Back in January, I had a brief exchange on Twitter prompted by this news story. The gist is that A. O. Scott, film critic for The New York Times, posted a tweet about the film Inside Llewyn Davis. The film’s promoters took out a full page ad in the Times displaying the tweet (or more accurately, the last two sentences of the tweet).

The linked article’s discussion assumes that Scott “own[s] the copyright to his tweets,” but notes that by tweeting, Scott could be presumed to be granting an implied license for reuse of the tweet elsewhere.

But can you even copyright a tweet? I did some research and was unable to come up with a clear answer. There was some academic discussion of the issue, and occasional instances in which Twitter users claimed others were infringing their tweets, but I could not find a clear instance in which someone had actually registered a copyright in a tweet.

So, 7 months and $35 later, I have my answer: no, you cannot copyright a tweet.

That, at least, is what the registration specialist at the Copyright Office decided to send me in response to my attempt to register this tweet as a literary work entitled “Tweet #452?:

Monkey bar fallacy: a bad person using something makes it bad. E.g., users of monkey bars include: children, TERRORISTS #tor

Of course, the rejection of this particular tweet does not imply that no tweet can be copyrighted. Perhaps the registration specialist did not feel my tweet was valuable or creative enough, and thus did not pass the (very low) threshold of originality.

This makes me wonder whether short poems like haikus are eligible for copyright protection. Browsing the Copyright Office’s registration database, I can find a number of registered literary works labeled “haikus” that are no longer than one page. Perhaps I would have had more luck if I had instead tweeted a haiku:

Monkey bar fallacy:
A bad person using something
Makes it bad.

(For sticklers, yes, I know it’s not 5-7-5, but it is 17 syllables.)

Ultimately, I wonder if the Copyright Office applies more scrutiny to short literary works than it does to photographs. In the U.S., we work under the assumption that every photograph taken by a human being is copyrighted. But I take a lot of photos, and many of them take far less time, effort, and creativity to compose than a tweet. Here’s an example:

Other countries have found that some photographs simply aren’t creative enough to warrant copyright protection. Wikipedia has a brief summary and link to the German text of a Swiss case in which a reporter’s photograph of a man holding record books was ruled ineligible for copyright.

It would be a fun, albeit expensive, experiment to try and register a variety of liminal works: handfuls of sentences, short quines, run of the mill photographs, “sculptures” made of a few Lego pieces, etc. I would contest the office’s decision about my tweet, but I don’t want to pay $250 out of pocket to do so, and I also don’t really want to write a funding proposal to try and convince someone else to give me the money.

To wrap up this little experiment, the Copyright Office’s online registration process allows registrants to submit comments with their registrations. I submitted the following text, although I have no way of knowing whether it was ever read:

In Ashleigh Brilliant v. W.B. Productions, Inc. (Civ. No. 79-1893-MBM, S.D. Cal Oct. 22, 1979), a U.S. District Court found that Brilliant’s copyrights on three epigrams were valid and enforceable. The epigrams were 12, 15, and 10 words respectively. Each was a single sentence, lacking rhyme or meter; rather, their originality consists of their pithiness. Tweet #452’s originality is similar: using 20 words and two sentences, it exposes the logical fallacy inherent in blaming tools, using humor and topical examples to communicate the point.

Circular 34 states that “copyright law does not protect names, titles, or short phrases or expressions.” Tweet #452 is clearly not a name or title, leaving only the question of whether it is a short phrase or short expression. The Oxford English Dictionary defines a phrase as “a small group or collocation of words expressing a single notion, or entering with some degree of unity into the structure of a sentence; a common or idiomatic expression.” Expression is similarly defined as “A word, phrase, or form of speech.”

Tweet #452 cannot be classified as either a “phrase” or “expression,” since it contain two complete sentences (i.e., two subject-verb pairs). Thus, Tweet #452 does not fall within the scope of Circular 34. Even if Tweet #452 were considered a phrase or expression, phrases or expressions as such are not necessarily ineligible for copyright, since Circular 34 specifies that only “short phrases or expressions” are ineligible for copyright, thereby suggesting that longer phrases or expressions are eligible.

