miscellaneous factZ – The online home of Rufus Pollock

This follows up my previous post. Here we are going to calculation public domain numbers based directly on authorial birth/death date information rather than on guesstimated weightings. We’re going to focus on the Cambridge University Library (CUL) data we used previously.

Table 1: PD Relevant Information Availability

Table 1 presents a summary of how much relevant information is available for items (books) of particular vintages in the CUL catalogue — we only show data from 1870 to 1950 on the presumption that (almost) all pre-1870 publications are PD (their authors would have had to live for more than 70 years post-publication for this not to be the case) and almost all publications post 1950 are in copyright today (their authors would have to have died before 1940 for this not to be the case).

As the table shows, at best only just over 40% of items have a recorded authorial death date and extending to include birth dates only raises this proportion to, at best, the mid mid-to-low fifties. Taking account of items which lack any associated author, raises these figures somewhat further to around 60%, though we should note that the reason for the lack of an associated author is not clear — is it because they are genuinely anonymous or simply because the information has not been recorded? Thus, even for the earliest items listed a large proportion of items (50% or more) lack the necessary information for direct computation of public domain status.

At the same time, we can take some heart, and some interesting facts, from this table. First, a reasonable proportion, amounting to many thousands of items, did have associated death dates. Second, at least for older items, the majority of those with any date had a death date (95% for 1870-1880 and still at over 70% for 1920-1930). Third, and this is a more general observation, proportions were surprisingly constant over time. For example, the proportion of ‘anonymous’ items lies in a narrow band between 10% and 13% for the entire periods. Similarly the proportion of items with any date information ranged only from 45% to 56%. At the same time, and reassuringly, though the proportion with death dates is relatively constant for the oldest periods, in the more recent ones it falls substantially; as one would expect given that some of the authors from those more recent eras are still alive.

Table 2: PD Status by Decade. ‘?’ indicates items where PD status could not be computed. Prop(ortion) 1 equals total PD divided by total for which status could be computed (sum of total PD and Not PD). Prop(ortion) 2 equals total PD divided by number of items for which any author date was known (’Any Date’ in previous table).

Table 2 reports the results of direct computation of PD status based on the information available. Note that, in doing these computations, we have augmented the basic life plus 70 rule with the additional assumptions that a) all items published in 1870 or before are PD b) no author is older than 100 (so if a birth date is more 170 years ago the item is PD) c) every author lives at least until 30 (so that any work published by an author born less than a 100 years ago is automatically not PD).

As is to be expected, for the majority of the periods, the availability of PD status (either PD or Not PD) closely tracks the availability of death date information — the total for which PD status can be determined (the sum of PD and Not PD) almost exactly equals the total for which death date information is available. It is only in the last period 1940-1950 that the birth date appears to make any contribution. More interesting, is how the number PD and Not PD vary over time, especially relative to each other (and as a proportion of the records for which any date is available).

These two proportions/ratios are recorded in the last two columns which record, respectively: 1) the PD total relative to the number of items for which any status could be computed (i.e. the sum of PD and Not PD) 2) the PD total relative to the total number of items for which any date information is available. These ratios change dramatically over the periods shown: starting in the 1870-1880 period in the high 90%s by the 1940s they are down to 20% or below.

Table 3: Suggested PD Proportions

The key question for us is how to extrapolate these PD proportions to the full set of records — i.e. from the set of records for which there is the necessary birth/death date information to that where there is not. The simplest, and most obvious, approach is to assume that the proportions are identical and therefore that the PD proportions calculated on the partial dataset apply to the whole. However, there are some obvious deficiencies in this approach.

In particular, our ability to compute a PD status is largely linked to the existence of a death date and it is likely that the presence of this information is itself correlated with authorial age — after all a death date can only exist once that person has died! This correlation, and the bias it gives rise to, is probably small in the early periods — the authors of any pre 1930 work are almost certainly no longer alive today. However, for the later periods, the bias may be more substantial — it is in these last two periods (1930-1940 and 1940-1950) that there is a significant reduction in the number of records with a death date and (relatedly) a significant increase in the number of records for whom the PD status is unknown.

