Polish Senate members (100) pigmentation

[Lucas]

It is introduction to the topic. Please someone counts it in detailed way but I give you the source:) Yes I am lazy...

For Polish Senate (100 members). Already I checked without counting every shade and various version of grey predominate. Quite many green, pure brown rarer then in official stats at first glance but with dark-mixed which I count as dark too it will be about 23 members.
For hazel / evenly-mixed I wait for someone else estimation first, I am not sure many times if I count it as green on light side, as some are with darker rings or random dots but most of eye looks lighter. Then I can confront my opinion.

In case of some there is no photo in Wikipedia, try to find best possible resolution. For example Lidia Staroń appears brown eyed on smaller images, in one big is dark grey eyed.

https://en.wikipedia.org/wiki/Category:Members_of_the_Senate_of_Poland_2019%E2%8 0%932023

[Supercomputer]

blue 36,3%
grey 21,1%
light mixed 15,1%
evenly mixed 8,1%
dark mixed 9,1%
brown 10,1%

In total 57,4% light eyes and 72,5% if you add light mixed ones. I'm less sure about the blue/grey divide because of weird lighting conditions, it could be that I misclassified some blue eyes under grey and vice versa. One member I did not count because I couldn't inquire his eye colour with enough confidence - Stanisław Ożóg. He probably has some kind of mixed eyes, but I'm not sure what kind.

https://docs.google.com/spreadsheets/d/1RxEEGwymZ__INYxXJePXQngp--0Pvo0LgdVlUcnVngE/edit?usp=sharing

[Creoda]

blue 36,3%
grey 21,1%
light mixed 15,1%
evenly mixed 8,1%
dark mixed 9,1%
brown 10,1%

In total 57,4% light eyes and 72,5% if you add light mixed ones. I'm less sure about the blue/grey divide because of weird lighting conditions, it could be that I misclassified some blue eyes under grey and vice versa. One member I did not count because I couldn't inquire his eye colour with enough confidence - Stanisław Ożóg. He probably has some kind of mixed eyes, but I'm not sure what kind.

https://docs.google.com/spreadsheets/d/1RxEEGwymZ__INYxXJePXQngp--0Pvo0LgdVlUcnVngE/edit?usp=sharing
Much bigger difference there between light and light-mixed than in many NW European countries. The comparison maps should factor in these differences somehow. Showing the prevalence of only one category of pigmentation can be misleading.

[Supercomputer]

Much bigger difference there between light and light-mixed than in many NW European countries. The comparison maps should factor in these differences somehow. Showing the prevalence of only one category of pigmentation can be misleading.

Yeah Polish Senate has more light mixed eyes than other countries. That's why I always include both pure light (blue and grey) and light mixed numbers in the summary. Some people consider light mixed eyes light, others don't.

[cass]

Much bigger difference there between light and light-mixed than in many NW European countries. The comparison maps should factor in these differences somehow. Showing the prevalence of only one category of pigmentation can be misleading.

Any such comparison is illegitimate as he arbitrary exclude or include supposed ethnic minorities in different countries.
Moreover its hardly representative sample as some electoral systems allow transferring candidates from districts strongly dominated by a given party.
exemplum https://en.wikipedia.org/wiki/Marek_Borowski

[Supercomputer]

Any such comparison is illegitimate as he arbitrary exclude or include supposed ethnic minorities in different countries.
Moreover its hardly representative sample as some electoral systems allow transferring candidates from districts strongly dominated by a given party.
exemplum https://en.wikipedia.org/wiki/Marek_Borowski

I am consistent with ethnic minorities. If I come across them I exclude them.

[Creoda]

Yeah Polish Senate has more light mixed eyes than other countries. That's why I always include both pure light (blue and grey) and light mixed numbers in the summary. Some people consider light mixed eyes light, others don't.
Here are weighted scores of some of your stats (where you used the same categories): +2 for light eyes, +1 for light-mixed, 0 for evenly mixed, -1 for dark mixed, -2 for dark. Then I halved the scores.

