From a motivation perspective, its pretty clear that we have a lot of fairly complicated issues in front us.  With 7+ billion people on this planet, and all of our complex, perfectly reasonable, and less than complimentary goals for material prosperity and ecosystem stability, long healthy diverse lives and healthy diverse ecosystems, good food and clean water, security, biodiversity, and predictability, things get pretty complicated.  Our collective capacity to  move through the next 5, 10, 1oo years with equity and responsibility, and our capacity to shift rapidly to a platform of true sustainability, will depends in part on our capacity for effective collaboration and in part on our willingness to focus on the work that is most likely to move us forward.  There is a lot we can know about the world, but if we focus on the really sticky questions surrounding our capacity to live sustainably on this planet, and we do this in a way that makes the most of our diverse talents, we will likely make a lot more progress than if we continue running our own races, marching to the beat of our own drummers.  Its easy to talk about the need to focus on “important research”, but its not a simple prospect for most of us.  When we talk about humanity in its totality and we consider the scale and complexity of the issues we need to grapple with, it’s clear we need some pretty wide ranging collaborative efforts.  Efforts that walk between disciplines, and between academics, civil society organizations, and the public and private sectors.  These are not simple to organize or sustain, there are differences in cultures, incentives and goals, and when I was inside an academic institution, I found few clear pathways for creating and sustaining these collaborative efforts, and even fewer signposts for identifying the research and synthesis that will deliver the largest benefits for ongoing work in conservation and sustainability.

The Luc Hoffman Institute seeks to fill these needs.  We will bring research and synthesis together across disciplines, geographies and institutional cultures, focus that work on critical question sets and themes standing in the way of progress on sustainability and conservation, and accelerate the work so that it is completed at the speed at which policy decisions are made.  We are situated within WWF, among the world’s largest conservation organizations, and yet we are very much a boundary organization, working between civil society and academic research capacity.  Much of our work will focus on organizing and supporting collaborative research, synthesis and implementation on specific themes. We are also taking a longer view, working to support global scientists who thrive in collaborative settings and are committed to maximizing the impact and the uptake of their work.

Hoffmann Fellows will play major roles in all our work. Hoffmann Fellow Positions are interdisciplinary post-doctoral positions focused on collaborative research and synthesis.  Calls for Hoffmann Fellows will often be made with a specific disciplinary focus, they will often have both an academic and a practitioner mentor, and they may be based in any number of locations, depending on the associated project and need.  All Hoffmann Fellows will work with a wide range of academics and practitioners in a variety of collaborative frameworks. Their work will often cross disciplines and institutional cultures and we will work to make sure their work is consistently focused on high-impact conservation research and synthesis.  This particular Hoffmann Fellow position will be based in Gland, Switzerland, and the position will work closely with the Hoffmann Institute Director (me) and the core staff as they come on board.  This position will involve travel, and time will likely be split between a range of existing research projects I have ongoing from my previous life as an academic,  the development of new research, and direct involvement with the collaborative groups that will come together around research and synthesis questions.  In a nutshell, this is an opportunity to be embedded at the center of one of the largest global conservation organizations, to work on a wide range of conservation science with direct impacts on practice and policy, and to join a diverse, tight-knit team focused on lowering the barriers to collaboration across disciplines and institutions.   We anticipate we will have between 4 and 7 Hoffmann Fellows working on a diverse set of topics at any one time, and while these fellows will be working across the globe, they will also be a team, and we will bring the Hoffmann Fellows together for periodic intensive training courses, networking events, and collaborative research.

To stay in touch about progress on the Institute, the Hoffmann Fellows Program, and all things related,  follow me on Twitter, or check in here.  I will migrate all of this to the Institute Web Site when we launch.

Below I  update the analysis and clarify my approach and address some of the critiques that came from some of the more statistically-minded readers.

I gave some thought to the right way to create comparables between countries, and I think the use of the Inequality-Adjusted Human Development Index (IHDI) may be preferable to the use of the newer HDI that does not adjust for inequality of human welfare distribution among citizens in a country.   There are a lot of reasons why differences in the distribution of welfare among citizens could be important, and the goal in using one of these indices is to create a set of comparables among countries.  In the following two graphs, I first plot the same relationship as before (now with Great Brittan Included – thanks Cooper), and I then plot the same relationship using IHDI (> 0.75). They show similar trends, with IHDI showing a stronger fit (correlation going from 0.7 to 0.8) as I expected it might.

