Go Back to China

Summary: When spoiled rich girl Sasha Li blows through most of her trust fund, she is cut off by her father and forced to go back to China and work for the family toy business.

Release Date: October 01, 2020

Genres: Comedy, Drama

Director: Emily Ting

Writer: Emily Ting

Runtime: 1 h 35 min

MPAA: TV-14

Production: Unbound Feet Productions, Endcrawl.com, Fuse Media, Endcrawl.com, Fuse Media

Distributor: Encore Inflight, Gravitas Ventures

Countries: China, United States

Language: English

N/A

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67%73%

67% of the Stars & Main Cast are Female.

73% of the Stars & Main Cast are "diverse."

Asian53.33%White26.67%Black6.67%Latino6.67%Mixed / Other6.67%

N/A

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CONTENT BREAKDOWN

Methodology

Douban:

IMDb:

Methodology

Cast

Stars:

Supporting cast:

Other Cast, Production

Other cast:

Production:

Representation

Star

Supporting

Other

Production

Race	Asian	White	Mixed / Other	Latino	Black	Total	Visuals	Info
Kairos	4	3		1	1	9		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	3					3		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			2		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/
Familysearch	2					2
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	10	4	1	1	1	17
Cast Percentages	58.82%	23.53%	5.88%	5.88%	5.88%	100%	{"name":"Cast Percentages","series":[{"name":"Asian","y":58.82,"color":"#90ee7e","sliced":true,"selected":true},{"name":"White","y":23.53,"color":"#2b908f","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":5.88,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":5.88,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Black","y":5.88,"color":"#f45b5b","sliced":true,"selected":true}],"prefix":""}
U.S. Population (2020) Percentage	6%	57.84%	9.32%	18.73%	12.4%		{"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	+52.82	-34.31	-3.44	-12.85	-6.52		{"name":"U.S. Population (2020)","series":[["Asian",6],["White",57.84],["Mixed \/ Other",9.32],["Latino",18.73],["Black",12.4]],"cast":[{"name":"Asian","y":58.82,"color":"#90ee7e"},{"name":"White","y":23.53,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.88,"color":"#55BF3B"},{"name":"Latino","y":5.88,"color":"#eeaaee"},{"name":"Black","y":5.88,"color":"#f45b5b"}]}
U.S. Buying Power (2018) Percentage	6.2%	74.35%	1.38%	9.42%	7.96%		{"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":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2018) Representation	+52.62	-50.82	+4.5	-3.54	-2.08		{"name":"U.S. Buying Power (2018)","series":[["Asian",6.2],["White",74.35],["Mixed \/ Other",1.38],["Latino",9.42],["Black",7.96]],"cast":[{"name":"Asian","y":58.82,"color":"#90ee7e"},{"name":"White","y":23.53,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.88,"color":"#55BF3B"},{"name":"Latino","y":5.88,"color":"#eeaaee"},{"name":"Black","y":5.88,"color":"#f45b5b"}]}
U.S. Average Individual Income (2018) Percentage	7.52%	65.34%	7.28%	9.51%	9.43%		{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11825174998483,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1360705388565,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1706765993728,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":164296821776,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1721419354421,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":1318328353188,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	+51.3	-41.81	-1.4	-3.63	-3.55		{"name":"U.S. Average Individual Income (2018)","series":[["Asian",7.52],["White",65.34],["Mixed \/ Other",7.28],["Latino",9.51],["Black",9.43]],"cast":[{"name":"Asian","y":58.82,"color":"#90ee7e"},{"name":"White","y":23.53,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.88,"color":"#55BF3B"},{"name":"Latino","y":5.88,"color":"#eeaaee"},{"name":"Black","y":5.88,"color":"#f45b5b"}]}
World population (2019) Percentage	31.25%	14.24%	1.92%	5.62%	14.47%		{"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	+27.57	+9.29	+3.96	+0.26	-8.59		{"name":"World population (2019) ","series":[["Asian",31.25],["White",14.24],["Mixed \/ Other",1.92],["Latino",5.62],["Black",14.47]],"cast":[{"name":"Asian","y":58.82,"color":"#90ee7e"},{"name":"White","y":23.53,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.88,"color":"#55BF3B"},{"name":"Latino","y":5.88,"color":"#eeaaee"},{"name":"Black","y":5.88,"color":"#f45b5b"}]}
World Buying Power Percentage	29.46%	36.48%	1.81%	9.35%	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	+29.36	-12.95	+4.07	-3.47	-0.5		{"name":"World Buying Power","series":[["Asian",29.46],["White",36.48],["Mixed \/ Other",1.81],["Latino",9.35],["Black",6.38]],"cast":[{"name":"Asian","y":58.82,"color":"#90ee7e"},{"name":"White","y":23.53,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5.88,"color":"#55BF3B"},{"name":"Latino","y":5.88,"color":"#eeaaee"},{"name":"Black","y":5.88,"color":"#f45b5b"}]}
Notes	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.		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.