Sweden: +81.65
Norway: +78.4
Denmark: +70.65
United Kingdom: +60.65
Poland: +50.3
Germany: +47.65
Belgium: +39.35
Austria: +29.2
Slovenia: +23.65
Croatia: +2
----------------------------------------
Romania: -10.3
Serbia: -31.45

These are what percentage each country is lighter eyed than darker eyed in those stats. Something like this would be most appropriate for overall pigmentation maps.

[Supercomputer]

Here are weighted scores of some of your stats (where you used the same categories): +2 for light eyes, +1 for light-mixed, 0 for evenly mixed, -1 for dark mixed, -2 for dark. Then I halved the scores to make the scale more realistic.

Sweden: +81.65
Norway: +78.4
Denmark: +70.65
United Kingdom: +60.65
Poland: +50.3
Germany: +47.65
Belgium: +39.35
Austria: +29.2
Slovenia: +23.65
Croatia: +2
----------------------------------------
Romania: -10.3
Serbia: -31.45

Something like this would be most appropriate for overall pigmentation maps.

I never did a study on Serbian parliament, (I tried, but the search results for parliament gives abysmal image quality results) only on graduate pics. For Croatia I did the study years ago and I used different categories and included all ethnic minorities so I don't know where you get this from.

[cass]

I am consistent with ethnic minorities. If I come across them I exclude them.

I doubt it.
I case of Netherlands you exclude arbitrary 1/3 and in Poland no one (not even one example I provided previously).

If they have the passive election law, they are assimilated and being elected they are hardly foreigners.

[Creoda]

I never did a study on Serbian parliament, (I tried, but the search results for parliament gives abysmal image quality results) only on graduate pics. For Croatia I did the study years ago and I used different categories and included all ethnic minorities so I don't know where you get this from.
I didn't say they were all from Parliaments, it was just a demonstration.

https://www.theapricity.com/forum/showthread.php?358674-Serbia-eye-colour-(Graduate-study)
https://www.theapricity.com/forum/showthread.php?358707-Croatian-eye-colour-(Graduate-study)

[Supercomputer]

I doubt it.
I case of Netherlands you exclude arbitrary 1/3 and in Poland no one (not even one example I provided previously).

If they have the passive election law, they are assimilated and being elected they are hardly foreigners.

The link for Polish senate was given to me by a Polish guy Lucas. He never mentioned any minorities to exclude. How am I supposed to know who is ethnically Polish and who isn't? Ethnic minorities in Poland (if there are any) are all White. I did not come across any foreign looking or foreign sounding Senators on that Wikipedia page. If you know of any tell me and I will fix my results.

[cass]

The link for Polish senate was given to me by a Polish guy Lucas. He never mentioned any minorities to exclude. How am I supposed to know who is ethnically Polish and who isn't? Ethnic minorities in Poland (if there are any) are all White. I did not come across any foreign looking or foreign sounding Senators on that Wikipedia page. If you know of any tell me and I will fix my results.

You answered yourself.
Nobody is authorized do decide whether assimilated half Moroccan, Dutch Indos, Turk or Ashkenazi is white, foreign or not.

[Supercomputer]

You answered yourself.
Nobody is authorized do decide whether assimilated half Moroccan, Dutch Indos, Turk or Ashkenazi is white, foreign or not.

For non Whites you can tell by the picture and name about 95% of the time. For Poland I trusted Lucas because he is Polish and he did not mention any minorities despite browsing that list before he made this thread. For Nordic countries I checked Wikipedia page for every person that looked exotic or had brown eyes just to be sure.

[cass]

For non Whites you can tell by the picture and name about 95% of the time. For Poland I trusted Lucas because he is Polish and he did not mention any minorities despite browsing that list before he made this thread. For Nordic countries I checked Wikipedia page for every person that looked exotic or had brown eyes just to be sure.


Very scientific indeed.

I am sure Lucas is too reasonable person to point out Ashkenazis or other minorities especially those who do not reveal it publicly.

[Supercomputer]

Very scientific indeed.

I am sure Lucas is too reasonable person to point out Ashkenazis or other minorities especially those who do not reveal it publicly.