Thus, in converting the partial PD proportions to full PD proportions it seems sensible to revise down somewhat the partial figures with the revision being greater in later periods. Moreover, we have a lower bound for any downwards revision provided by the total PD as a proportion of all records — which even in the 1940-1950 period stood at 6%. In light of these considerations Table 3 gives fairly conservative figures for PD proportions that when estimating PD size based on publication dates. Interestingly, even with out conservative assumptions, these proportions are rather higher than those used in our previous analysis.

In doing research for the EU Public Domain project (as here and here) we are often handling large datasets, for example one national library’s list of pre-1960 books stretched to over 4 million items. In such a situation, an algorithm’s speed (and space) can really matter. To illustrate, consider our ‘loading’ algorithm — i.e. the algorithm to load MARC records into the DB, which had the following steps:

1. Do a simple load: i.e. for each catalogue entry create a new Item and new Persons for any authors listed
2. “Consolidate” all the duplicate Persons, i.e. a Person who is really the same but for whom we create duplicate DB entries in part 1 (we can do this because MARC cataloguers try to uniquely identify authors based on name + birth date + death date).
3. [Not discussed here] Consolidate “items” to “works” (associate multiple items (i.e. distinct catalogue entries) of, say, a Christmas Carol, to a single “work”)

The first part of this worked great: on a 1 million record load we averaged between 8s and 25s (depending on hardware, DB backend etc) per thousand records with speed fairly constant throughout (so that’s between 2.5 and 7.5h to load the whole lot). Unfortunately, at the consolidate stage we ran into problems: for a 1 million item DB there were several 100 thousand consolidations and we were averaging only 900s per 1000 consolidations! (This also scaled significantly with DB size: a 35k records DB averaged 55s per 1000). This would mean a full run would require several days! Even worse, because of the form of the algorithm (all the consolidation for a given person were done as a batch) we ran into memory issues on big datasets with some machines.

To address this we switched to performing “consolidation” on load, i.e. when creating each Item for a catalogue entry we’d search for existing authors who matched the information we had on that record. Unfortunately this had a huge impact on the load: time grew superlinearly and had already reached 300s per 1000 records at the 100k mark having started at 40 — Figure 1 plots this relationship. By extrapolation, 1M records would take 100 hours plus — almost a week!

At this point we went back to the original approach and tried optimizing the consolidation, first by switching to pure sql and then by adding some indexes on join tables (I’d always thought that foreign keys were auto indexed but it turned out not to be the case!). The first of these changes solved the memory issues, while the second resolved the speed problems providing a speedup of more than 30x (30s per 1000 rather 900s) and reduced the processing time from several days to a few hours.

Many more examples of this kind of issue could be provided. However, this one already serves to illustrate the two main points:

• With large datasets speed really matters
• Even with optimization algorithms can take a substantial time to run

Both of these have a significant impact on the speed, and form, of the development process. First, because one has to spend time optimizing and profiling — which like all experimentation is time-consuming. Second because longer run-times directly impact the rate at which results are obtained and development can proceed — often bugs or improvements only become obvious once one has run on a large dataset, plus any change to an algorithm that alters output requires that it be rerun.

Figure 1: Load time when doing consolidation on load

This post continues the work begun in this earlier post on “Estimating Information Production and the Size of the Public Domain”. Update: 2009-07-17 there is now a follow-up post.

Having already obtained estimates of the number of items (publications) produced each year based on library catalogue data our next step is to convert this into an estimate of the “size” of the public domain. (NB: as already discussed, “size” could mean several different things. Here, at least to start with, we’re going to take the simplest and crudest approach and equate size with number of publications/items.)

The natural, and most obvious, approach here is to go through our 1 million+ items and compute their public domain status (as discussed in this earlier post). Unfortunately, as detailed there, this is problematic because we often have insufficient information in library catalogues with which to compute PD status with certainty — in particular, author death dates are frequently absent. Thus, it will be necessary to fall back on some approximate method.

For example, we can use base PD status on simple publication dates: if a book was published, say, 140 years ago it is very likely it is in the public domain — for it to be in copyright its author must have lived more than 70 years after the book came out (remember copyright lasts for life plus 70 years in the EU)! Conversely, any publication less than 70 years old is almost certainly not in the public domain. For periods in between we can assume some proportion of publications are PD starting close to zero for more recent items and rising towards one for older ones. A calculation along those lines is provided in the following table:

Number of UK Public Domain Publications (Based on Cambridge University Library Catalogue Data)

So, based on the assumptions regarding PD proportions given in the table, there are somewhat over 600 thousand PD books according to the holdings of Cambridge University Library (of which just over half, approx 390k are from before 1870). The British Library dataset is approx 4x as big as Cambridge University Library and the numbers scale up roughly proportionately giving a total of over 2.4 million items.

