But this new consultation is a little different from the old ones, in both form and content. First the form:

Rather than follow recent practice, and produce a document on which interested parties can comment, we wish to make sure that all those with the greatest knowledge and expertise in this field can contribute to the development of a draft strategy, which can then be widely consulted on later this year.

Seems like a sensible idea. Rather than drafting a bunch of stuff internally that only gets slapped down as being simultaneously over- and under-ambitious, why not try to build a consensus from the start?

The second difference is the scope of the consultation. Previous efforts have had fairly wide remits, looking at technology standards, skills and quality assurance, grant schemes, feed-in tariffs and so on. But the new strategy, undoubtedly reflecting the coalition’s spend-thrift ways, is crystal clear about what is in and, more to the point, what is out of scope. Check out these extracts from the invitations to join the four working groups:

• WG 1: Quality and certification Out of scope: complete removal of certification and industry standards, publicly financed instruments.
• WG 2: Technology development Out of scope: support for R&D and developing export markets would need to be through the existing mechanisms within Government, publicly financed instruments
• WG 3: Skills Out of scope: not looking to set up new bodies but to work with existing organisations operating in the sector, publicly financed instruments
• WG 4: Information and advice Out of scope: Publicly financed instruments

Notice a trend?

First off, my blogging routine has somewhat ground to a halt and I’m not updating this site as much as I used to (or would like to). Work commitments keep me pretty busy and whatever online time I do have, I tend to contribute over at AcademicProductivity.com instead. So part of this post is to say sorry to those readers who might have been looking for updates on the UK microgeneration scene or other news.

But this post is also about trying to understand why my blogging efforts didn’t really take off. There’s any number of sites that will tell you what you need to do to be successful – post frequently, build a community, etc. – and yes, I’ve neglected much of that advice: mea culpa. That’s just big picture stuff though and I’d like to do a proper statistical post-mortem to understand why my blogging habits broke down. In other words, WWNSD^*?

The record

Let’s start with some basic descriptive statistics of my posting record.

• First post = 2002-09-27
• Total posts = 143
• Mean lag between posts = 17.4 days

Next I plotted the distribution of posts and modelled it as a normal distribution with μ = 2006-11-05 and σ = 441.1 (the data passes a Shapiro test, p = 0.000434).

You can see that it’s not really normal and there’s a point where I tried to kick start my blogging again in early 2008. But using this distribution let’s us answer some simple questions.

For example, at what point should I have admitted defeat and stopped blogging? Using the language of statistical process control, there should be a sigma threshold at which point most of your good posts are behind you and you’re just in decline. My last post was published 61 days ago: at that point, assuming a normal distribution, 98.6% of the posts I was theoretically ever going to make were behind me. This corresponds to +2.2σ.

So that’s one useful finding already: by the time, you’re at the +2σ side of a normal distribution, you should start thinking about why you blog. Actually scratch that – start thinking about it at +1σ ; if you ever hit +3, find a new hobby.

Draft posts

In addition to the 143 published posts, I have 58 draft posts. To my mind, this is where the real autopsy begins.

One question I had was whether my blogging slowed down because I stopped having ideas, or because I just wasn’t follow through on them. The figure below compares the temporal distribution of both published posts and drafts and there is a significant difference between the two samples (using Kolmogorov-Smirnov test, p = 1.665e-05).

At first, this suggests that both modes of failure are contributing. The narrower distribution of the draft posts shows that the flow of new ideas did dry up at some point even though I kept posting after that. But anecdotally, I can remember that these most recent published posts were written on the spur of the moment: they never even entered the drafts queue. So while I did stop thinking of new draft ideas, I think new post ideas in general kept coming.

The bigger issue was the lack of motivation and the resulting failure to convert drafts to posts. Posts were taking simply too long to complete and the sight of an ever-increasing backlog made it difficult to know where to start.

So there’s another warning sign: if your drafts pile builds up to more than about 5 posts, consider pruning substantially. You can either delete the drafts entirely or use a link dump post to clear out the backlog. Just remember that if you’ve got more than a few drafts sitting around, it’s very unlikely that you will go back to these posts and if you do, you probably won’t remember why they were interesting in the first place.

Tits versus owls

I think the drafts dilemma is a really good illustration of why microblogging services like Twitter have taken off. For me, a quality post will take a couple of hours work. I like to check my facts before publishing, find a few interesting references, and it’s hard to really think through an issue and present something new and useful in less than 100 words. (My posts may have only averaged 252 words but there’s a big spread.)