You're nit-picking. The methodology is good enough to weed out most if not all of minorities. If I had to check Wikipedia for every singe member it would double the time and it still wouldn't be 100% reliable as most Wikipedia articles for most MPs are stubs

[cass]

You're nit-picking. The methodology is good enough to weed out most if not all of minorities. If I had to check Wikipedia for every singe member it would double the time and it still wouldn't be 100% reliable as most Wikipedia articles for most MPs are stubs

Nitpicking?
There are already 1.5 mln Dutch of Indos partial ancestry, fully assimilated.


Just to be sure how did you chose whether they are Dutch or not:
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/rajkowski-qm-vvd
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/wassenberg-fp-pvdd
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/markuszower-g-pvv

[Russki]

For non Whites you can tell by the picture and name about 95% of the time. For Poland I trusted Lucas because he is Polish and he did not mention any minorities despite browsing that list before he made this thread. For Nordic countries I checked Wikipedia page for every person that looked exotic or had brown eyes just to be sure.

And what if ethnic minority has light eyes?

I excluded two light-eyed Tatars in my Russian study.

[Supercomputer]

Nitpicking?
There are already 1.5 mln Dutch of Indos partial ancestry, fully assimilated.


Just to be sure how did you chose whether they are Dutch or not:
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/rajkowski-qm-vvd
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/wassenberg-fp-pvdd
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/markuszower-g-pvv

Yes you are. Fully assimilated does not mean you change your racial appearance. Most don't even change their first or last names. What would you want me to do, email every member and ask them fi they have some Ashkenazi acnestry because I am conducting an eye colour study? I have done plenty of work in my free time, I haven't seen you do any work but shit on work done by others.

[Supercomputer]

And what if ethnic minority has light eyes?

I excluded two light-eyed Tatars in my Russian study.

I didn't say I just use light eyes. I use first name, last name and appearance. If it gives me a strange vibe, I check Wikipedia for possible foreign ancestry. But it still isn't 100% reliable. I doubt the few minorities that are able to slip through affect the results in any significant way. The results match other studies to high degree. That's all I'm willing to do in my free time. If you're not satisfied, do the study yourself.

[cass]

Yes you are. Fully assimilated does not mean you change your racial appearance. Most don't even change their first or last names. What would you want me to do, email every member and ask them fi they have some Ashkenazi acnestry because I am conducting an eye colour study? I have done plenty of work in my free time, I haven't seen you do any work but shit on work done by others.

Can you answer my previous question?
I am very interested in your approach.

[Supercomputer]

Can you answer my previous question?
I am very interested in your approach.

If the name sounded non Dutch, I checked Wikipedia.

[cass]

If the name sounded non Dutch, I checked Wikipedia.

Can you disclose your decision in these specific cases?

https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/rajkowski-qm-vvd
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/wassenberg-fp-pvdd
https://www.houseofrepresentatives.nl/members_of_parliament/members_of_parliament/markuszower-g-pvv

[Supercomputer]

Can you disclose your decision in these specific cases?

You expect me to remember than? Seriously?

[cass]

You expect me to remember than? Seriously?

Ok short memory problems.
I expect rather hasty biased decisions which you are ashamed of now.

[Lucas]

blue 36,3%
grey 21,1%
light mixed 15,1%
evenly mixed 8,1%
dark mixed 9,1%
brown 10,1%

In total 57,4% light eyes and 72,5% if you add light mixed ones. I'm less sure about the blue/grey divide because of weird lighting conditions, it could be that I misclassified some blue eyes under grey and vice versa. One member I did not count because I couldn't inquire his eye colour with enough confidence - Stanisław Ożóg. He probably has some kind of mixed eyes, but I'm not sure what kind.

https://docs.google.com/spreadsheets/d/1RxEEGwymZ__INYxXJePXQngp--0Pvo0LgdVlUcnVngE/edit?usp=sharing

So I have little more dark + dark mixed (23% vs 19%) and here you classified 4% from them as evenly mixed. I don't argue as evenly mixed is hardest category to estimate for me.
I am little surprised that your grey number is much lower then I thought, we must have different definition of it but it is minor difference for me.