This post and the included image are licensed CC BY-SA 4.0, and may be shared and reposted with attribution. When reposting, please include a link back to the original story, which will contain the most up-to-date version.

In another instance of the U.S. Chamber of Commerce’s Global IP Center (GIPC) posting factually incorrect information, on June 11, the GIPC cross-posted a blog post from Plagiarism Today purporting to clarify the meanings of “5 Copyright Terms We Need to Stop Using Incorrectly.”

I ran across this post because of the following GIPC tweet (screenshot posted here in case it mysteriously disappears):

Unfortunately, the linked post gets basic facts about copyright law wrong. On fair use, it reads:

What it Means: A fair use of a work is an infringement of a work where the court has determined that the infringer is not liable due to the nature of the infringement being within the bounds of the law.

I’m honestly not sure how much more wrong one can get. 17 U.S.C. § 107 plainly states:

the fair use of a copyrighted work, including such use by reproduction in copies or phonorecords or by any other means specified by that section, for purposes such as criticism, comment, news reporting, teaching (including multiple copies for classroom use), scholarship, or research, is not an infringement of copyright.

To say a fair use is an infringement is to fundamentally misunderstand the nature of U.S. copyright law. It’s also nonsensical. By definition, an “infringement” means going beyond what is permitted by law. An “infringement being within the bounds of the law” is no infringement at all.

The author’s confusion probably stems from the fact that in lawsuits, fair use is raised as an “affirmative defense.” Many people wrongly interpret this to mean that fair use is a kind of acceptable copyright infringement. This is incorrect. Wikipedia explains it nicely:

“Affirmative defense” is simply a term of art from litigation reflecting the timing in which the defense is raised. It does not distinguish between “rights” and “defenses”, and so it does not characterize the substance of the defendant’s actions as “not a right but a defense”.

In other words, an affirmative defense is an admission that you committed the alleged acts, but that other circumstances make these acts lawful.

GIPC blog contributors might want to take an introductory copyright law class before trying to educate others on the meaning of fair use.

Reposted from To Promote the Progress? under its CC BY-SA 4.0 license.

This post is licensed CC-BY SA 3.0, and may be shared and reposted with attribution. Please include a link back to the original, which will contain the most up-to-date version.

Last year, the USPTO released a widely cited report entitled “Intellectual Property and the U.S. Economy: Industries in Focus.” This report emphasized the importance of IP to the U.S. economy, claiming “the entire U.S. economy relies on some form of IP,” and estimating that “IP-intensive industries” accounted for 40 million American jobs and 35% of the U.S. GDP in 2010.

While many pro-IP groups hailed the report as demonstrating the importance of IP to the American economy, the report was widely panned by critics who pointed out that the definition of “IP-intensive industries” was so broad as to be meaningless. Indeed, according to the report, the number one IP-intensive industry by employment in the United States was… grocery stores. Although supporters of stricter IP regulation and enforcement continue to rely on the report to justify policies relating to copyrights and patents, the vast majority of the report’s purported economic benefits were attributed to trademarks.

USPTO’s report was released in March 2012, and received a lot of attention. Just one month prior, the National Science Foundation (NSF) released the findings of a survey on business use of intellectual property. While a few sites picked up on the NSF report last year, it received far less media attention than it deserved. Why? Perhaps because it turns out that if you actually ask, the vast majority of businesses report that intellectual property is not important to them.

Infojustice.org was among the few noting that the NSF’s findings directly contradict the USPTO report. The initial NSF report, published in February 2012, reported data from 2008. However, it has recently been updated to include data from 2009 and 2010.

But wait – surely I’m making all this up. If “IP-intensive” industries account for 40 million jobs and 35% of GDP, intellectual property must be very important to businesses. What’s this “vast majority,” then?

