Airport '77

Summary: Art thieves hijack a 747, hit fog and crash into the ocean, trapping them and the passengers under one hundred feet of water.

Release Date: March 25, 1977

Genres: Action, Drama, Thriller

Director: Jerry Jameson

Writers: Arthur Hailey

, Michael Scheff

, David Spector

Runtime: 1 h 54 min

MPAA: PG

Production: Universal Pictures

Distributor: DiscoVision, National Broadcasting Company (NBC), Image Entertainment, GoodTimes Home Video, Universal Pictures Home Entertainment (UPHE), MCA/Universal Home Video

Country: United States

Language: English

Movie budget: $ 6,000,000

Budget:$6M

Possible lazy cash grab:

sequel, third part

Adaptation/remake:

based on novel

Possible Big Business:

Production:

Universal Pictures

-1%

The Rotten Tomatoes audience rated this -1% lower than the critics.

33%32%

The average Metacritic score is 36%.

Metacritic Meta:

36/100

44%11%

44% of the Stars & Main Cast are Female.

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

White83.33%Black11.11%Jewish5.56%

N/A

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CONTENT BREAKDOWN

Methodology

RottenTomatoes:

33%32%

Douban:

Eiga:

IMDb:

Kinopoisk:

Metacritic:

Moviemeter:

OFDb:

Methodology

Cast

Stars:

Supporting cast:

Other Cast, Production

Other cast:

Production:

Representation

Star

Supporting

Other

Production

Race	White	Black	Total	Visuals	Info
Kairos	10	1	11		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		3
Ethnic	2		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/
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/
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":"Black","y":5.56,"color":"#f45b5b","sliced":true,"selected":true}],"prefix":""}
U.S. Population (2010) Percentage	63.7%	12.6%		{"name":"U.S. Population (2010)","series":[{"name":"White","y":63.7,"color":"#2b908f"},{"name":"Arab","y":0.55,"color":"#DF5353"},{"name":"Asian","y":5.61,"color":"#90ee7e"},{"name":"Black","y":12.6,"color":"#f45b5b"},{"name":"Indian","y":0.92,"color":"#7798BF"},{"name":"Indigenous","y":0.9,"color":"#aaeeee"},{"name":"Latino","y":16.3,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":4.56,"color":"#55BF3B"},{"name":"Jewish","y":1.71,"color":"#ff0066"}],"prefix":""}	Source: US Census (Note: Racial and ethnic categories overlap so the sum will not equal 100%.)
U.S. Population (2010) Representation	+30.74	-7.04		{"name":"U.S. Population (2010)","series":[["White",63.7],["Black",12.6]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
U.S. Buying Power (2010) Percentage	77.06%	7.85%		{"name":"U.S. Buying Power (2010)","series":[{"name":"White","y":9431400000000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":603500000000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":961200000000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":82500000000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1018000000000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":143100000000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2010) Representation	+17.38	-2.29		{"name":"U.S. Buying Power (2010)","series":[["White",77.06],["Black",7.85]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
U.S. Average Individual Income (2018) Percentage	71.15%	9.47%		{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11951648546571,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1167575046537,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1591592669815,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":121160969070,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1374819228748,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":591945348131,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	+23.29	-3.91		{"name":"U.S. Average Individual Income (2018)","series":[["White",71.15],["Black",9.47]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
World population (2007) Percentage	15.53%	12.37%		{"name":"World population (2007) ","series":[{"name":"Mixed \/ Other","y":12338721324,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":38122017455,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Indigenous","y":9214330072,"color":"#aaeeee","sliced":true,"selected":true},{"name":"White","y":103255750927,"color":"#2b908f","sliced":true,"selected":true},{"name":"Black","y":82249533677,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Asian","y":220324384465,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Arab","y":53380310758,"color":"#DF5353","sliced":true,"selected":true},{"name":"Indian","y":143813838260,"color":"#7798BF","sliced":true,"selected":true},{"name":"Jewish","y":2242754357,"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 (2007) Representation	+78.91	-6.81		{"name":"World population (2007) ","series":[["White",15.53],["Black",12.37]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
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],["Black",6.38]],"cast":[{"name":"White","y":94.44,"color":"#2b908f"},{"name":"Black","y":5.56,"color":"#f45b5b"}]}
Notes

Tags / Keywords

1970s admiral aerial camera shot air air mask air pressure aircraft aircraft carrier aircraft cockpit airliner airplane airplane accident airplane crash airplane hijack airplane hijacking airport airport personnel alarm anchor art art collector art thief attempted robbery autopilot aviation badge balloon bar bartender based on novel beach bermuda triangle binoculars blackmail blind man blindness blockbuster blood boat boeing boeing 747 boyfriend girlfriend relationship bullhorn buoy bus businessman camera captain card game chart child in jeopardy claustrophobia cloud co pilot collector communication compressor concussion conspiracy control tower corpse critic crushed to death crying cult favorite danger death diagram disaster disaster action disaster film disguise diver diving suit doctor drowning drunkenness dulles international airport engineer englishman englishwoman entertainer entertainment escape evacuation explosion fake mustache father daughter relationship fear fire flashlight flight flight attendant flight deck flood flooding fog frogman gas gas cylinder gas mask grand hotel format grandfather grandfather grandson relationship grandson grief handgun heist helicopter hijack hijacker hijacking husband wife relationship hysteria industry island jumbo jet knife knocked out knocked unconscious lack of oxygen leak life jacket lifesaver little boy little girl locker locker room loss luxury male protagonist mansion map marital problems millionaire mother daughter relationship mother son relationship murder museum musician naval officer navy near death experience nerve gas ocean oil platform oil rig one day timespan oxygen tank painting palm beach florida palm tree panic paranoia passenger philanthropist photographer pianist piano playing pilot pistol pistol whipped plane playing cards poetic justice poker press private jet psychotronic film punched in the face race against time radar raft reference to pierre auguste renoir repeat sequel reporter rescue robbery runway sabotage scream scuba diver sea search search and rescue security security guard sequel ship ship captain shock singer singing sinking sleeping gas slut spiral staircase stewardess suit and tie sunglasses surprise ending survival suspense swimming tears terminal thief third part tied up timeframe 1970s tourniquet tracking device transportation u.s. navy unconscious underwater scene uniform veterinarian washington d.c.washroom watching a movie water wealth widow wig

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Airport '77

Stars:

Supporting cast:

Other cast:

Production:

Parental Guide: +add

IMDb Rating

Commonsensemedia Rating

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