In Polish stats from 1956 where every Martin number was provided we had for men:

10,82 % - brown (Martin 1-5)
4,96% - rather mainly dark mixed (Martin 6)
9,9% - dark and evenly mixed (Martin 7)

so 25,68% not light

women

13,89 % - brown (Martin 1-5)
3,32% - rather mainly dark mixed (Martin 6)
12,24% - dark and evenly mixed (Martin 7)

so 29,45% not light

Average for both sexes, not light = 27,56%

So nearly the same like you estimate (26,5%), even your is little lighter.

[Supercomputer]

Ok short memory problems.
I expect rather hasty biased decisions which you are ashamed of now.

No biased decisions. You should be ashamed of accusing me this. I have no incentive to lightwash or darkwash the Dutch.

[Lucas]

@Cass

His estimation is fully concordant with 1956 survey, so don't complain about some of Jewish ancestry, if so how many two or three? And I think not all are brown eyed so it is irrelevant.
Pure browns among Senate members are mostly of typical Alpinoid phenotype, not Armenoid...
.
Like him, otherwise he is in Polish phenotype spectrum too.

https://upload.wikimedia.org/wikipedia/commons/e/ef/Zdzis%C5%82aw_Pupa_Kancelaria_Senatu_2019.jpg

[cass]

@Cass

His estimation is fully concordant with 1956 survey, so don't complain about some of Jewish ancestry, if so how many two or three? And I think not all are brown eyed so it is irrelevant.
Pure browns among Senate members are mostly of typical Alpinoid phenotype, not Armenoid...
.
Like him, otherwise he is in Polish phenotype spectrum too.



I'm just amazed at his arbitrary decisions to reject or include some people from other series.
Complete inconsistency.

[Lucas]

I'm just amazed at his arbitrary decisions to reject or include some people from other series.
Complete inconsistency.

Plesase better discuss in this thread only about Polish Senate members.

[cass]

No biased decisions. You should be ashamed of accusing me this. I have no incentive to lightwash or darkwash the Dutch.

I have my doubts you included Rajewski as Dutch and excluded Ashkenazi persons for example.
Excluding 30% of MP is very suspicious.

[Supercomputer]

I'm just amazed at his arbitrary decisions to reject or include some people from other series.
Complete inconsistency.

Like for example?

[Supercomputer]

I have my doubts you included Rajewski as Dutch and excluded Ashkenazi persons for example.
Excluding 30% of MP is very suspicious.

Why is it suspicious to exclude 30% of Dutch parliament members? The Netherlands is full of people of immigrant descent.

[Lucas]

So I have little more dark + dark mixed (23% vs 19%) and here you classified 4% from them as evenly mixed. I don't argue as evenly mixed is hardest category to estimate for me.
I am little surprised that your grey number is much lower then I thought, we must have different definition of it but it is minor difference for me.

In Polish stats from 1956 where every Martin number was provided we had for men:

10,82 % - brown (Martin 1-5)
4,96% - rather mainly dark mixed (Martin 6)
9,9% - dark and evenly mixed (Martin 7)

so 25,68% not light

women

13,89 % - brown (Martin 1-5)
3,32% - rather mainly dark mixed (Martin 6)
12,24% - dark and evenly mixed (Martin 7)

so 29,45% not light

Average for both sexes, not light = 27,56%

So nearly the same like you estimate (26,5%), even your is little lighter.

In 1956 survey
blue (13-16 Martin) - 42,87% among men, 32.1% women, average 37.59% (Supercomputer Senate estimation 36,3%) [I edited calculation for women and average now is correct)
grey (12-9 Martin) - 19,89% men, 22,98% women, average 21,43% (Supercomputer Senate estimation 21,1%)

green (8 Martin) - 11,56% men, 15,25% women, average 13.4% (Supercomputer estimation 15.1% light mixed)

dark and evenly mixed (6+7 Martin) - average 15,21% (Supercomputer estimation for both 17.2%)
brown (1-5 Martin) - average 12.35% (Supercomputer estimation 10.1%)

[cass]

Like for example?

You have not revealed your personal paricular opinions. You only stated how many you have chosen as “pure”. Some numbers are very suspicious.
Moreover you admitted yourself biased approach for different regions.