• In 2010, 87.2% of businesses reported that trademarks were “not important” to them.
• 90.1% of businesses reported that copyrights were “not important” to them.
• 96.2% of businesses reported that patents were “not important” to them.

If you still think I’m making these numbers up (and I wouldn’t blame you if you did), head on over to the NSF’s page describing the survey, results, and methodology. Note that these results are consistent across the three years of the survey, and the survey itself is a representative sample across the country.

According to the NSF, the Business Research and Development and Innovation Survey (BRDIS) “is an annual, nationally representative sample survey of approximately 43,000 companies, including companies in manufacturing and nonmanufacturing industries. The target population for BRDIS consists of all for-profit companies that have five or more employees and that perform R&D in the United States.”

If you examine the details, the survey results begin to make more sense. Larger companies tend to report intellectual property as being more important; businesses designated as especially “R&D active” also place more importance on various kinds of intellectual property.

Nevertheless, the results of this survey (now in its third year) are striking. Even when looking at a sector where one would expect heavy reliance on intellectual property, the results do not match expectations. For example, take one of the most copyright-dependent sectors we can imagine: “R&D active” software publishing. In 2010, 51.4% of respondents in this sector said copyright was “very important”; 34.6% said it was “somewhat important”; and 13.9% said it was “not important.” That is, only about half of respondents in a purportedly heavily copyright-dependent sector describe copyright as “very important” to their business.

In my mind, there are two ways of interpreting these data: either all the survey respondents are totally uninformed about what is going on in their businesses, or formal intellectual property protection is far less important to the vast majority of U.S. businesses than some would like us to believe.

Some additional highlights:

• 61.7% of businesses manufacturing computer and electronic products report that patents are “not important” to them.
• 96.3% of businesses with less than 500 employees report that patents are “not important” to them.
• 45.6% of businesses with 25,000 or more employees report that patents are “not important” to them.
• 53.6% of businesses classified in the information sector (NAICS code 51 – i.e., a sector we’d expect to rely heavily on copyright) report that copyrights are “not important” to them.
• Overall, businesses report that trade secrets are the most important form of intellectual property protection, with 13.2% of businesses calling trade secrets “very important” or “somewhat important.” Trademarks are a close second, with copyrights and patents significantly farther behind. Trailing in last place is sui generis protection for semiconductor mask works, although that is no surprise.

Please share widely and repost with attribution. This content is licensed CC BY-SA 3.0. Comments, suggestions, and criticism are welcome. Originally posted at To Promote the Progress?

Early Monday morning, Wikileaks released a second set of documents pertaining to the ongoing Trans-Pacific Partnership negotiations. Unlike the previous leak, this one does not contain a draft text, and instead consists of a series of comments and analysis by an unidentified negotiating party (clearly not the U.S.), as well as a table reporting each negotiating party’s position on specific issues in each chapter. The documents come from the Salt Lake City round of negotiations, which took place from November 19 to November 24, 2013.

The comments are brief, but well worth reading, as they indicate a degree of frustration with the lack of progress during the Salt Lake City round, and explicitly charge the United States with intransigence (e.g., on the topic of agricultural export subsidies, the author writes “All TPP countries except the U.S. commit to eliminate them”; likewise, with respect to financial services, he/she writes “United States shows zero flexibility.”)

An additional round of negotiations was held from December 7 to December 10 in Singapore. We learned yesterday that contrary to previous expectations, the TPP will not be concluded by year’s end, and instead at least one additional meeting will be held in January 2014.

Following up on my previous post, which analyzed the leaked intellectual property chapter by using network graphs, in this post I analyze overall negotiating positions across the entire agreement, as well as in each individual chapter. This analysis is based on the leaked table reporting negotiating positions.

Visualizing Negotiating Positions

The following graphs take the approach of plotting negotiating “distances” between countries. That is, the more dissimilarity there is between two countries’ negotiating positions, the further apart the countries will appear on a graph. Distances are derived directly from the leaked position table. The centroid is given by the origin point (0,0). In most cases, both axes used the same scale, but in a few cases (which I note) they are different. Scales are not comparable between graphs. All the graphs use “jitter,” which helps avoid overlapping labels, but makes distances slightly inexact. For technical details, see the “Nuts and Bolts” section towards the end.