Tags / Keywords

female frontal nudity female full frontal nudity female nudity girl skinny dipping

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44% of the Stars & Main Cast are Female.

100% of the Stars & Main Cast are "diverse."

Latino91.67%Indian8.33%

N/A

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Methodology

IMDb:

Methodology

Frank and Ava (2020)

Summary: Before he was chairman of the board. He was just a man, desperate for a woman, clinging to a dream. The story of Sinatra as never told before and Ava Gardner, the woman who saved him, by breaking him. Based on true stories.

Release Date: May 14, 2020

Genres: Drama, Biography, History

Director: Michael Oblowitz

Writers: Willard Manus

, Rico Simonini

Runtime: 1 h 50 min

Production: 8th House Entertainment, All Edge Entertainment, AllEdge Entertainment

Country: United States

Language: English

Domestic: $ 18,829

Box office:

Domestic:$18.8KWorldwide:$18.8K

N/A

No Rotten Tomatoes ratings imported yet.

No Metacritic ratings imported yet.

33%11%

33% of the Stars & Main Cast are Female.

11% of the Stars & Main Cast are "diverse."

White83.33%Asian5.56%Mixed / Other5.56%Jewish5.56%

N/A

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Methodology

IMDb:

Methodology

La ville est tranquille (2000)

Summary: Marseilles' working-class struggles amidst city crisis. Fish worker's addicted daughter, bartender with secret unveiled.

Release Date: January 17, 2001

Genre: Drama

Director: Robert Guédiguian

Writers: Jean-Louis Milesi

, Robert Guédiguian

Runtime: 2 h 13 min

Production: Agat Films & Cie, Canal+, Diaphana Films

Distributor: New Yorker Films

Country: France

Language: French

Domestic: $ 66,303

Box office:

Domestic:$66.3KWorldwide:$66.3K

N/A

No Rotten Tomatoes ratings imported yet.

No Metacritic ratings imported yet.

39%13%

39% of the Stars & Main Cast are Female.

13% of the Stars & Main Cast are "diverse."

White87.5%Black12.5%

N/A

Possibly woke elements:

interracial,interracial relationship,racism

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Methodology

Douban:

IMDb:

Moviemeter:

OFDb:

Methodology

Born Winner (1976)

Summary: A young man whose passions are money, beautiful women and racing motorcycles comes up with a scheme that will allow him to combine all three, all while committing the "perfect" crime.

Genres: Drama, Crime

Director: Aldo Lado

Writers: Stefano Calanchi

, Lucio Collo

, Aldo Lado

Runtime: 1 h 37 min

Production: Marzia Cinematografica, New Gold Entertainment

Country: Italy

Language: Italian

N/A

No Rotten Tomatoes ratings imported yet.

No Metacritic ratings imported yet.

19%7%

19% of the Stars & Main Cast are Female.

7% of the Stars & Main Cast are "diverse."

White93.33%Asian6.67%

1.00

This film gets a 1.00/5 family friendly score

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CONTENT BREAKDOWN

Methodology

IMDb:

OFDb:

Methodology

Hannah Takes the Stairs (2007)

Summary: Hannah is a recent college graduate interning at a Chicago production company. She is crushing on two writers at work, Matt and Paul, who share an office and keep her entertained. Will a relationship with one of them disrupt the d...

Release Date: August 22, 2007

Genres: Comedy, Drama, Romance

Director: Joe Swanberg

Writers: Joe Swanberg

, Greta Gerwig

, Kent Osborne

Runtime: 1 h 23 min

MPAA: Not Rated

Production: Film Science

Country: United States

Language: English

Domestic: $ 22,815

International: $ 4,108

Box office:

Domestic:$22.8KInternational:$4.1KWorldwide:$26.9K

-14%

The Rotten Tomatoes audience rated this -14% lower than the critics.

59%45%

The Metacritic audience rated this -6% lower than the critics.

Metacritic Meta:

63/100

Metacritic User:

57/100

36%0%

36% of the Stars & Main Cast are Female.

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

White90.91%Jewish9.09%

N/A

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Methodology

RottenTomatoes:

59%45%

Douban:

Eiga:

IMDb:

Kinopoisk:

Metacritic:

Metacritic User:

OFDb:

Methodology

Russian Dolls (2005)

Summary: Five years after their summer together in Barcelona, Xavier, William, Wendy, Martine and Isabelle reunite.

Release Date: June 15, 2005

Genres: Comedy, Drama, Romance

Director: Cédric Klapisch

Writer: Cédric Klapisch

Runtime: 2 h 05 min

MPAA: Not Rated

Production: Lunar Films, StudioCanal, France 2 (FR2), Canal+, Ce Qui Me Meut Motion Pictures, TPS Cinéma

Distributor: StudioCanal, IFC Films

Countries: France, United Kingdom

Language: French

Movie budget: $ 12,500,000

Domestic: $ 326,095

International: $ 23,401,206

Box office:

Budget:$12.5MDomestic:$326.1KInternational:$23.4MWorldwide:$23.7M

The Rotten Tomatoes audience rated this 6% higher than the critics.