Of course this is a fairly crude approach based purely on publication date and it be improved in a variety of ways, most notably by using the authorial birth date information which is usually present in catalogue data (we can also use death date information where present). This will be the subject of the next post. (2009-07-17 the post is up here).

Here we’re going to look at using library catalogue data as a source for estimating information production (over time) and the size of the public domain.

Library Catalogues

Cultural institutions, primarily libraries, have long compiled records of the material they hold in the form of catalogues. Furthermore, most countries have had one or more libraries (usually the national library) whose task included an archival component and, hence, whose collections should be relatively comprehensive, at least as regards published material.

The catalogues of those libraries then provide an invaluable resource for charting, in the form of publications, levels of information production over time (subject, of course, to the obvious caveats about coverage and the relationship of general “information production” to publications).

Furthermore, library catalogue entries record (almost) the right sort of information for computing public domain status, in particular a given record usually has a) a publication date b) unambiguously identified author(s) with birth date(s) (though unfortunately not death date). Thus, we can also use this catalogue data to estimate the size of the public domain — size being equated here to the total number of items currently in the public domain.

Results

To illustrate, here are some results based on the catalogue of Cambridge University Library which is one of the UK’s “copyright libraries” (i.e. they have a right to obtain, though not an obligation to hold, one copy of every book published in the UK). This first plot shows the numbers of publications per year (as determined by their publication date) up until 1960 (when the dataset ends) based on the publication date recorded in the catalogue.

A major concern when basing an analysis on these kinds of trends is is that fluctuations over time derive not from changes in underlying production and publication rates but changes in acquisition policies of the library concerned. To check for this, we present a second plot which shows the same information but derived from the British Library’s catalogue. Reassuringly, though there are differences, the basic patterns look remarkably similar.

Number of items (books etc) Per Year in the Cambridge University Library Catalogue (1600-1960).

Number of items (books etc) Per Year in the British Library Catalogue (1600-1960).

What do we learn from these graphs?

• In total there were over a million “Items” in this dataset (and parsing, cleaning, loading and analyzing this data took on the order of days — while the preparation work to develop and perfect these algorithms took weeks if not months)
• The main trend is a fairly consistent, and approximately exponential, increase in the number of publications (items) per year. At the start of our time period in 1600 we have around 400 items a year in the catalogue while by 1960 the number is over 16000.
• This is a forty-fold increase and corresponds to an annual growth rate of approx 0.8%. Assuming “growth” began only around the time of the industrial revolution (~ 1750) when output was around 1000 (10-year moving average) gives a fairly similar growth rate of around 0.89%.
• There are some fairly noticeable fluctuations around this basic trend:
  1. There appears to be a burst in publications in the decade or decade and a half before 1800. One can conjecture several, more or less intriguing, reasons for this: the cultural impact of the French revolution (esp. on radicalism), the effect of loosening copyright laws after Donaldson v. Beckett, etc. However, without substantial additional work, for example to examine the content of the publications in that period these must remain little more than conjectures.
  2. The two world wars appear dramatically in our dataset as sharp dips: the pre-1914 level of around 7k+ falls by over a third during the war to around 4.5k and then rises rapidly again to reach, and pass, 7k per year in the early 20s. Similarly, the late 1930s level of around 9.5k per year drops sharply upon the outbreak of war reaching a low of 5350 in 1942 (a drop of 45%), and then rebounding rapidly at the war’s end: from 5.9k in 1945 to 8k in 1946, 9k in 1947 and 11k in 1948!

To do next (but in separate entries — this post is already rather long!):

• Estimates for the the size of the public domain: how many of those catalogue items are in the public domain
• Distinguishing Publications (”Items”) from “Works” — i.e. production of new material versus the reissuance of old (see previous post for more on this).

Colophon: Background to this Research

I’m working on a EU funded project on the Public Domain in Europe, with particular focus on the size and value of the public domain. This involves getting large datasets about cultural material and trying to answer questions like: How many of these items are in the public domain? What’s the difference in price and availability of public domain versus non public domain items?

