feet tall (72 inches) = 1
5 feet tall and below (60 inches and below) = .1
Thus we can come up with the value of every 1 inch above 60 = 1/12th of the difference between 1 and .1 = 1/12 * .9 = 9/120 = 3/40
So, if you're 5'4'' your value in height is .1 + 4 * 3/40 = .1 + 3/10 = .4
If you're 5'10'' your value in height is .1 + 10 * 3/40 = .1 + 3/4 = .85
If you're 6'2'' your height value is 1 + 2 * 3/40 = 1 + 3/20 = 1.15
Etc.
Of course this measurement is probably inaccurate in that your rating should follow a parabolic scale instead of a linear one, but that is more of a theoretical difference as opposed to an implementation difference. My goal here is to provide a base level structure for such a formula - the actual scales are up to you to decide upon and investigate.
Let's continue by making a similar equation for facial rating.
Let's conservatively say that 5/10 is 1, and 0/10 is .1 for examples' sake. Thus we come up with the value of each point above 0/10 to as .9 * 2/10 = 18/100.
A person whose face is objectively 2/10, their face value is .1 + 2 * 18/100 = .1 + 36/100 = .46.
A person whose face is objectively 5/10, their face value is .1 + 5 * 18/100 = .1 + 9/10 = 1.
A person whose face is objectively 8/10 = .1 + 8 * 18/100 = .1 + 144/100 =.1 + 1.44 = 1.54.
Again, this is an oversimplified linear model. I think one could rightfully argue that the difference between 0/10 rating and 2/10 is lesser in terms of sexual attractiveness than a 6/10 and 8/10. Again, this is a gradient likely based on a parabolic ratio that you would have to settle on, but for the purposes of this simplified model we will stick to the linear.
If we assume for the purposes of this example that the only factors that matter are height and face, we can construct the following formula of attractiveness:
Height * face = attractiveness, with 1 being average male attractiveness
In numerical terms it would be:
Y = height in inches above or at 60 inches = .1
X = face rating above or at 0/10 = .1
A = outcome attractiveness rating
(.1 + y * 3/40) * (.1 + x * 18/100) = a
So for a person with a height of 5'4'' and a face of 8/10 we would have:
(.1 + 4 * 3/40) * (.1 + 8 * 18/100) = (.4) * (1.54) = 616/1000 = .616
This means that this person has 61.6% of the chance of ascending in the same situation as a person who is 6 feet tall and 5/10 face, again based off of our oversimplified model of linear attractiveness for both variables.
What you need to do is settle on appropriate scales for all of the above variables in order to devise a formula with a normalized 1 in each measure. As I suggested above, I don't think it is linear but in the form of x^2 or similar.
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Even with this many variables we have not taken foids stats into consideration, ideally we would measure her smv, social media addiction, the population density, the locations gender imbalance,and measure your value - the foid value. That will tell how stacked the deck is vs. the whole range of foids, hint, it's always stacked in her favor
IQ is so high everyone was left speechless. Great job. Wish we had graphs and charts.
x9999
Somewhat IQ post
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