Big Men

Summary: The film's central story follows a small group of American explorers at Dallas-based oil company Kosmos Energy. Between 2007 and 2011, with unprecedented, independent access, Big Men's two-person crew filmed inside the oil company...

Release Date: March 14, 2014

Genre: Documentary

Director: Rachel Boynton

Writer: Rachel Boynton

Runtime: 1 h 39 min

MPAA: Not Rated

Production: Boynton Films Production, Sundial Pictures, BBC Storyville, Impact Partners

Distributor: Abramorama

Countries: United Kingdom, Denmark, United States

Language: English

Domestic: $ 56,286

Box office:

Domestic:$56.3KWorldwide:$56.3K

-23%

The Rotten Tomatoes audience rated this -23% lower than the critics.

100%77%

No Metacritic ratings imported yet.

N/A0%

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

N/A

Possibly woke elements:

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CONTENT BREAKDOWN

Methodology

RottenTomatoes:

100%77%

IMDb:

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"}]}
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Big Men

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