In the Meantime

Summary: A queer woman in her late twenties continuously runs headfirst into an existential crisis over the course of a year.

Genres: Comedy, Drama

Director: Nicholas Anthony

Writer: Nicholas Anthony

Runtime: 1 h 33 min

Country: Australia

Language: English

Movie budget: $ 40,000

Budget:$40K

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20%33%

20% of the Stars & Main Cast are Female.

33% of the Stars & Main Cast are "diverse."

White66.67%Indian33.33%

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CONTENT BREAKDOWN

Methodology

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Cast

Stars:

Supporting cast:

Other Cast, Production

Other cast:

Production:

Representation

Star

Supporting

Other

Production

Race	White	Mixed / Other	Latino	Indian	Black	Total	Visuals	Info
Kairos	8					8		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
Forebears	3		1	1	1	6
Ethnic	2	1				3		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/
Total	14	1	1	1	1	18
Cast Percentages	77.78%	5.56%	5.56%	5.56%	5.56%	100%	{"name":"Cast Percentages","series":[{"name":"White","y":77.78,"color":"#2b908f","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":5.56,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Indian","y":5.56,"color":"#7798BF","sliced":true,"selected":true},{"name":"Black","y":5.56,"color":"#f45b5b","sliced":true,"selected":true}],"prefix":""}
U.S. Population (1950) Percentage	89.5%	0.03%	2.1%		10%		{"name":"U.S. Population (1950)","series":[{"name":"White","y":89.5,"color":"#2b908f"},{"name":"Arab","y":0,"color":"#DF5353"},{"name":"Asian","y":0.21,"color":"#90ee7e"},{"name":"Black","y":10,"color":"#f45b5b"},{"name":"Indian","y":0,"color":"#7798BF"},{"name":"Indigenous","y":0.2,"color":"#aaeeee"},{"name":"Latino","y":2.1,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":0.03,"color":"#55BF3B"},{"name":"Jewish","y":3.11,"color":"#ff0066"}],"prefix":""}	Source: US Census (Note: Racial and ethnic categories overlap so the sum will not equal 100%.)
U.S. Population (1950) Representation	-11.72	+5.53	+3.46		-4.44		{"name":"U.S. Population (1950)","series":[["White",89.5],["Mixed \/ Other",0.03],["Latino",2.1],["Indian",0],["Black",10]],"cast":[{"name":"White","y":77.78,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Latino","y":5.56,"color":"#eeaaee"},{"name":"Indian","y":5.56,"color":"#7798BF"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
U.S. Buying Power (2000) Percentage	81.25%	0.76%	6.26%		7.72%		{"name":"U.S. Buying Power (2000)","series":[{"name":"White","y":6413300000000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":276400000000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":609100000000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":40300000000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":494000000000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":60300000000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2000) Representation	-3.47	+4.8	-0.7		-2.16		{"name":"U.S. Buying Power (2000)","series":[["White",81.25],["Mixed \/ Other",0.76],["Latino",6.26],["Indian",0],["Black",7.72]],"cast":[{"name":"White","y":77.78,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Latino","y":5.56,"color":"#eeaaee"},{"name":"Indian","y":5.56,"color":"#7798BF"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
U.S. Average Individual Income (2018) Percentage	91.73%	0.02%	0.97%		6.9%		{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":10071633252712,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":26213784481,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":757617279863,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":16148742549,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":106234548000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":2335750822,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	-13.95	+5.54	+4.59		-1.34		{"name":"U.S. Average Individual Income (2018)","series":[["White",91.73],["Mixed \/ Other",0.02],["Latino",0.97],["Indian",0],["Black",6.9]],"cast":[{"name":"White","y":77.78,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Latino","y":5.56,"color":"#eeaaee"},{"name":"Indian","y":5.56,"color":"#7798BF"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
World population (1960) Percentage	24.26%	1.83%	5.41%	17.64%	8.74%		{"name":"World population (1960) ","series":[{"name":"Mixed \/ Other","y":5505891663,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":16303932915,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Indigenous","y":3319084808,"color":"#aaeeee","sliced":true,"selected":true},{"name":"White","y":73088413576,"color":"#2b908f","sliced":true,"selected":true},{"name":"Black","y":26323680328,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Asian","y":105885338709,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Arab","y":16554213546,"color":"#DF5353","sliced":true,"selected":true},{"name":"Indian","y":53158782795,"color":"#7798BF","sliced":true,"selected":true},{"name":"Jewish","y":1167943535,"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 (1960) Representation	+53.52	+3.73	+0.15	-12.08	-3.18		{"name":"World population (1960) ","series":[["White",24.26],["Mixed \/ Other",1.83],["Latino",5.41],["Indian",17.64],["Black",8.74]],"cast":[{"name":"White","y":77.78,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Latino","y":5.56,"color":"#eeaaee"},{"name":"Indian","y":5.56,"color":"#7798BF"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
World Buying Power Percentage	36.48%	1.81%	9.35%	6.94%	6.38%		{"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	+41.3	+3.75	-3.79	-1.38	-0.82		{"name":"World Buying Power","series":[["White",36.48],["Mixed \/ Other",1.81],["Latino",9.35],["Indian",6.94],["Black",6.38]],"cast":[{"name":"White","y":77.78,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"},{"name":"Latino","y":5.56,"color":"#eeaaee"},{"name":"Indian","y":5.56,"color":"#7798BF"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
Notes		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.	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.