For Nordic countries I checked Wikipedia page for every person that looked exotic or had brown eyes just to be sure.

[Creoda]

Best to keep a list of every persons name and recorded pigmentation, for transparency. Can also go back and make changes if necessary.

[Lucas]

Best to keep a list of every persons name and recorded pigmentation, for transparency. Can also go back and make changes if necessary.

I have no doubts Supercomputer estimation is correct, differences with official 1956 survey are 0.3 - 2.2% for a category so in statistical error range.
https://www.theapricity.com/forum/showthread.php?359167-Polish-Senate-members-(100)-pigmentation&p=7427113&viewfull=1#post7427113

[Supercomputer]

So I have little more dark + dark mixed (23% vs 19%) and here you classified 4% from them as evenly mixed. I don't argue as evenly mixed is hardest category to estimate for me.
I am little surprised that your grey number is much lower then I thought, we must have different definition of it but it is minor difference for me.

In Polish stats from 1956 where every Martin number was provided we had for men:

10,82 % - brown (Martin 1-5)
4,96% - rather mainly dark mixed (Martin 6)
9,9% - dark and evenly mixed (Martin 7)

so 25,68% not light

women

13,89 % - brown (Martin 1-5)
3,32% - rather mainly dark mixed (Martin 6)
12,24% - dark and evenly mixed (Martin 7)

so 29,45% not light

Average for both sexes, not light = 27,56%

So nearly the same like you estimate (26,5%), even your is little lighter.

The number for blue eyes is also similar to that 1956 survey. If we look at men (Senators were mainly male) 14-16 it's 35,77 versus 36,3 from me.

[Lucas]

The number for blue eyes is also similar to that 1956 survey. If we look at men (Senators were mainly male) 14-16 it's 35,77 versus 36,3 from me.

Here is detailed breakdown, yes it is nearly the same https://www.theapricity.com/forum/showthread.php?359167-Polish-Senate-members-(100)-pigmentation&p=7427113&viewfull=1#post7427113

I think in case of 1956 really such breakdown for colors is inline with your categories, maybe in other countries grey is also 13, but here is impossible that those numbers especially for grey are not identical. Just a 0.3% difference...

blue (13-16 Martin)
grey (12-9 Martin)
green (8 Martin) - Sup light mixed
dark and evenly mixed (6+7 Martin)
brown (1-5 Martin)

[Supercomputer]

You have not revealed your personal paricular opinions. You only stated how many you have chosen as “pure”. Some numbers are very suspicious.
Moreover you admitted yourself biased approach for different regions.

What opinions? My criteria is clear:

blue and grey - light eyes without notable mixture
light mixed - light eyes with small brown/yellow spots/rings
evenly mixed - dark and light parts approx. equal in size
dark mixed - mostly dark eye, but not entirely.

What numbers are suspicious? The results always match other studies very well. If you want I can cite them for you.

How is that a biased approach? I simply didn't want to bother checking every Polish looking MP with a Polish sounding first and last name if they are really 100% Polish. Poland is pretty homogenous country. It decided it would be a waste of time. For Nordic countries brown eyes are much more suspiscious of foreign ancestry than other places where brown eyes are much less common among the native population and foreign ancestry is more common.

[Lucas]

In 1956 survey
blue (13-16 Martin) - 42,87% among men, 32.1% women, average 37.59% (Supercomputer Senate estimation 36,3%) [I edited calculation for women and average now is correct)
grey (12-9 Martin) - 19,89% men, 22,98% women, average 21,43% (Supercomputer Senate estimation 21,1%)

green (8 Martin) - 11,56% men, 15,25% women, average 13.4% (Supercomputer estimation 15.1% light mixed)

dark and evenly mixed (6+7 Martin) - average 15,21% (Supercomputer estimation for both 17.2%)
brown (1-5 Martin) - average 12.35% (Supercomputer estimation 10.1%)

Here is from original paper [Górny 1972]

https://i.imgur.com/rIrqYLx.jpg


https://i.imgur.com/IPowWTw.jpg