Bizaardvark

Summary: Centers on best friends Paige and Frankie who express their offbeat individuality through funny music videos on their vlog channel Bizaardvark.

Release Date: June 24, 2016

Genres: Comedy, Family

Runtime: 0 h 30 min

MPAA: TV-G

Production: Headquarters Post (HQpost), It's a Laugh Productions

Country: United States

Language: English

N/A

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39%18%

39% of the Stars & Main Cast are Female.

18% of the Stars & Main Cast are "diverse."

White76.47%Latino5.88%Jewish5.88%Asian5.88%Mixed / Other5.88%

N/A

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Race	White	Latino	Mixed / Other	Asian	Jewish	Total	Visuals	Info
Kairos	11	1		1		13		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
Bettaface	2					2		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
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/
Surname					1	1		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/
Forebears		1				1
Total	13	2	1	1	1	18
Cast Percentages	72.22%	11.11%	5.56%	5.56%	5.56%	100%	{"name":"Cast Percentages","series":[{"name":"White","y":72.22,"color":"#2b908f","sliced":true,"selected":true},{"name":"Latino","y":11.11,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Asian","y":5.56,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Jewish","y":5.56,"color":"#ff0066","sliced":true,"selected":true}],"prefix":""}
U.S. Population (2020) Percentage	57.84%	18.73%	9.32%	6%	2.02%		{"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	+14.38	-7.62	-3.76	-0.44	+3.54		{"name":"U.S. Population (2020)","series":[["White",57.84],["Latino",18.73],["Mixed \/ Other",9.32],["Asian",6],["Jewish",2.02]],"cast":[{"name":"White","y":72.22,"color":"#2b908f"},{"name":"Latino","y":11.11,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Asian","y":5.56,"color":"#90ee7e"},{"name":"Jewish","y":5.56,"color":"#ff0066"}]}
U.S. Buying Power (2018) Percentage	74.35%	9.42%	1.38%	6.2%			{"name":"U.S. Buying Power (2018)","series":[{"name":"White","y":12147700000000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1013300000000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1300200000000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":114600000000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1539000000000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":224700000000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2018) Representation	-2.13	+1.69	+4.18	-0.64			{"name":"U.S. Buying Power (2018)","series":[["White",74.35],["Latino",9.42],["Mixed \/ Other",1.38],["Asian",6.2],["Jewish",0]],"cast":[{"name":"White","y":72.22,"color":"#2b908f"},{"name":"Latino","y":11.11,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Asian","y":5.56,"color":"#90ee7e"},{"name":"Jewish","y":5.56,"color":"#ff0066"}]}
U.S. Average Individual Income (2018) Percentage	65.34%	9.51%	7.28%	7.52%			{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11634301323350,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1338741837216,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1679216574979,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":161644857794,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1693633411408,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":1297048822201,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	+6.88	+1.6	-1.72	-1.96			{"name":"U.S. Average Individual Income (2018)","series":[["White",65.34],["Latino",9.51],["Mixed \/ Other",7.28],["Asian",7.52],["Jewish",0]],"cast":[{"name":"White","y":72.22,"color":"#2b908f"},{"name":"Latino","y":11.11,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Asian","y":5.56,"color":"#90ee7e"},{"name":"Jewish","y":5.56,"color":"#ff0066"}]}
World population (2016) Percentage	14.56%	5.65%	1.9%	31.7%	0.34%		{"name":"World population (2016) ","series":[{"name":"Mixed \/ Other","y":14080928408,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":41779986108,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Indigenous","y":10563007755,"color":"#aaeeee","sliced":true,"selected":true},{"name":"White","y":107672581567,"color":"#2b908f","sliced":true,"selected":true},{"name":"Black","y":102800941644,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Asian","y":234445222813,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Arab","y":63813089200,"color":"#DF5353","sliced":true,"selected":true},{"name":"Indian","y":161901582394,"color":"#7798BF","sliced":true,"selected":true},{"name":"Jewish","y":2488256092,"color":"#ff0066","sliced":true,"selected":true}],"prefix":""}	NOTE: ZR is the first organization to ever create a global buying power divided by race. Essentially we just took data from CIA.gov FactBook, UN Population Estimates, and The World Bank's Population Estimates / Purchasing Power Parity Per Capita.
World population (2016) Representation	+57.66	+5.46	+3.66	-26.14	+5.22		{"name":"World population (2016) ","series":[["White",14.56],["Latino",5.65],["Mixed \/ Other",1.9],["Asian",31.7],["Jewish",0.34]],"cast":[{"name":"White","y":72.22,"color":"#2b908f"},{"name":"Latino","y":11.11,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Asian","y":5.56,"color":"#90ee7e"},{"name":"Jewish","y":5.56,"color":"#ff0066"}]}
World Buying Power Percentage	36.48%	9.35%	1.81%	29.46%	1.11%		{"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":"$"}	NOTE: ZR is the first organization to ever create a global buying power divided by race. Essentially we just took data from CIA.gov FactBook, UN Population Estimates, and The World Bank's Population Estimates / Purchasing Power Parity Per Capita.
World Buying Power Representation	+35.74	+1.76	+3.75	-23.9	+4.45		{"name":"World Buying Power","series":[["White",36.48],["Latino",9.35],["Mixed \/ Other",1.81],["Asian",29.46],["Jewish",1.11]],"cast":[{"name":"White","y":72.22,"color":"#2b908f"},{"name":"Latino","y":11.11,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Asian","y":5.56,"color":"#90ee7e"},{"name":"Jewish","y":5.56,"color":"#ff0066"}]}
Notes		Many Latinos check "White" or "Other" on the Census. So this overlaps with "Mixed" race and "White." Also, when there was a discrepancy with the percentage listed on the Wikipedia table and our calculated numbers, the Wiki table's numbers were used. Likewise, when the population total was missing from the Census pdf, the estimate was calculated using the percentage from the Wiki table. NOTE: It turns out that the reason America doesn't have a separate "Latino" race is because the League of Latin American Citizens protested against discrimination towards Mexicans and got themselves to legally be considered "White." Check the research links in our Google Doc for more info.	The "Mixed / Other" categories overlap, and the 2 or more category was not an option until the 2000 Census. So for the combined column, all data will be taken from the "Other" column except for 2000, 2010, & 2020. For those, the average between the "2 or More Races" and "Some Other Race" will be used.	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.	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.

2010s disney channel duo female protagonist schoolgirl

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