This first graph represents the overall negotiating position distances between countries across all available chapters. There is a striking separation between the United States and all other TPP negotiating parties. Australia comes closest to the U.S. position, although it is not any further from the centroid than Peru. Overall, this graph serves to provide a simple visual confirmation of the leaked comments and other news reporting on TPP negotiations: the U.S. position is quite distant from the consensus point of all other countries.

Since my area of interest is intellectual property, I look at the IP chapter next. The results suggest my previous analysis was relatively accurate. The U.S. position in the intellectual property chapter is again farthest from the centroid. Australia is also quite far from the centroid, but also far from the U.S. All the other parties are clustered relatively close together, although we can still see differences within this cluster: e.g., Vietnam and Brunei are quite near one another, as are Canada and Malaysia (I had noted both these connections in the previous analysis).

In the remainder of this section, I consider each leaked chapter in alphabetical order.

The competition/state-owned enterprises graph tells a very different story than the previous two graphs. Here we immediately see two clusters on either side of the centroid: a United States/Canada/Australia/New Zealand/Mexico cluster, and a Japan/New Zealand/Singapore/Brunei/Chile cluster. Peru, Vietnam, and Malaysia fall in the middle. Note that the relative level of disagreement when compared to other chapters is low, since the data source reports positions only on a single proposal (sub-national coverage).

In the customs chapter, we see agreement amongst all parties except Japan (who has a “reserved position”) and the United States (who is the only party accepting the proposal). Again, the relative level of disagreement when compared to other chapters is low, since the data source reports positions only on a single proposal (a de minimis exception of $200).

The e-commerce chapter also provides a very different picture. There is a clear United States/Japan/Mexico cluster, which Peru also joins. Canada is nearby, but Australia is not. Brunei and Vietnam, normally close pairs, are quite far apart in this chapter.

The environment chapter also shows a distant United States position. Canada, Australia, Japan, Mexico, and Brunei cluster together quite close to the centroid, while Peru, Chile, Vietnam and Malaysia (all lower-income and middle-income countries) appear on the other periphery.

In government procurement, Mexico and Malaysia are the outliers. Both have rejected the proposal for sub-national coverage of this chapter. Relative distances are still small, given that there are only two proposals shown in the source table.

In the investment chapter, the United States appears again as the country furthest from the centroid. Japan is also relatively distant. Australia/Canada/Mexico cluster together, as do Brunei/New Zealand/Peru/Malaysia/Chile. One of the biggest debates in this chapter surrounds so-called investor-state dispute settlement, which would permit foreign firms to sue governments over alleged trade agreement violations. This type of provision is what has permitted tobacco company Philip Morris to sue the Australian government over its plain packaging legislation.

On labor issues, Australia and the United States cluster together far from the centroid. Mexico is also quite distant. Malaysia and Canada form a pair, but closer to the centroid. Mexico’s peripheral position is due to its rejection of the proposal on forced labor. The other two proposals concern sub-national coverage and dispute settlement.

The legal chapter includes a variety of topics such as the medicines “transparency” annex (i.e., the U.S. taking aim at foreign drug price controls), provisions exempting tobacco regulations from challenge, the “cultural exception” (bonjour Quebec!), and issues concerning when the agreement will enter into force, inter alia. Interestingly, we have almost a circle of positions around the centroid, with the exception of the United States, which is again farthest from the centroid.

The market access chapter is what most people typically think of when discussing trade agreements. Here, we see a wide variety of positions, representing significant disagreement. However, yet again, the United States appears farthest from the centroid. As noted above, the U.S. is the lone holdout on the proposal to eliminate agricultural subsidies. A recent Washington Post article on the U.S. sugar industry suggests that such subsidies aren’t going anywhere. I suppose that’s why the TPP is called a “partnership agreement”, rather than a “free trade agreement.”