I’ve also been involved for several years in Public Domain Works, a project to create a database of works which were in the public domain.

Colophon: Data and Code

All the code used in parsing, loading and analysis is open and available from the Public Domain Works mercurial repository. Unfortunately, the library catalogue data is not: library catalogue data, at least in the UK, appears to be largely proprietary and the raw data kindly made available to us for the purposes of this research by the British Library and Cambridge University Library was provided only on a strictly confidential basis.

In my original post on Visualizing Technology Flows from Patent Data I just presented static information — flows for a single year. As I said there:

The next step is to watch how these flows, and the relationships implied by them, have evolved over time. We can do this by plotting the same graph say, every 3 years, from 1975 up until the present.

At the time I had already coded up, and computed, snapshots for each year. However, considerations of space, as well as a desire to find a way to display the information in a ‘nice’ (animated) form, warranted a separate entry. After what, as usual, has turned out to be a rather longer delay than intended, I’ve finally got round to having a first stab at this using simple animated gifs:

Animated Citation Flows 1975-1994 (1994 base year) (click through for full-size ~ 2MB). Click here to rerun the animation.

Here I’ve fixed the layout of the nodes based on the final year (1994) flows. I’ve also done quite a lot of tedious playing around (if only one had stylesheets!) with edge and node sizes to try and improve the look and they are still far from perfect (NB: this means edge/node sizes differ slightly from the images in the original post). As before:

• Size of nodes indicates total citation flows from that area in that year
• Yellow portion is citations back into that subcategory while black represents portion that is into other subcategories (comparison by area).
• Direction of flow is indicated by an arrow head (a rectangular block) with size of flow measured by width of edge and size of head.

Note that we are displaying year values not cumulative values — so, for example, links between nodes may get smaller or even disappear from one year to the next. What jumps out from this?

• The substantial increase in flows over time (most obviously seen in the size of the nodes).
• (At least based on examination by eye) no great change in the balance of these flows between cites outside and cites within a category (relative sizes of black and yellow in nodes).
• Growth has varied substantially across areas (largely, I would hazard, in line with the no. of patents in that area). In particular, the “Computer/Electronics” cluster (top-right) has grown substantially faster than the “Chemicals” sector at centre-left. Individual categories showing especially marked growth include: Biotechnology, Computer Hardware and Software, Communications, Information Storage, and Drugs.
• It also looks like some areas have grown more strongly linked and “clustered” over time (e.g. Computer/Electronics, and Drugs to Organic Compounds) though it is hard to tell from this visualization (pointing to the need for more formal techniques …).
• Something which is very clear from the visualization is that there is significant year-to-year variation with clear drops in flows in some cases year-on-year

I also computed another version where the network layout is based on that year’s flows — rather than with a fixed layout based on a given base year.

Unfortunately, this looks too “busy”, particularly as the sensitivity of the network layout algorithm (networkx.graphviz_layout) means that categories move around a lot. (To save on space — the files are big — I haven’t posted this up but if anyone is interested let me know and I’ll upload it).

One solution to this would be to move to rendering cumulative, rather than per-year, flows. This might also improve the base-year case: even there, it might be more natural, at least from a visual point of view, to display changes in flows over time via their impacts on “stocks” rather than displaying the “flows” themselves.

So, next steps:

• Plot cumulative flows
• Write up a more formal analysis based on e.g. PCA. I’ve already done PCAs on individual years and an animation might be interesting.
• Do animations right: the proper way to do this with would be with a proper “slider” widget and stop/start control. It looks like this should be pretty easy in javascript using e.g. jquery but it doesn’t look to be trivial — if it is please let me know how! (BTW: I know I could use Flash but it’s proprietary …).

I’m posting up an essay on “Discounting and Self-Control” (pdf). The essay, which I haven’t really touched for over a year, is still in its early stages but having lacked the time to do much on it over the last year, and going on the motto of “release early, release often”, I’m posting it up as a form of alpha version.

… then must you speak
Of one that loved not wisely, but too well;
Of one not easily jealous, but, being wrought,
Perplex’d in the extreme; of one whose hand,
Like the base Judean, threw a pearl away
Richer than all his tribe; …

– Othello, The Moor of Venice

Abstract

An agent’s intertemporal choices depend on a variety of factors, most prominently, their valuation of future payoffs as encapsulated in a discount function. However, it is also clear that factors such as self-control may also play an important role, and given the similarity of impact, a confouding one. We explore the literature on this issue as well as examining what occurs when those with higher time-preference (whether arising from discounting or self-control) also enjoy their consumption more.