In contrast, writing 140 characters takes very little time at all and even seasoned bloggers like Kottke seem to have adopted quite a brief style. Compare this with people like Andy Baio, Ben Fry or Errol Morris, all of whom blog infrequently (once a week to once a month) but with posts ranging from a couple hundred words to thousands. If tweeting is for the birds, then these guys are the owls: patient and knowledgeable.

Sources of inspiration

Next, I wanted to figure out how many of my posts are inspired by links. My gut feeling is that I often blog in response to things I’ve seen on the web and when I was focusing on microgeneration issues, these germs of an idea often came from traditional news media. So I looked through the draft posts and identified those that had (a) at least one link in them and (b) a news site link (specifically from the Guardian or the BBC). The result? 72.4% of my draft posts contained at least one link and 44.8% had either a BBC or Guardian link in them.

Is there any difference between the share of links in published and non-published posts? In other words, were the drafts “lazier” than the regular posts? Unfortunately I can’t easily tell since 89.5% of published posts have a link in them; they may not have started from a link but they did grow to include one. The presence of a news link is a slightly better measure in this regard, but the results still don’t show a significant difference (Chi-squared test, p = 0.389).

Timing of posts

How about the timing of the posts and drafts? Were there certain days that I was more likely to post than others? Well yes and no. First, a chi-squared test shows that there is no significant difference between the weekdays of draft and published posts (p = 0.972). However if you look at the overall distribution of the activity, there is a significant difference between the observed daily frequency and the null hypothesis that the posts would be equally distributed across all 7 days (p = 7.19e-11). As the figure below shows, Tuesday is more popular day for posting and Saturday decidedly less so. Apparently this early week preference is a common phenomena with Twitter as well.

As a final thing, I did a time series decomposition. This sort of analysis can help you identify seasonal, trend and irregular components in your data. After first grouping the data into weekly bins, I generated the following plot. For my data, there isn’t really anything going on beside the main trend. However it would be interesting to apply this analysis to a larger data set like Twitter’s feed or the posts of a more prolific blogger.

Conclusion

I think my experience has probably been fairly typically of the lower middle orders of bloggers. I started with a lot of enthusiasm and a clear idea about what I wanted to cover. But as time passed, other pressures crept in and I wasn’t able to keep up the pace, even as the site started to attract more interest.

The key issue for me is that I like to write longer posts and these take time. If it suits your personality, then you may be able to write a brilliant blog with short sharp posts and many people do. But if you’re trying to cover issues in more depth, then a much more concerted effort is required.

This analysis has been very helpful for me to understand my blogging habits and foibles. But I think there are three take-away points for any blogger:

• Monitor post frequency
  You need to monitor the frequency of your published posts so that you can observe any decline in output and then actively decide what to do about it, rather than letting inertia take hold. A simple sigma-style analysis can be helpful: if you’re on the +1σ side of your post distribution, then start re-evaluting what you want to achieve with blogging.
• Keep it fresh
  You need to be ruthless in keeping your draft queue short so aim for fewer than five, and certainly no more than ten, draft post ideas. The author’s enthusiasm shines through on good blogs. If you’re trudging through six-month-old ideas just for the personal satisfaction of clearing out a backlog, stop: your readers don’t care.
• Tits and owls
  There appears to be two emerging styles of blogging. Tits are those people that thrive with a short style, using Twitter or just shorter frequent posts. By contrast, owls post less frequently but with detailed longer posts. New bloggers should experiment and get to know which style works best for you. Be aware though that if you’re an owl, you may have a harder job building up a following for your website. You’ll need to find an audience that’s patient enough to wait for your new posts and read their longer contents. These categories are also mainly applicable to amateur bloggers. Pros may have the time necessary to do one detailed post per day, whereas the rest of us might only manage one good post per week or per month.

Having now realised that I’m an owl, I plan to revamp the site in the coming months as a more static home on the web with less frequent, but more detailed, posts. Hope to see you back here then.

One of the main themes running through the event was how to measure greenhouse gas emissions from cities. There have been numerous figures published recently, such as the IEA’s estimate that cities are responsible for 71% of global direct and fossil-fuel related emissions. There was much hand-wringing among the conference participants though about whether the methods for compiling such inventories are sufficiently mature to facilitate comparative studies or for use in international trading arrangements.

Some of the worry seems misplaced. Of course better data is always desirable but as a representatitve from ICLEI pointed out, the world hadn’t even agreed on the official list of greenhouse gases in 1992. Now 17 years later, we’re complaining about too many competing methods. And anyway, if the world is aiming for massive emission reductions on the order of 80% by 2050, then surely we have enough information to act.

