How Copyright Makes Works Disappear (Study 1) and How Secondary Liability Rules Enable YouTube Help the Problem for Music (Study 2)

Paul J. HealdHerbert Smith Fellow & Affiliated Lecturer, Cambridge UniversityProfessor of Law, University of IllinoisProfessorial Fellow, CIPPM, Bournemouth University

Papers.ssrn.com/sol3/papers.cfm?abstract_id=2290181

Study #1: How Copyright Makes Works Disappear . . .

• Random sample of 7000 fiction books on Amazon• Only new books available from Amazon [no used

titles or titles from Amazon “affiliates”]• Gathered via a random ISBN number generator• 2317 of 7000 titles located in the Library of

Congress catalog• Date of earliest LOC edition used as proxy for

initial publication date of title [note this biases dates upward chronologically]

We might expect to see this . . .

Or this . . .

2000's

1980's

1960's

1940's

1920's

1900's

1880's

1860's

1840's

1820's

1800's0

50000

100000

150000

200000

250000

300000

Library Book Titles by Decade of Publica-tion

Harold Washington LibraryAll Chicago Branches

What Professor Landes Would Expect to See . . .

19001910

19201930

19401950

19601970

19801990

20002010

0

200

400

600

800

1000

1200

New Books Available Now

Decade of Ini-tial Publication Date of Book

18001820

18401860

18801900

19201940

19601980

20000

50

100

150

200

250

300

350

400

2317 New Editions from Amazon by Decade

Fiction & Non-Fiction Books

18001820

18401860

18801900

19201940

19601980

20000

50

100

150

200

250

300

Estimated Number Titles Available on Amazon by Decade

Fiction & Non-Fiction Books

18001820

18401860

18801900

19201940

19601980

20000

100

200

300

400

500

600

700

800

Estimated Book Titles Adjusted for Total Number of Books Published Per Decade

Fiction and Non-Fiction Books

18001820

18401860

18801900

19201940

19601980

20000.00

50.00

100.00

150.00

200.00

250.00

Estimated Amazon Titles by Type of Work

Ficton Works

Non-Fiction Works

Copyright Distortion?

2000's

1980's

1960's

1940's

1920's

1900's

1880's

1860's

1840's

1820's

1800's0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

8000000

9000000

10000000

Initial Publication Dates of New and Used Books for Sale 2012-2013

Used BooksNew Books

Abso

lute

Num

ber o

f Use

d Ti

tles a

nd F

itted

Sa

mpl

e of

New

Titl

es

x

y

z

What About Music?

• Brooks (2006) shows only 14% of famous old tunes digitized, so I Tunes or Amazon CD’s would be age-biased.• So, collected data from two movie soundtrack

samples• Top 100 grossing movies of all-time from

www.boxofficemojo.com• 134 randomly selected movies from

www.boxofficemojo.com• All from DVD’s currently on sale at Amazon

2013 At Date of Movie Release

170 160

637 647

807 Songs in Top 100 Grossing Movies

Public Domain Copyrighted

>160

(-140 PD)

(-120 PD)

(-100 PD)

(-80 PD)

(-60 PD)

(-60 ©

)

(-40 ©

)

(-20 ©

)

(-1 ©

)0

50

100

150

200

250778 Songs from Top 100 Grossing Films

Movie Release Date Minus Song Publication Date

2013 At Movie Release

73 69

814 818

887 Songs in 136 Random MoviesPublic Domain Copyrighted

Why So Many Fewer PD Songs in the Randomly Picked Movies?

• Unlikely that directors of big budget blockbusters are more price sensitive.• But Median release date of 100 highest grossing

movies is 1977 and the median release data of the 134 random movies is 2002 [Box Office Mojo skews to newer movies]• Oldest random movie was released in 1981.

But why should relatively newer movies have fewer PD songs?

• Due to copyright term extensions (e.g. 1976), newer movies are farther removed from the public domain reservoir of songs.

• HYPOTHESIS: The half of the Top Grossing films released before 1977 will rely on more PD songs than the half released after 1977.

>130 -120 -110 -100 -90 -80 -70 -60 -500

5

10

15

20

25

30

35

Age of Songs from Movie Release Date: Pre & Post-1977

Songs in Post-1977 Movie ReleasesSongs in Pre-1977 Movie Releases

0

40

80

120

PD Songs in Movies Before and After 1977

Number of Songs

Study #2: Uploading Hits on YouTube: How Notice and Takedown Rules Facilitate the Availability of Music

• Collected the Number One Songs in Brazil and France, from 1930-1960 and from US from 1930-68..• Searched for each song on YouTube and charted the first

10 uploads containing a version of the song.• Tracked 4 types: recorded songs with only a picture of

the album or CD cover or a picture of the artist; amateurs performing the song; custom videos with the song in the background; and television and movies clips.• Noted uploader identity. # of views, date of upload,

monetized or not.

Why is this Non-Monetized?

Preliminaries

• Almost all of the uploads are unauthorized. •Much outright infringement is tolerated –

remains up and not monetized.•Many uploads are monetized.• Average upload date is July ‘09 for non-

monetized uploads and September ‘09 for monetized uploads.

Not Monetized Monetized

103

272

Uploaded Number 1 US Songs 1930-67

375 Uploads

Mean Views Median Views

656,000

130,000

1,940,000

226,000

Views by Users

Not Monetized Monetized

Recorded Song

Historical TV Perf.

Historical Movie Perf.

Custom Vid

New Amateur

Perf.

66

22

72 2

18

48

168 9

Type of Upload by Percent270 Monetized Uploads 104 Unmonetized Uploads

Who can take down uploads?

• Custom videos and new amateur performances: Owner of the composition copyright.• Recorded songs: Owner of composition OR

sound recording copyright.• Television or movie clips: Owner of composition

OR video copyright.• YouTube requires proof of ownership of all

components to monetize!

Questions about U.S. Market• Does a coordination effect hamper the ability of

to monetized uploads where owners of compositions and videos must cooperate?• Do better post-1968 contracts increase the

monetization rate?• Why do composers tolerate so much

infringement in the context of television and movies clips?• How bad is the problem of lost television

episodes, specials, and newscasts?

France and Brazil in Comparison

US France Brazil0

1020304050607080

US, French, & Brazilian 1930-1960 No. 1 Songs: Percent Monetized

Percent Mone-tized

Custom Video

Am. Perf.

Record

ing

TV or Movie

0

10

20

30

40

50

60

70

Monetized Uploads by Percent

USBrazilFrance

Custom Video

Am. Perf. Recording TV or Movie

0

10

20

30

40

50

60

70

Non-Monetized Uploads by Percent

USBrazilFrance

Tentative Overall Conclusions

• Traditional book and music publishing models demonstrate how copyright stands in between works and the consuming public.• Non-owners play a very important role in

maintaining the availability of public domain and copyrighted works.• YouTube, lowers transaction costs, providing

valuable information, and facilitating both availability to consumers and revenue streams to owners.• Current secondary liability rules look efficient!