Introduction

The exercise of will, especially in the form of self-control, has long been recognized as central to human existence, experience, and morality. Over the last few decades there has been increasing interest in the issue from a scientific perspective. At the same time, it has also long been appreciated that humans (and other animals) make trade-offs between the present and the future — as well as between different points in the future, and that events taking place closer to the present are given greater weight than those which are more distant. Traditionally, at least in economics, this type of behaviour has been subsumed under the heading of discounting.

Both of these factors, self-control and discounting, affect behaviour, and choices, in relation to outcomes which do not (all) take place in the present. However they are distinct. Specifically, consider a very simple case of two outcomes A and B where B occurs after A (for example, A might be one ice cream today and B an ice cream and a doughnut tomorrow). Self-control issues arise where one prefers B over A but is unable to execute on this preference and therefore actually takes (’chooses’) A. By contrast, in the discounting case A is actually preferred over B and therefore is chosen (freely) by the decision maker.

It would seem important to keep these two aspects of decision making clearly separated. While lack of ’self-control’ is usually seen as disadvantageous and a reason for adopting various ‘commitment strategies’ — for example, by opting to remove various items from the choice set (having no cigarettes in the house) — the simple preference for the present over the future incorporated in the discounting model would seem to generate no such difficulties.

However, empirically it may prove rather difficult to do so. As shown by the simple example above the same observed ‘choice’ for A (one ice cream today) over B (ice cream plus doughnut tomorrow) can be the result of two very different processes. Thus if we only observe choices, and not the underlying preferences and/or the process by which the choice is arrived at, it may be impossible to distinguish the two.

It is perhaps for this reason that these distinct aspects are sometimes conflated. Consider, for example, Mischel et al 1989 which is entitled “Delay of Gratification in Children” and summarizes much of Mischel of pioneering work on this area. Mischel’s approach is clearly more oriented along the self-control aspect, and this is borne out in the types of experiments conducted (more on this below). Nevertheless they state (p.934) “The obtained concurrent associations [between treatments and delay] are extensive, indicating that such preferences reflect a meaningful dimension of individual differences, and point to some of the many determinants and correlates of decisions to delay (18).” Here the orientation towards self-control has become a general “decision to delay” and this is borne out by the associated footnote (18) which references related literature in other disciplines and is worth quoting in its entirety:

[... see full essay for more]

Patricia Akester, a colleague of mine in the Centre for Intellectual Property and Information Law has just published the results of her recent research in the form of a 208 page report entitled Technological accommodation of conflicts between freedom of expression and DRM: the first empirical assessment.

There has been a lot of debate as to whether DRM/TPM can be used to go ‘beyond copyright’ and restrict legitimate uses of copyrighted material but little empirical work. Patricia’s work is therefore very valuable in providing the first systematic empirical data that we can use to assess what is going on. Here I’ll let her conclusions speak for herself but I strongly encourage readers to take a look at the study itself via the above link:

[From p. 99-100] This project looked at the impact of DRM on the ability of users to take advantage of certain exceptions to copyright. Based on a series of interviews with key organisations and individuals, involved in the use of copyright material and the development and deployment of DRM, this study examined how these issues are working out in practice. While the nightmarish vision of digital lock up has not materialised, this survey concluded, nevertheless , that significant problems do exist, and others can readily be foreseen:

1. Although DRM has not impacted on many acts permitted by law, certain permitted acts are being adversely affected by the use of DRM;
2. This is in spite of the existence of technological solutions (enabling partitioning and authentication of users. to accommodate those permitted acts (privileged exceptions.;
3. Beneficiaries of privileged exceptions who have been prevented from carrying out those permitted acts (because of the employment of DRM. have not used the complaints mechanism set out in UK law;
4. Article 6(4. of the Information Society Directive put an onus on content owners to accommodate privileged exceptions voluntarily. Voluntary measures have emerged in the publishing field, but not all content owners are ready to act unless they are told to do so by regulatory authorities.

These four conclusions will be explained in more detail and this will be followed by proposed solutions and recommendations.