Perhaps the most interesting critique of these data comes from the idea that suicide rates should be removed from the data.  I can see both sides of this.  If we include suicide, as I do here, we are focused on all violent gun deaths, and the relationship between gun deaths and gun access appears relatively clear (a bit on leverage below).   When we remove suicide from gun violence, and keep the same restrictions as above (using HDI or IHDI) the relationship weakens considerably, and we get extremely large leverage values for the US.  (I have included the data I used at the end of this post for people to play with, and an example graphic is here). As Richardson et al (2011) point out – the US had a homicide rate that was 6.9 times higher than other high-income countries in 2003 (the year used in their analysis).  The disparity in the data I am using is slightly less, but the massive outlier status of the US  – both in terms of gun availability and in terms of homicides and gun violence in general, makes me think this discussion is worth the ink.  Bottom line,  we have a bunch of countries with relatively low firearm deaths and relatively low firearm availability, and we have the US, at the other extreme. When we remove suicide from the mix,  tts pretty hard to use this data to make strong conclusions.  Is this a scale dependent relationship that is obscured by other differences between countries until  we get out past 50 or so firearms per person?  Is there something very different going on in the US that has nothing to do witb gun availability?  We are  not going to answer these questions with the data at hand, and we are probably better served by looking at other datasets – particularly data comparing gun availability and gun violence among states in the US, where we start to develop stronger control groups.  For those interested in digging deeper, Miller’s 2003 paper is a good place to start, or the review by Helpburn and Hemenway.  My quick read of the data suggests a significant link between these variables.

One more point here – as a matter of public policy, it may also be a bit questionable to remove gun-related suicides from the debate over the relationship between gun violence and gun availability, but that depends a lot on your perspective, and I will let others hammer that out.

A final point on leverage values and the US – A number of readers on the blog and in facebook took issue with my fit line, and suggested that the US was a significant outlier, artificially increasing the fit of the relationship.  To some extent, that is exactly the point.  I was careful in the previous post not to stake to strong a claim on the linear fit, but it is worth pointing out a couple of things here.  The US is an outlier, both in terms of gun ownership and in terms of gun violence, but if we take the US out of the analysis (which sort of misses the point, but is interesting from a statistical perspective), we still get a significant positive correlation between gun ownership rates and gun-related violence, regardless of whether we restrict the data using HDI or IHDI, though it is stronger using IHDI. This is true for gun violence, but not when we remove suicides (see previous paragraph).

I got a few comments on the blog focused on alternative modeling approaches, and I like where they are heading, so I am posting the data here both as a CSV called guns, and in the original excel format, called gunsdata.  This way, Tarj, SKG, Alex and  others can build on this late night obsession of mine.

Back to Environmental issues for me!

Gun Violence as a Function of Gun Ownership rates for all countries

The first graph is the relationship between gun ownership (guns per 100 residents) and gun violence (gun related deaths per 100,000 people), across all 75 countries where that data is easily obtainable (see end of post for data sources).  If I were an advocate for gun rights, I might feel pretty good – there appears to be no correlation at all between gun ownership and gun violence among countries.  Here in the United States, we look somewhat remarkable in our capacity to keep our guns in check.  We have loads of guns, and a lot less gun related violence than many countries.  Countries like… El Salvidor, Jamaica, Honduras, Gautamala, Swaziland, Columbia… Hmmm.  These countries are not exactly comparable to the US.  In a perfect world, we’d like to have data on a series of countries that are mirror images to the U.S. in all ways (size, GDP, urbanization, age of country …) except access to guns.  We don’t have that of course, but we get a lot closer by restricting the data to “similar” countries. There are a number of metrics out there we could use to do this. Here I use the UNDP Human Development Index (HDI) as a way of creating a similar set of countries.   The HDI combines data on  life expectancy, education, and income indices to rank countries into four tiers of human development – very high, high, medium, and low.

