| White | Jewish | Asian | Total | Visuals | Info |
|---|
|
| Forebears | 3 | | 1 | 4 | | |
| Kairos | 3 | | | 3 | | A third party facial recognition software company we used to maintain objectivity. Upload images to the facial recognition demo page to check the veracity of our data set. Or use their API and do a bulk peer review if you'd like. Source: https://www.kairos.com/demos |
| Surname | 1 | 1 | | 2 | | A third party free program that uses US Census data to create an algorithm that analyzes surnames and guesses what ethnicity the person is. Obviously there are issues with this data set such as African Americans who have the last names of their ancestors' slave owner. However, when no other data set is available, this can give a rough estimate and expand the data pool for the less important cast members with no IMDb or TMDb image. Please consider downloading their source code via GitHub to verify the accuracy of our data set, and to peer review our conclusions. Source: https://pypi.org/project/ethnicolr/ |
| Ethnic | 1 | | | 1 | | This is the most reliable data source for accurate ethnic breakdowns of famous people. Often the information is crowdsourced by users and they cite all their sources (family trees, obituaries, census archives, etc.) on the bottom of the page. The only issue is converting their ambiguous and inconsistent verdicts into quantifiable variables. Source: https://ethnicelebs.com/ |
| Bettaface | 1 | | | 1 | | A third party facial recognition software company we used to maintain objectivity. Upload images to the facial recognition demo page to check the veracity of our data set. Or use their API and do a bulk peer review if you'd like. Source: https://www.betafaceapi.com/demo_old.html |
| Total | 9 | 1 | 1 | 11 | | |
|---|
| Cast Percentages | 81.82% | 9.09% | 9.09% | 100% | {"name":"Cast Percentages","series":[{"name":"White","y":81.82,"color":"#2b908f","sliced":true,"selected":true},{"name":"Jewish","y":9.09,"color":"#ff0066","sliced":true,"selected":true},{"name":"Asian","y":9.09,"color":"#90ee7e","sliced":true,"selected":true}],"prefix":""} |
|---|
| U.S. Population (2020) Percentage | 57.84% | 2.02% | 6% | | {"name":"U.S. Population (2020)","series":[{"name":"White","y":57.84,"color":"#2b908f"},{"name":"Arab","y":0.54,"color":"#DF5353"},{"name":"Asian","y":6,"color":"#90ee7e"},{"name":"Black","y":12.4,"color":"#f45b5b"},{"name":"Indian","y":1.35,"color":"#7798BF"},{"name":"Indigenous","y":1.12,"color":"#aaeeee"},{"name":"Latino","y":18.73,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":9.32,"color":"#55BF3B"},{"name":"Jewish","y":2.02,"color":"#ff0066"}],"prefix":""} | Source:
US Census
(Note: Racial and ethnic categories overlap so the sum will not equal 100%.) |
| U.S. Population (2020) Representation | +23.98 | +7.07 | +3.09 | | {"name":"U.S. Population (2020)","series":[["White",57.84],["Jewish",2.02],["Asian",6]],"cast":[{"name":"White","y":81.82,"color":"#2b908f"},{"name":"Jewish","y":9.09,"color":"#ff0066"},{"name":"Asian","y":9.09,"color":"#90ee7e"}]} | |
| U.S. Buying Power (2023) Percentage | 72.69% | | 6.97% | | {"name":"U.S. Buying Power (2023)","series":[{"name":"White","y":13897000000000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1333100000000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1533100000000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":136400000000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1924000000000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":295300000000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"} | |
| U.S. Buying Power (2023) Representation | +9.13 | | +2.12 | | {"name":"U.S. Buying Power (2023)","series":[["White",72.69],["Jewish",0],["Asian",6.97]],"cast":[{"name":"White","y":81.82,"color":"#2b908f"},{"name":"Jewish","y":9.09,"color":"#ff0066"},{"name":"Asian","y":9.09,"color":"#90ee7e"}]} | |
| U.S. Average Individual Income (2018) Percentage | 65.34% | | 7.52% | | {"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11825174998483,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1360705388565,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1706765993728,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":164296821776,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1721419354421,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":1318328353188,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"} | |