Last Tuesday I was at the RES Annual Conference to present my paper “Is Google the Next Microsoft? Competition, Welfare and Regulation in Internet Search”. I’ve uploaded my slides from the talk here and below is a recently prepared overview. The full paper can be online on the SSRN site at:

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1265521

Overview

Beginning from nothing twelve years ago, today online search is a multi-billion dollar business and search engine providers such as Google and Yahoo! have become household names.

While search has become increasingly ubiquitous it has also grown increasingly dominated by a single firm: Google. For example today in the UK Google accounts for 90% of all searches and in many other countries Google has a similar lead over its rivals.

In this paper I investigate why the search engine market is so concentrated and what implications this has for us both now, and in the future. I also look at whether search engines will require regulation and if so in what form. In doing so we also give a detailed explanation of the how the search engine market works, its history, and how it has come to be such a lucrative, and important, activity.

To summarize the main points:

(a) Though search engines provide ordinary users with a `free’ service they gain something very valuable in exchange: attention. Attention is an increasingly valuable good, being in ever more limited supply — after all each of us have a maximum of 24 hours of attention available in any one day (and usually much, much less). Access to that attention is correspondingly valuable especially for those who have products or services to advertise. Thus, while web search engines do not charge users, they can retail the attention generated by their service to those are willing to pay for access to it.

(b) The search engine market is already extremely concentrated. In many countries a single firm (usually Google) possesses of market share an order of magnitude larger than its rivals. As stated, in the UK Google already holds over 90% market share as. However, it is also noteworthy that there are some marked variations, for example in China Google trails the leaders.

(c) Competition issues are likely to become more serious as this dominance becomes established. It is important to realise that while search appears ‘free’ we do pay indirectly via the charges to advertises — who must in turn recoup that money from consumers. A dominant search engine may have incentives to distort its ‘results’ in ways that increase it owns profits but harm society — for example by suppressing organic search results that would substitute for or harm associated ’sponsored’ results (adverts).

(d) There are a number of approaches that regulators and policy-makers could take to protect against these adverse consequences. For example, policy-makers could look at ways to separate the ’software’ and ’service’ parts of a search engines activity, or less dramatically, they could set up a regulatory body to review search result rankings and choices.

Conclusion: it will be increasingly necessary for there to be some form of oversight, possibly extending to formal regulation, of the search engine market. In several markets monopoly, or near monopoly, already exists and there is every reason to think this situation will persist. Left unchecked by competition the private interests of a search engine and the interests of society as whole will diverge and, thus, left entirely unregulated, online search will develop in ways that are harmful to the general welfare.

It is therefore important that policy-makers begin now to develop their strategy in relation to this key area of the knowledge economy. The power rapidly accumulating in the hands of a few major search providers is a great one. It behoves to ensure that it is used in a way that brings the greatest benefit to society as a whole.

On March 18th I was in Brussels to give a talk as one of two “invited experts” (the other being from the Motion Picture Association) to a session on the topic of “Copyright Enforcement” held by the Working Group on Authors’ Rights of the European Parliament’s JURI Committee. Below is the slightly tidied up text of the talk I gave.

Talk Text

Good afternoon and thank-you for inviting me here today. To introduce myself I’m the Mead Fellow in Economics at Emmanuel College, University of Cambridge and an Associate at the Centre for Intellectual Property and Information Law also at the University of Cambridge. I believe that my colleague Professor Bently came here in October to speak to a similar gathering that time on the topic of copyright term extension.

To begin with I want to make a few general points before proceeding to the specific area — enforcement — that today’s meeting looks at.

The first point I would like to make is when we talk of copyright we must remember that it is not a single unified thing but, in reality, a bundle of different attributes. For example, there is the crucial distinction between:

• Economic rights: the ‘monopoly’ right to control reproduction and distribution of the work (and thereby to control, at least partially, its price). We should also note that in some cases this ‘exclusive’ right may be converted into a right for equitable remuneration.
• Moral rights: rights of attribution and integrity. These can exist separately and independently of any economic rights. Furthermore they are often norms that we respect irrespective of any copyright: I still credit Shakespeare for Romeo and Juliet even if it is in the ‘public domain’.

