How to Be a Good Wife

Summary: Paulette and her husband have been running a housekeeping school. After the sudden death of her husband, Paulette discovers that the school is on the verge of bankruptcy and has to take her responsibilities.

Release Date: March 11, 2020

Genres: Comedy, Drama

Director: Martin Provost

Writers: Martin Provost

, Séverine Werba

Runtime: 1 h 49 min

Production: Les Films du Kiosque, France 3 Cinéma, Orange Studio, Umedia, Canal+

Countries: France, Belgium

Language: French

Movie budget: $ 6,280,000

Box office:

Budget:$6.3MWorldwide:$6M

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83%0%

83% of the Stars & Main Cast are Female.

0% of the Stars & Main Cast are "diverse."

White100%

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CONTENT BREAKDOWN

Methodology

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Methodology

Cast

Stars:

Supporting cast:

Other Cast, Production

Other cast:

Production:

Representation

Star

Supporting

Other

Production

Race	White	Arab	Total	Visuals	Info
Kairos	7		7		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	4		4		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/
Familysearch	3		3
Forebears	1	1	2
Crowd	1		1		This is the crowdsourced dataset created by users like you! We greatly appreciate your cooperation in making ZR the most accurate and massive database on the internet. Sometimes the verdicts are submitted by looks alone, sometimes users attach an image and a source link. Due to this inconsistency please take the results with a grain of salt and click each actor for more info.
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	17	1	18
Cast Percentages	94.44%	5.56%	100%	{"name":"Cast Percentages","series":[{"name":"White","y":94.44,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":5.56,"color":"#DF5353","sliced":true,"selected":true}],"prefix":""}
U.S. Population (2020) Percentage	57.84%	0.54%		{"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	+36.6	+5.02		{"name":"U.S. Population (2020)","series":[["White",57.84],["Arab",0.54]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Arab","y":5.56,"color":"#DF5353"}]}
U.S. Buying Power (2018) Percentage	74.35%			{"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":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2018) Representation	+20.09			{"name":"U.S. Buying Power (2018)","series":[["White",74.35],["Arab",0]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Arab","y":5.56,"color":"#DF5353"}]}
U.S. Average Individual Income (2018) Percentage	65.34%			{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11825174998483,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1360705388565,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1706765993728,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":164296821776,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1721419354421,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":1318328353188,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	+29.1			{"name":"U.S. Average Individual Income (2018)","series":[["White",65.34],["Arab",0]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Arab","y":5.56,"color":"#DF5353"}]}
World population (2019) Percentage	14.24%	8.82%		{"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":""}	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 (2019) Representation	+80.2	-3.26		{"name":"World population (2019) ","series":[["White",14.24],["Arab",8.82]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Arab","y":5.56,"color":"#DF5353"}]}
World Buying Power Percentage	36.48%	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	+57.96	-0.82		{"name":"World Buying Power","series":[["White",36.48],["Arab",6.38]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Arab","y":5.56,"color":"#DF5353"}]}
Notes		Arab Americans are less than 1% of the US population and often check "White" or "Other" on the US Census. And the only data available for them started when the US Census added ancestry in 1980. So assume a less than 1% margin of error and overlap with the "White" and "Other" categories.

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How to Be a Good Wife Passed!

This movie passed 3 of 3 tests. It was entered by mat on 2021-04-19 06:30:05. mat said:

Film with an almost exclusively female cast. Also fails the reverse Bechdel test, since the two named men never...

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How to Be a Good Wife

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