| U.S. Average Individual Income (2018) Representation | +16.48 | | +1.57 | | {"name":"U.S. Average Individual Income (2018)","series":[["White",65.34],["Jewish",0],["Asian",7.52]],"cast":[{"name":"White","y":81.82,"color":"#2b908f"},{"name":"Jewish","y":9.09,"color":"#ff0066"},{"name":"Asian","y":9.09,"color":"#90ee7e"}]} | |
| World population (2019) Percentage | 14.24% | 0.34% | 31.25% | | {"name":"World population (2019) ","series":[{"name":"Mixed \/ Other","y":14688882870,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":42991259469,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Indigenous","y":10971786583,"color":"#aaeeee","sliced":true,"selected":true},{"name":"White","y":108889096410,"color":"#2b908f","sliced":true,"selected":true},{"name":"Black","y":110601821551,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Asian","y":238860161621,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Arab","y":67406299429,"color":"#DF5353","sliced":true,"selected":true},{"name":"Indian","y":167470202093,"color":"#7798BF","sliced":true,"selected":true},{"name":"Jewish","y":2568698093,"color":"#ff0066","sliced":true,"selected":true}],"prefix":""} | |
| World population (2019) Representation | +67.58 | +8.75 | -22.16 | | {"name":"World population (2019) ","series":[["White",14.24],["Jewish",0.34],["Asian",31.25]],"cast":[{"name":"White","y":81.82,"color":"#2b908f"},{"name":"Jewish","y":9.09,"color":"#ff0066"},{"name":"Asian","y":9.09,"color":"#90ee7e"}]} | |
| World Buying Power Percentage | 36.48% | 1.11% | 29.46% | | {"name":"World Buying Power","series":[{"name":"White","y":3010602822170000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Latino","y":771525888400000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Jewish","y":91700962050000,"color":"#ff0066","sliced":true,"selected":true},{"name":"Black","y":526264226360000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indigenous","y":174285727610000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":148984454560000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Arab","y":526400066100000,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":2431392083750000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Indian","y":572687873900000,"color":"#7798BF","sliced":true,"selected":true}],"prefix":"$"} | |
| World Buying Power Representation | +45.34 | +7.98 | -20.37 | | {"name":"World Buying Power","series":[["White",36.48],["Jewish",1.11],["Asian",29.46]],"cast":[{"name":"White","y":81.82,"color":"#2b908f"},{"name":"Jewish","y":9.09,"color":"#ff0066"},{"name":"Asian","y":9.09,"color":"#90ee7e"}]} | |
| Notes | | If there were any inconsistencies with percentages calculated using our Census data, the Jewish Data Bank percentages were the ones used. Also please review the Jewish Data Bank pdf to understand the difference between the "Core" Jewish population and the "Extended" / "Law of Return" Jewish populations. We are displaying the "Core" Jewish populations since that is what the Jewish Data Bank and Wikipedia articles chose.
Also, the 1942 population estimates were used for the 1940 row. For the 2000 estimates, the "Core" definition was not used, so we used the 5.2 mil broader estimate instead of the 4.3 mil estimate since the 5.2 broader estimate seemed too drastic of a drop and the definitions weren't congruent with Core and Law of Return.
| The US Census considers Pakistani, Sri Lankan, Indian, and Bangladeshi as Asians. At ZR we group Pakistanis with the Arab world. And we group Sri Lankan and Bangladeshi with India because 1.) they are all genetically similar as "South Asians and 2.) there are only a handful of actors from those regions in our database.
However, you are viewing the "Asian Alone" category from the US Census when comparing it with Domestic representation. Also note that the 2000 and 2010 estimates include MultiRacial Asians not just "Asian Alone" estimates, and in some categories they include Native Hawaiians as "Asian."
So there is a margin of error less than 1% and some inconsistencies with the grouping. | |
