Inside the Rain

Summary: Facing expulsion from college over a misunderstanding, a bipolar student indulges his misery at a strip club where he befriends a gorgeous, intelligent, outrageous woman and they hatch a madcap scheme to prove his innocence.

Release Date: March 13, 2020

Genres: Comedy, Drama, Romance

Director: Aaron Fisher

Writer: Aaron Fisher

Runtime: 1 h 30 min

MPAA: TV-MA

Production: Act 13

Country: United States

Language: English

Movie budget: $ 1,000,000

Domestic: $ 8,140

Box office:

Budget:$1MDomestic:$8.1KWorldwide:$8.1K

-19%

The Rotten Tomatoes audience rated this -19% lower than the critics.

86%67%

No Metacritic ratings imported yet.

39%40%

39% of the Stars & Main Cast are Female.

40% of the Stars & Main Cast are "diverse."

White60%Black20%Latino13.33%Asian6.67%

0.80

Commonsensemedia

Message2/5
Role model1/5
Violence3/5
Sex4/5
Language4/5
Drugs4/5

This film gets a 0.80/5 family friendly score

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CONTENT BREAKDOWN

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Stars:

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Race	White	Latino	Black	Asian	Mixed / Other	Total	Visuals	Info
Kairos	7	1	3	1		12		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	2	1		1	1	5
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/
Total	9	3	3	2	1	18
Cast Percentages	50%	16.67%	16.67%	11.11%	5.56%	100%	{"name":"Cast Percentages","series":[{"name":"White","y":50,"color":"#2b908f","sliced":true,"selected":true},{"name":"Latino","y":16.67,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Black","y":16.67,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Asian","y":11.11,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B","sliced":true,"selected":true}],"prefix":""}
U.S. Population (2020) Percentage	57.84%	18.73%	12.4%	6%	9.32%		{"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	-7.84	-2.06	+4.27	+5.11	-3.76		{"name":"U.S. Population (2020)","series":[["White",57.84],["Latino",18.73],["Black",12.4],["Asian",6],["Mixed \/ Other",9.32]],"cast":[{"name":"White","y":50,"color":"#2b908f"},{"name":"Latino","y":16.67,"color":"#eeaaee"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Asian","y":11.11,"color":"#90ee7e"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"}]}
U.S. Buying Power (2018) Percentage	74.35%	9.42%	7.96%	6.2%	1.38%		{"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":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2018) Representation	-24.35	+7.25	+8.71	+4.91	+4.18		{"name":"U.S. Buying Power (2018)","series":[["White",74.35],["Latino",9.42],["Black",7.96],["Asian",6.2],["Mixed \/ Other",1.38]],"cast":[{"name":"White","y":50,"color":"#2b908f"},{"name":"Latino","y":16.67,"color":"#eeaaee"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Asian","y":11.11,"color":"#90ee7e"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"}]}
U.S. Average Individual Income (2018) Percentage	65.34%	9.51%	9.43%	7.52%	7.28%		{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11825174998483,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1360705388565,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1706765993728,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":164296821776,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1721419354421,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":1318328353188,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	-15.34	+7.16	+7.24	+3.59	-1.72		{"name":"U.S. Average Individual Income (2018)","series":[["White",65.34],["Latino",9.51],["Black",9.43],["Asian",7.52],["Mixed \/ Other",7.28]],"cast":[{"name":"White","y":50,"color":"#2b908f"},{"name":"Latino","y":16.67,"color":"#eeaaee"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Asian","y":11.11,"color":"#90ee7e"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"}]}
World population (2019) Percentage	14.24%	5.62%	14.47%	31.25%	1.92%		{"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	+35.76	+11.05	+2.2	-20.14	+3.64		{"name":"World population (2019) ","series":[["White",14.24],["Latino",5.62],["Black",14.47],["Asian",31.25],["Mixed \/ Other",1.92]],"cast":[{"name":"White","y":50,"color":"#2b908f"},{"name":"Latino","y":16.67,"color":"#eeaaee"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Asian","y":11.11,"color":"#90ee7e"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"}]}
World Buying Power Percentage	36.48%	9.35%	6.38%	29.46%	1.81%		{"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	+13.52	+7.32	+10.29	-18.35	+3.75		{"name":"World Buying Power","series":[["White",36.48],["Latino",9.35],["Black",6.38],["Asian",29.46],["Mixed \/ Other",1.81]],"cast":[{"name":"White","y":50,"color":"#2b908f"},{"name":"Latino","y":16.67,"color":"#eeaaee"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Asian","y":11.11,"color":"#90ee7e"},{"name":"Mixed \/ Other","y":5.56,"color":"#55BF3B"}]}
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 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.

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This film gets a 0.8/5 family friendly score

MPAA Certification	No MPAA rating found yet. Add Family Friendly Rating?
IMDb Rating https://www.imdb.com/title/tt11029976/parentalguide last updated: 2024-10-26Update data
Commonsensemedia Rating https://www.commonsensemedia.org/movie-reviews/inside-the-rain last updated: 2024-10-26Update data
Message 2/5	Film is meant to create understanding of what it's like to live with bipolar disorder; shows more realistic portrayal of psychiatric ward and other psych patients than most Hollywood movies do.
Role model 1/5	Ben's mental health diagnoses include bipolar disorder, ADHD, OCD, and borderline personality disorder; he's portrayed realistically. A sex worker isn't shamed or ostracized for the way she makes money.
Violence 3/5	Main character attempts suicide, and there are references to previous attempts. A patient in a psychiatric unit has scars up and down her wrists from suicide attempts. A group of young men speaks disrespectfully to a young woman; another man intervenes (moments of yelling, threatening posturing). Police roughly handle someone they believe is trying to harm himself.
Sex 4/5	A couple of sex scenes. Bare breasts seen. A porn actress dressed in bondage gear talks dirty to her online audience. A model acts as a naked serving tray for food at a strip club; no sensitive body parts shown. Strippers dance suggestively in revealing dresses, but not naked. A sexy video is shown in which the model moves in a sultry way while wearing lingerie. Several instances of characters in underwear.
Language 4/5	Frequent profanity includes "ass," "bitch," "blow job," "cum," "hell," "p---y" (implying weakness), "s--t," "slut," and many uses of "f--k."
Drugs 4/5	Character must take several prescription drugs for chemical imbalance; he mixes them with hard liquor with no consequences. Later, he intentionally overdoses on the medications in a suicide attempt -- which has far-reaching consequences. College students smoke pot and drink alcohol, which sometimes leads to sex. Characters smoke cigarettes, drink wine.

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