Furthermore these economic and moral rights have a variety of attributes such as:

• Term, i.e. the length that the right lasts.
• The breadth of the right. For example, in the US copyright for performers is ‘narrower’ than in the EU because certain uses of recording (notably broadcast on the radio) need not be paid for. There are also limitations and exceptions related to educational use or use for criticism where permission need not be sought from the rightsholder.
• Lastly there is enforcement. After all one can have very ’strong’ rights but then be permissive in enforcement, or, conversely, have more limited ‘rights’ but be very strict in the enforcement. I would also point out that enforcement is a social as well as legal matter: when I attribute an author the main reason I do it is not because I might get ’sued’ if I do not but because it is the right thing to do — people should be credited when their work is used wherever it is reasonable to do so.

The value of a right is determined by the interplay of all of these. Deciding on the level of enforcement is therefore the same problem as deciding on the level of copyright generally. And we can’t think about this without asking about the purpose behind copyright’s existence.

The answer here is a simple one: copyright is instrument created in order to promote the interests of society as a whole — not, I must emphasize, to promote the interests of the producers of creative works. Of course we care about remunerating producers and artists, both because they are members of society, but also, and more importantly, because by remunerating them we ensure the creation of more works which society as a whole can enjoy.

Nevertheless, it is essential to keep in mind that the purpose of copyright is broader than to promote the interests of a single group. This fact then is central to any assessment of the form and level of copyright and it has important implications. For example if we have a proposal that will help artists but overall harm society we should not support that proposal. Moreover, it is also a fact that is sometimes neglected, for example this very working group is entitled “Working Group on Author’s Rights” not “Working Group on Copyright and Social Welfare”.

In using copyright to promote social welfare we are then presented with a basic trade off between the benefits of the monopoly in the form of the new work created as a result of the monopoly accrued rents, and its in the form of reduced access to creative works. We are therefore seeking a balance: we want enough copyright but not too much. And, returning to our point above, this logic applies to enforcement as much as any other aspect of the “copyright package”.

In particular: if there is already ‘too much’ copyright stronger enforcement will make things worse. If there is too little copyright then more enforcement will make things better. Now, my personal preference is for strong enforcement of fair rules

Unfortunately, the rules currently aren’t fair — for example copyright is almost certainly far too long. As such it is hard to justify a push for strong enforcement. In addition, I would also argue that the unfairness of the current copyright regime is also a major reason why strong enforcement will be difficult, if not impossible, to achieve in practice. Why?

The reason is simple: the successful enforcement of any rule depends on that rule having public legitimacy — being considered reasonable by the majority of the populace. Currently that is not the case: copyright suffers from a serious lack of “respect” and a marked lack of public legitimacy.

If you wish to change that we need the rules to be fair and balanced — it hard to have respect and enforcement of an unfair system. For example, copyright term should be reduced and we should expressly avoid extensions, especially retrospective ones like that currently before Parliament in relation to sound recordings. Such policies appear to reflect nothing more than special interest lobbying and this can only make copyright’s “marked lack of public legitimacy” worse — I would note here the recent joint statement put out by European IP law centres who emphasized that retrospective term extension would seriously undermine respect for copyright and make “piracy the easy option”.

It will be almost impossible to enforce unjust rules. If we are to have strong enforcement it therefore must be of just rules and just rules must be reasonable rules. For example, is it reasonable in an age of costless reproduction to continue to promote a model of copyright based on exclusive rights? Much of the “problem” of unauthorised file-sharing could be resolved if we moved to an alternative compensation system based on an equitable remuneration right approach. In one fell swoop we would eliminate the biggest “enforcement” problem going while also increasing the size of benefits to be divided between users and makers of creative works. Surely this is the more reasonable, and sensible, option!

As I am coming to the end of my allotted span let me conclude. Copyright must be designed to promote the welfare of society as a whole not one specific group. As such, in designing any aspect of copyright, including enforcement, it is important not to have too much as well as not to have too little. We must also remember that copyright, like any other rule or law, depends for its enforcement on willing compliance more than explicit punishment. As such the most important factor in ensuring better observance of copyright is to increase its legitimacy which it markedly lacks at present. To achieve that we need to create a more just, and more reasonable, copyright regime. Thank-you.

Yesterday (Monday) The Times published an open letter signed by many of the leading UK academics concerned with the issue of copyright term extension.