In the second graph, I restricted the data to all countries in the top  HDI category (Very High HDI [HDI > 0.79]). The picture changes dramatically.   Now we see a clear positive relationship between gun access and gun violence.  The US clearly has the most gun violence and the most guns.  I have fit a linear regression through this data (Adj. R2 = 0.47), and if we think the linear relationship is reasonable to begin with, we could begin to think about why some countries are above the line and others are below the line (for example, the US is considerably above the line, and thus it appear that US citizens not only have more guns per capita, they also have a harder time keeping their guns pointed away from other people compared to  many other countries).  I would not  walk too far down that path without adding a lot more nuance to the analysis.  There are all sorts of things we might want to

Gun Violence as a Function of Gun Ownership rates for countries with a Very High Human Development Index Score 

consider – size of country, % of people living in big cities, etc..  I doubt very much these variables will change the basic picture (more access to guns is positively related to more gun violence, all else being equal), but they would be worth exploring.  All the data used here were taken directly  from public sources, see firearm-related death rates and guns per capita data.

A bundle of tips for building a clear slide

• Titles: Use a simple declarative/informative brief title at top of EACH slide. Not “Effects of A” but “A Blocks B” or “A is Inactive” or “A activates B.” This will help those who doze or looked down or jotted a note when you first said what the slide was.
• Size of lettering. 20 to 35 point in PowerPoint! Everyone makes them too small. 18 points is the lowest you can go for a label. The larger size is for titles. A convenient rule of thumb is that the lowercase letters of any label need to be 1/40 of the size of the picture at least–you can measure this during practice projection. This goes for the numbers labeling tic marks on graphs and the indication of their units too. Don’t be embarrassed to use large letters. Look at any billboard. No printed figure labeled for publication has letters big enough for a projected slide made from the same picture. Re-letter figures from the literature to meet this requirement. You can erase the old letters in Photoshop and re-label in PPT, or cover the old letters with new ones in a white box. To make a test, project something in the auditorium and go to the very BACK of the room and ask if it is clear. Can you really read the smallest letter? Similarly a transparency made with the 12-point type that we would consider generous for a printed document is not visible on projection.
• Lines: Often you will import graphs from another program. Either in PPT or in the original program, make the axis thickness and symbol sizes adequate. A 1 point line thickness does not show. If you import graphs and then shrink them on the PPT page, letters, lines, and symbols will become smaller.
• Colors: Colors are great but try also to have contrasting brightness. Objects differing in color but not brightness are hard to see. Contrast is paramount. Textured backgrounds just make it hard to see the stuff you are presenting. They obscure your message. Dark reds and blues are brilliant on the computer screen but disappear if put on a black background. Dark reds are fine against white. Yellow disappears against a white background
• Consistency and continuity: Movies have a continuity editor who makes sure that the cars stay the same color from scene to scene and people wear the same clothes coming out of the door as they did going into it. Similarly, try to keep the same color/symbol/thickness for control data versus that for test data. In diagrams, represent the same object the same way each time. Use decent graphics and layout and a consistent theme — so it looks and feels like the slides were made for the talk you are actually giving rather than a bunch of slides from other talks
• Transitions: use av to supplement your message, not provide the main entertainment. zooming slides, too many animations, lots of videos, etc. etc. the audience should remember YOU first, your message/science second, and your av third.

You know when you are ready when…

• You know what is on the next slide without having to think, and you can transition easily from one slide to the next
• You have eliminated all the text “crutches” from your talk
• You know what part you would cut if your talk is running too long and you are able to cut it on the fly without a pause[1]
• You are comfortable explaining all of your material and working with the audience directly
• You know what points you need to make for every slide you show

Resources

• Watch Amy Cuddy’s ‘power poses’:
• Garr Reynolds’ blog Presentation Zen is pretty good if you can get past the self-promo and wise sage schtick.
• It is worth studying – though not necessarily emulating – the so-called Lessig method.
• Watch, and re-watch, some fantastic seminars. If you are associated with a strong academic department now, the best place to look is the seminar of the last couple of people you hired.
• For better or worse, Powerpoint is the universal medium of research seminars. There’s a growing realization that Powerpoint was adopted without hard thought about how humans process visual and written information. Although this seems like a boring debate, it’s important for everyone who uses Powerpoint to ponder a bit. Michael Alley (Penn State) has done audience-based research on this. Click here for some of his thoughts on this.

[1] It is excruciating when a speaker says ‘I should skip this since I don’t have time’, and then they end up talking a long time about it anyway (And this is where having less text on the slides useful because it’s way less obvious if you’re skipping something…)