This pragmatic view was best expressed in a paper by Chris Kennedy, Anu Ramaswami and others titled A protocol for City based GHG emission indices. Using the corporate emissions protocol of the World Resource Institute, they suggest that the emissions of a city should include:

• Scope 1 emissions from the consumption of fossil-fuels directly within the city boundary (e.g. natural gas);
• Scope 2 emissions from the indirect consumption of imported fuels like electricity, heat or steam; and
• a limited set of Scope 3 indirect emissions from key resources consumed within the city (e.g. cement, steel, food) and a share of major cross-boundary transport (e.g. air travel, freight).

The key thing about this approach is that by using a reduced set of Scope 3 emissions, you can capture the open nature of cities, i.e. their dependence on resources imported from other regions, without introducing too much administrative hassle. It’s a question of diminishing returns and this proposal seems like a sensible one if a practicable international framework for urban emissions inventories is to be established.

The full paper, and the accompanying presentation, should be available from the URS website in the coming days.

Alpha’s main advantage is that it contains large amounts of curated data, codified in a robust manner that allows for “computation”. Reasoning might be a better word. If you enter a query like “GDP US vs. France“, it knows that you want to compare the GDP time series, whereas “GDP US / France” works out the ratio between the two values. In other words, Alpha is a demonstration of the potential of the semantic web. If all data is labeled and the relationships between types of data explained in an ontology, then computers can use this information to manipulate data and answer pretty complicated user queries: like “how many UK Premiership footballers come from home towns over 3000m altitude?” (why you’d want to do such a query is another, perhaps unanswerable, question).

At the moment, many of the Alpha datasets are incomplete and so you can only do limited queries. But since I work mainly on cities, I wanted to check what’s available on this topic.

The answer is not much, but then not much is all that’s readily available anyway. If you do a simple search on a major international city – say Lagos – you get the following:

I thought maybe if you tried a US city, the results would be better since much of Alpha’s data comes from American sources. But nope – you just get the basic location, population, weather, time and elevation.

But you can do neat comparisons: check this out. Flight info!

Sadly, for those interested in urban energy, you can’t do much else. Type in “London energy consumption” and it thinks you want to see how long it takes to fly from London to Energy, Illinois (7 hours 40 minutes, if you’re curious).

So overall, a neat tool but still a work in progress. I guess if I was to draw up a wishlist of changes, I’d like to see more curated city data sets (from the UN and IEA’s World Energy Outlook, for example) and an option to set metric units by default!. (If this bothers you too, go here and vote for the feature. In the intro video, Stephen Wolfram mentions that they use IP lookups to contextualise the results – i.e. do you mean London, Ontario or London, England – but I can’t tell if I’m seeing imperial because they think the UK runs on imperial units or if they just assume imperial for everyone.)

Then on Wednesday, we got some leaflets through the door and I found out that the head of the RMT, Bob Crow, is campaigning with the No2EU party. Ding! So he’s selfishly competing for the anti-Europe vote as opposed to altruistically warning about the dangers of electing racists who exaggerate. (The leaflet stack had one from the BNP claiming that the main parties want to “give 80 million Muslim Turks the right to swamp Britain”. A) There are 72 to 75 million Turks and B) I doubt all of them want to come over here.)

But is that really kosher? Having your members, who work for a public body, go out and picket on behalf of their shop steward? Shame the elections aren’t next week – they could have handed out the leaflets during their planned strike instead and saved themselves a day of holiday.

At first I thought, ‘Well, I must not have read the paper properly that day.’ But a retrospective search turns up only two Guardian articles (one news, one opinion), a cranky opinion piece in the Times, and nothing in the Telegraph, Independent, or Economist.

This is disappointing. The report asks serious questions about how our society seeks to improve the lives of its citizens and it’s been almost entirely ignored by the mainstream media. And while the blogs do take up some of the slack, the debate isn’t always as rigorous as one might hope.

Having now read some comments from around the web, and re-examined the original report, I think part of this apathy is because of the definitional baggage and misunderstanding that surrounds the concept of economic growth. Let me explain what I mean.

According to the SDC, the report is an examination of the “connections and conflicts between sustainability, growth, and wellbeing.” This seems straight-forward and as expected, there is lots of interesting material in there about resource consumption, the sociology of consumption, debt levels and so on. But the problem is that the term “economic growth” isn’t clearly defined anywhere and so people tend to get carried away with what they believe economic growth to be, rather than properly digesting the report’s message.

So let’s start afresh and tread carefully. The Google consensus defines economic growth in two parts: 1) an increasing production of goods and services in an economy 2) as measured by real GDP.