The letter, of which I was a signatory, is focused on the change in the UK government’s position (from one of opposition to a term extension to, it appears, one of allowing an extension “perhaps to 70 years”). However, it is noteworthy that this is only one in a long line of well-nigh universal opposition among scholars to this proposal to extend copyright term.

For example, last April a joint letter was sent to the Commission signed by more than 30 of the most eminent European (and a few US) economists who have worked on intellectual property issues (including several Nobel prize winners, the Presidents of the EEA and RES, etc). The letter made very clear that term extension was considered to be a serious mistake (you can find a cached copy of this letter online here). More recently — only two weeks ago — the main European centres of IP law issued a statement (addendum) reiterating their concerns and calling for a rejection of the current proposal.

Despite this universal opposition from IP experts the Commission put forward a proposal last July to extend term from 50 to 95 years (retrospectively as well as prospectively). That proposal is now in the final stages of its consideration by the European Parliament and Council. We can only hope that they will understand the basic point that an extension of the form proposed must inevitably to more harm than good to the welfare of the EU and should therefore be opposed.

The Letter

Dear Minister,

Open Letter re. Proposed Copyright Term Extension for Sound Recordings

We are writing because of the sudden, and unexplained, change of Government position in relation to copyright term extension for sound recordings.

In 2006, the Government received the recommendations of an independent and comprehensive review of intellectual property policy, commissioned by the then Chancellor Gordon Brown. The review, led by Andrew Gowers (a former editor of the Financial Times) took “an evidence-based approach to its policy analysis”, supplementing a formal call for evidence with commissioned external expertise.

The review examined several extension options, including the increase to 70 years, and explicitly rejected extension as being a bad deal for the UK in cultural and economic terms. The Government, led by the Treasury which was then headed by Gordon Brown, clearly supported this view.

What then occasions a sudden volte-face two years later and only a few weeks after statements from the Department for Innovation, Universities and Skills (DIUS) indicating support for the original decision? We are not aware of any new evidence that has come to light, and the only independent study available since then, that of Professor Hugenholtz at the University of Amsterdam, has also been highly critical of extension.

There has been some talk of ‘moral arguments’ for extension but it is hard to discern a compelling ‘moral’ case for a proposal whose prime effect is to benefit major label shareholders and a few, already highly successful, artists while imposing significantly greater costs on new creators, the general listening public and the custodians of our cultural heritage.

As Gowers concluded, and the Government has until now consistently reaffirmed, policy-making in this area should be evidence-based and designed to promote the broader welfare of society as a whole. Policies that appear to reflect nothing more than lobbying will only perpetuate the “marked lack of public legitimacy” which the Gowers report lamented — and discourage those who wish to contribute constructively to future Government policy-making in these areas. We therefore call on the Government to present any evidence that has led to this change of policy.

Yours Sincerely,

Professor Lionel Bently, and Dr Rufus Pollock, Centre for Intellectual Property and Information Law, University of Cambridge

Professor Martin Kretschmer, and Professor Ruth Towse, Centre for Intellectual Property Policy & Management, Bournemouth University

Professor Nicholas Cook, AHRC Research Centre for the History and Analysis of Recorded Music, Royal Holloway, University of London

Professor P.A. David, Emeritus Professor of Economics and Economic History, University of Oxford

Professor Graeme Dinwoodie, Chair in Intellectual Property Law, Queen Mary College, University of London

Professor Johanna Gibson, Director Queen Mary Intellectual Property Research Institute, Queen Mary College, University of London

Professor John Kay, Chair, British Academy Copyright Review

Professor Paul Klemperer, Edgeworth Professor of Economics, University of Oxford

Professor Hector MacQueen, and Professor Charlotte Waelde, SCRIPT/AHRC Centre Intellectual Property & Technology Law, University of Edinburgh

Professor David M Newbery, Professor of Economics, University of Cambridge

Dr Mark Percival, Queen Margaret University, Edinburgh, Chair, International Association for the Study of Popular Music (UK/IRL)

Dr Martin Cloonan, Senior Lecturer, University of Glasgow, ex-Chair, International Association for the Study of Popular Music (UK/IRL)

Professor Danny Quah, Professor of Economics, London School of Economics

Professor David Vaver, former Reuters Professor of IP and IP Law and Director of the Intellectual Property Research Centre, University of Oxford

Richard Chesser, Chair, Trade and Copyright Committee, International Association of Music Librarians (UK/IRL)