72%78%

No Metacritic ratings imported yet.

56%17%

56% of the Stars & Main Cast are Female.

17% of the Stars & Main Cast are "diverse."

White83.33%Latino5.56%Black5.56%Arab5.56%

N/A

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Methodology

RottenTomatoes:

72%78%

Douban:

IMDb:

Kinopoisk:

OFDb:

Methodology

Drowning by Numbers (1988)

Summary: Three generations of women share the same problem--marriage woes--and want to put an end to it.

Genres: Comedy, Drama

Director: Peter Greenaway

Writer: Peter Greenaway

Runtime: 1 h 58 min

MPAA: R

Production: Film Four International, Elsevier-Vendex Film Beheer, Allarts Production

Distributor: Live Home Video, Prestige, Severin Films

Countries: Netherlands, United Kingdom

Language: English

Domestic: $ 424,773

International: $ 52,266

Box office:

Domestic:$424.8KInternational:$52.3KWorldwide:$477K

The Rotten Tomatoes audience rated this 2% higher than the critics.

87%89%

No Metacritic ratings imported yet.

39%11%

39% of the Stars & Main Cast are Female.

11% of the Stars & Main Cast are "diverse."

White88.89%Black5.56%Latino5.56%

N/A

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Methodology

RottenTomatoes:

87%89%

Douban:

IMDb:

Kinopoisk:

OFDb:

Methodology

Uranus (1990)

Summary: After World War II, a small French village struggles to put the war behind as the controlling Communist Party tries to flush out Petain loyalists. The local bar owner, a simple man who likes to write poetry, who only wants to be l...

Release Date: December 12, 1990

Genres: Comedy, Drama

Director: Claude Berri

Writers: Marcel Aymé

, Claude Berri

, Arlette Langmann

Runtime: 1 h 40 min

MPAA: R

Production: DD Productions, Films A2, Investimage 2, Soficas Sofi Ano

Country: France

Language: French

Domestic: $ 342,198

Box office:

Domestic:$342.2KWorldwide:$342.2K

Adaptation/remake:

based on novel

N/A

No Rotten Tomatoes ratings imported yet.

No Metacritic ratings imported yet.

22%6%

22% of the Stars & Main Cast are Female.

6% of the Stars & Main Cast are "diverse."

White94.44%Latino5.56%

N/A

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CONTENT BREAKDOWN

Methodology

IMDb:

Kinopoisk:

Moviemeter:

OFDb:

Methodology

Hear My Song (1991)

Summary: The owner of a failing club seeks infamous Irish singer Josef Locke in order to bring business and success to his club.

Genres: Comedy, Drama, Music

Director: Peter Chelsom

Writers: Peter Chelsom

, Adrian Dunbar

Runtime: 1 h 44 min

MPAA: R

Production: British Screen Productions, Channel Four Films, Limelight Productions

Distributor: Miramax Home Entertainment, Paramount Home Entertainment

Countries: Ireland, United Kingdom

Language: English

Domestic: $ 4,313,473

Box office:

Domestic:$4.3MWorldwide:$4.3M

Adaptation/remake:

based on true story

-13%

The Rotten Tomatoes audience rated this -13% lower than the critics.

90%77%

No Metacritic ratings imported yet.

44%0%

44% of the Stars & Main Cast are Female.

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

White100%

N/A

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CONTENT BREAKDOWN

Methodology

RottenTomatoes:

90%77%

Eiga:

IMDb:

Moviemeter:

OFDb:

Methodology

Love and Human Remains (1993)

Summary: In Edmonton, Canada, a failed actor lives with a bookish woman, whom he dated before coming out as a homosexual. While they and their friends each aim to find love and sexual gratification, a serial killer stalks the city's women.

Release Date: June 23, 1995

Genres: Comedy, Drama

Director: Denys Arcand

Writer: Brad Fraser

Runtime: 1 h 40 min

MPAA: R

Production: Atlantis Films, First Choice Films, Max Films Productions, Super Ecran, Téléfilm Canada

Distributor: Sinister Cinema

Country: Canada

Language: English

Domestic: $ 542,985

Box office:

Domestic:$543KWorldwide:$543K

Adaptation/remake:

based on play

N/A

No Rotten Tomatoes ratings imported yet.

No Metacritic ratings imported yet.

39%0%

39% of the Stars & Main Cast are Female.

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

White93.75%Jewish6.25%

N/A

LGBTQ content included:

gay, homosexual, gay kiss, lesbian, gay man, bisexual, gay protagonist, bisexual woman

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Methodology

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last updated: 1970-01-01Update data

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https://www.commonsensemedia.org

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Methodology

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Global Consensus

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rating: 3.9/10

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Strong and multidimensional female characters are fine. This is mainly referring to girlboss crap, unrealistic Mary Sue content, and/or egregious scenes of manhood being disparaged.

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