At first glance, Prosperity Without Growth appears to focus primarily on part 1, the consequences of production and consumption processes. In this context, growth clearly relates to issues such as increasing absolute resource consumption, the feedbacks between improvements in labour productivity, consumption and employment levels, the links between the continual production and consumption of novelty and so on. But the second part of the definition – that is, growth as measured by changes in real GDP – is covered in a less obvious way. As far as I can tell, no where does the report say that the growing value of economic output is a bad thing. The problem is the pursuit of growth in GDP, a measure which fails to account sufficiently for the finite nature of natural resources (apart from market scarcity effects) and the fact that increased GDP does not necessarily mean happier healthier people.

So, for example, when blog commenters say that failing to pursue GDP growth will deny those in poverty a chance to improve their condition, they’re assuming that GDP is a good measure of well-being. It’s at best an imperfect measure and in fact, we could raise the GDP per capita in our hypothetical poor society in all sorts of ways that don’t actually improve the well-being of those we’re trying to help. We could gain this new “wealth” by depleting our natural capital stocks (e.g. by over-harvesting forests, fisheries) or by concentrating any societal income gains with the already well-off.

As a commenter in this forum suggested, perhaps the best way to understand these issues is via this thought experiment from 1966: the idea of the spaceman (resource constrained) versus the cowboy (unconstrained) economy.

In the cowboy economy, consumption is regarded as a good thing and production likewise; and the success of the economy is measured by the amount of the throughput from the “factors of production”…The gross national product is a rough measure of this total throughput…

By contrast, in the spaceman economy, throughput is by no means a desideratum, and is indeed to be regarded as something to be minimized rather than maximized. The essential measure of the success of the economy is not production and consumption at all, but the nature, extent, quality, and complexity of the total capital stock, including in this the state of the human bodies and minds included in the system. In the spaceman economy, what we are primarily concerned with is stock maintenance.

What I would argue is that Prosperity Without Growth is concerned with the physical, social and economic characteristics of the spaceman economy. It is not saying that societies should stop trying to increase their “wealth”; it is saying, in part, that how we measure wealth – or rather prosperity – is inseparable from the way we go about achieving our goals. Indeed measurement issues are explicitly addressed in the report’s policy recommendations: #4, to improve macro-economic accounting and re-assess the use of GDP and #7, to develop a new measure for a more widely defined notion of prosperity. (Although in retrospect, perhaps this could have been highlighted more clearly. The SDC’s info page on the report doesn’t mention these definitional issues at all and I think fails to distinguish why the report is different from all the other world-is-going-to-hell-in-a-handbasket stuff that’s already out there.)

Sadly, it seems that these shades of gray are too subtle for many in both traditional and web medias to grasp. And if these concepts are not brought to the attention of the wider public and given the debate they deserve, it seems unlikely that the political system will respond and use the present economic crisis to re-assess what it means for us to be prosperous.

In fact, Sellafield is a classic illustration of the failure of British industry. We were pioneers of nuclear power but in our desire to build our own atomic weapons, failed abysmally when it came to developing and managing our own civil reactors and reprocessing plants.

As a result, we have been left with a multibillion-pound clean-up bill and the prospect of buying either American or French reactors for our next generation nuclear plants. The lesson of Sellafield is not so much that nuclear power is dangerous but that Britain seems incapable of implementing any long-term engineering plan that comes its way, from high-speed trains to wind turbines or rocket launchers.

To be honest, I can’t tell if this is crazy good or crazy bad. On the one hand, compact self-contained nukes would give better output – more of it and more predictable – than similarly distributed renewables. But still, the units are buried underground and every 7 to 10 years, a lorry full of fresh uranium comes round to your house (well more realistically your local factory, industrial estate etc.), digs up the reactor to refuel it, and takes away the old waste. Although the transportation of nuclear materials has been relatively safe to date, I wonder how things change when you start shipping around lots of little containers rather than a few big loads (ignoring medical isotopes).

The first units are scheduled for delivery in five to ten years to a Czech utility company.

For years, microgeneration advocates have looked at the rapid deployment of solar and wind in Germany and called for similar incentives, which pay microgen owners for exporting their electricity to the grid, here in the UK. But in 2005, my research found that the UK government was fundamentally opposed to this option as an unnecessary intervention in the market. Obviously, market intervention has become a little more fashionable of late but there have also been serious economic analyses published to say it is in fact more economically-efficient to promote renewables and microgeneration using a feed-in tariff, rather than the current renewables obligation mechanism.

Of course the details haven’t been announced yet. But that the fact that a feed-in tariff is now being considered, alongside the government’s new commitment to a 80% – not 60% – reduction in greenhouse gas emissions by 2050, suggests that things may be changing in Whitehall. Let’s wait and see.