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Please take my survey regarding gender in cubing!

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#3
Can you please change "females" to "women" ? Thank you :)
“Female” is age-neutral, “women” implies adults. Awkward, but I understand the decision.

I don’t have an opinion on the question, but it should be fairly straightforward to figure out which event has the highest percentage of female competitors ranked in the top 100 and get an objective answer.
 
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#4
“Female” is age-neutral, “women” implies adults. Awkward, but I understand the decision.

I don’t have an opinion on the question, but it should be fairly straightforward to figure out which event has the highest percentage of female competitors ranked in the top 100 and get an objective answer.
Can you please change "females" to "women" ? Thank you :)
I get both of your reasonings here, but I think One Wheel is correct in this context. Women would refer to adults, and not count people below the age of like 18. But in some cases the word female is used unwell. Sorry if I caused any issues.
 
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#5
My message has already created a whole debate that was deleted by moderators, so let's not start another one.
I'm just saying that female is an adjective not a noun, so either say "women" or "female cubers", not "females".
 
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#7
My message has already created a whole debate that was deleted by moderators, so let's not start another one.
I'm just saying that female is an adjective not a noun, so either say "women" or "female cubers", not "females".
Female is also a noun, just as male is.
 
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#8
I don’t have an opinion on the question, but it should be fairly straightforward to figure out which event has the highest percentage of female competitors ranked in the top 100 and get an objective answer.
Out of top 100 in each event:
  1. clock: 8.0%
    minx: 8.0%
  2. 666: 6.0%
    777: 6.0%
  3. 333ft: 4.0%
    skewb: 4.0%
  4. 555: 3.0%
    333mbf: 3.0%
  5. 222: 2.0%
    333bf: 2.0%
    333fm: 2.0%
    444: 2.0%
    555bf: 2.0%
    pyram: 2.0%
    sq1: 2.0%
  6. 333: 1.0%
    333oh: 1.0%
    444bf: 1.0%
 
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#9
Out of top 100 in each event:
  1. clock: 8.0%
    minx: 8.0%
  2. 666: 6.0%
    777: 6.0%
  3. 333ft: 4.0%
    skewb: 4.0%
  4. 555: 3.0%
    333mbf: 3.0%
  5. 222: 2.0%
    333bf: 2.0%
    333fm: 2.0%
    444: 2.0%
    555bf: 2.0%
    pyram: 2.0%
    sq1: 2.0%
  6. 333: 1.0%
    333oh: 1.0%
    444bf: 1.0%
Those numbers are low enough that it’s hard to draw any conclusions. I wonder what it would look like if instead of the top 100 we looked at the top 10%.
 

Aerma

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#10
Those numbers are low enough that it’s hard to draw any conclusions. I wonder what it would look like if instead of the top 100 we looked at the top 10%.
I don't think it's the portion of the data that doesn't mean much, but rather cubing as a whole. If you look at the top 10% and see that, I don't know, 5% are females, that doesn't mean that females are worse than males - just that there are less females who cube.
 
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#11
I don't think it's the portion of the data that doesn't mean much, but rather cubing as a whole. If you look at the top 10% and see that, I don't know, 5% are females, that doesn't mean that females are worse than males - just that there are less females who cube.
If you look at the top 10%, and 18% of females with megaminx averages are in that top 10% then females are relatively better at Megaminx. If the numbers in the top 100 were closer to 20+ that might be a good indicator, but saying that 1 of the top 100 3x3 averages belongs to a female doesn’t really mean anything.
 
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The FitnessGram Pacer Test is a multi stage...
#12
I don't think it's the portion of the data that doesn't mean much, but rather cubing as a whole. If you look at the top 10% and see that, I don't know, 5% are females, that doesn't mean that females are worse than males - just that there are less females who cube.
FEWER NOT LESS
 
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#14
I wonder what it would look like if instead of the top 100 we looked at the top 10%.
Changing from top 100 to top 10% moves a couple of events around:
  1. clock: 7.35%
  2. 333ft: 6.39%
  3. minx: 6.11%
  4. pyram: 4.67%
  5. skewb: 4.22%
  6. 777: 4.09%
  7. 333: 3.47%
  8. 666: 3.46%
  9. 333bf: 3.21%
  10. 444: 2.86%
  11. 333mbf: 2.83%
  12. 333fm: 2.51%
  13. 555: 2.46%
  14. sq1: 2.41%
  15. 222: 2.32%
  16. 333oh: 1.96%
  17. 444bf: 1.12%
  18. 555bf: 0.0%
 

Kit Clement

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#15
I've hypothesized before that there's a relative advantage for female cubers over male cubers in megaminx because of the large number of colors and higher incidence of color blindness (partial or full) in male cubers. The data seem to at least not reject this idea.
 
Last edited:
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#17
Changing from top 100 to top 10% moves a couple of events around:
  1. clock: 7.35%
  2. 333ft: 6.39%
  3. minx: 6.11%
  4. pyram: 4.67%
  5. skewb: 4.22%
  6. 777: 4.09%
  7. 333: 3.47%
  8. 666: 3.46%
  9. 333bf: 3.21%
  10. 444: 2.86%
  11. 333mbf: 2.83%
  12. 333fm: 2.51%
  13. 555: 2.46%
  14. sq1: 2.41%
  15. 222: 2.32%
  16. 333oh: 1.96%
  17. 444bf: 1.12%
  18. 555bf: 0.0%
Fascinating. The color blindness hypothesis makes sense for Megaminx, and maybe even for feet. My first official feet solve I messed up because I confused colors. No idea what the difference would be for clock. But hey, more representation for female cubers, sounds like yet another great argument for keeping feet!

Lmao I'm female and I suck at megamix.
I’m pretty sure practice is a much stronger indicator of Megaminx success than gender.
 
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