Rules of origin are rules defining where a product is deemed to come from. Given that anything other than the simplest products will incorporate materials or parts from multiple countries, such rules are critically important in determining what products benefit from tariff reductions. We can see significant disagreement between most parties, with the United States position yet again farthest from the centroid.

With respect to trade in services, the United States and Canadian positions are identical, but farthest from the centroid. Peru and Chile are also peripheral, while all other parties cluster together near the centroid. The U.S. and Canadian positions are defined by their rejection of the “necessity test” proposal. Necessity tests require domestic regulation of services to be limited to only what is “necessary” to achieve a party’s policy objectives. Peru’s position is defined by its rejection of the open skies (air travel regulation) proposal.

SPS refers to sanitary and phytosanitary measures, which deal with food safety and plant and animal health regulations. If you’re wondering what this has to do with free trade, think of Japan or the European Union banning imports of U.S. beef: such bans may be motivated by legitimate health and safety concerns, but they may also simply provide a convenient cover for protectionism. The graph shows a significant amount of disagreement amongst most parties. In this chapter, the U.S. remains on the periphery, as does Japan, although there is no major consensus cluster amongst the other parties.

TBT stands for technical barriers to trade. Such provisions in trade agreements are designed to ensure that regulations, standards, and testing or certification requirements do not unduly burden free trade. Australia and the United States are clustered near one another, but this time it is a Peru/Chile cluster that is farthest from the centroid. All the Asian members plus New Zealand also form a cluster.

These graphs use ISO standard 2 letter country codes, but for reference, here is a legend:

Without access to the text, it’s sometimes difficult to know exactly what the various proposals mean. However, what we do know is that in the majority of chapters for which we have data, the United States appears quite far from the centroid position, and often by itself. This isn’t really news, but I think it’s interesting to systematically consider the distances between negotiating positions, and to note that the distances and clusters vary significantly by chapter and issue.

As for what it means, I think it’s fair to conclude that the TPP – unlike something like ACTA – is by no means an agreement amongst “like-minded countries.” Now, contention and disagreement isn’t always bad; on the contrary, it’s part and parcel of any negotiation. But one has to wonder about which countries are going to end up shifting positions, and in what direction, in order to make consensus and a final text possible. I suspect it won’t be the United States offering the compromises.

There are important issues at stake in the TPP negotiations, affecting access to medicines, national health policies, and national sovereignty inter alia. Yet the negotiating parties are being pushed to come to an agreement within the next two months. I won’t delve into any more detail here about the substantive issues, other than to recommend this Guardian guide to the most contentious issues in the TPP negotiations.

Nuts and Bolts

The approach I use here is called multidimensional scaling (MDS) which visualizes similarity and differences between cases as distances in N-dimensional space. I have to give a hat tip to Zhou Fang, who suggested this approach to me.

The leaked table of negotiating positions lends itself perfectly to MDS. In fact, the hardest part was probably retyping the scanned Wikileaks document. I coded an “accepted” position as 1, a rejected” position as a 0, and a “reserved position” as 0.5. Note that coding is somewhat arbitrary; e.g., I could have chosen 1, -1, and 0 instead. Different coding will affect the nominal distances, but not the relative distances (unless the coding employed unequal intervals).

The dist function creates a distance matrix. The MASS library provides the isoMDS function. isoMDS chokes when cases are identical (zero distance), so I had to add a nominal amount of distance between otherwise identical negotiating positions. Plotting is done with ggplot2, which makes adding jitter very easy. I adjust jitter on a case-by-case basis in order to avoid misleading distortions in the graphs. Most of the graphs use identical X and Y axes, but in a few cases the Y axis would have been highly compressed, so I expand it to make visual differentiation possible. Note carefully the scale changes between graphs.

Data and code available upon request. I’m currently in South Africa, so between the time difference and sporadic access to the Internet, I might not get back to you quickly, but I will do so eventually.