Here’s the abstract:

When one surveys news reports today, mention of disasters seem to be commonplace. And, quite often, there is a lot of response to disasters. Aid agencies channel money or other forms of relief directly to communities who need it or to organizations who are better prepared to implement response work. Governments create plans to offer rehabilitation support, or find some other way to compensate those who are affected by disasters. Academicians write reports comparing one disaster to similar disasters, and theorize about what could have been done to minimize the impact of the disaster.

But where is the community in this post-disaster scenario? And what about the communities who have not suffered catastrophes? Are they safe? Is that enough? Is it appropriate to merely respond to disasters, or is there a better way to approach disaster risk reduction? And what does this mean for a development organization?

ACEDRR believes that there is simultaneously a positive and negative relationship between development and disasters. However, development efforts have incredible potential to contribute to disaster risk reduction and to help create a “culture of preparedness”. Development practitioners have a responsibility to be aware of this continuum and use it to guide their work and to build knowledge about disaster preparedness and prevention.

This primer is by no means a complete account of the relationship between disasters and development. However, it is hoped that this primer can serve as an introduction for practitioners to become more sensitized to the relationship, and that they use this awareness to change from working in what is mostly a reactive manner, to working in a proactive one. It is also hoped that this primer can lay a foundation for further discussions and research—not discussions and research designed around communities, but ones which include the community as an integral partner and as a stakeholder whose traditional wisdom might be able to help us with some of the more complicated issues we face in our rapidly modernizing world.

And, here’s the report itself.

[Cross-posted at ananda.mahto.info. Spread the link around!]

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Map party time. For some reason this happens every once in a while with me. A few years ago, I got to develop a website filled with choropleth maps galore. It was a pretty tedious process. Excel sheets. Photoshop. No good access to free Indian shapefiles. I was even thinking of making my own SVG files of Indian states at one point and thinking of a complex PHP and MySQL website.

Skip forward a few years now, and I’m back with the maps. Only this time, I have some new tools and resources: the software named after a pirate’s favorite letter, some free maps from the Global Administrative Areas website, some data from the 2001 Indian Census (I selected district data, all districts, and total population), and Google Docs (to clean up my CSV files).

Enough history. Let’s get started mapping, and since I’m in Tamil Nadu, I’m going to restrict myself to that state.

First, download the district level RData file from the GADM website (it’s a little under 7MB). Double-click on the file to open the R workspace. By using > ls() we can see that the only object in this workspace is named “gadm”. At this point, you can’t actually do much. Typing > fix(gadm) just pops up an editor window that says
<S4 object of class structure("SpatialPolygonsDataFrame", package = "sp")> which isn’t really useful. We need to load the libraries we’ll need:

> library(sp)
> library(RColorBrewer)

Since I want to see what is in the gadm object, I can just write a CSV of the object by typing > write.csv(gadm, "gadm-data.csv"). This will get us the following file:

As you can see, this spreadsheet is for all the districts in India, but I’m only interested in Tamil Nadu. Furthermore, without first sorting, not all of the Tamil Nadu districts are presented together. To fix this, I can simply create a new object for Tamil Nadu. For this, I only want the rows where the value in the “NAME_1″ column is “Tamil Nadu”. It might also be easier for me if I have a CSV of this new object so that I can arrange my data from the census in the right order, and it’s also easier if the district names (which are under the variable “NAME_2″) are in alphabetical order.

> Tamil.Nadu = gadm[gadm$NAME_1=="Tamil Nadu",] # Select only Tamil Nadu
> Tamil.Nadu = Tamil.Nadu[order(Tamil.Nadu$NAME_2),] # Order by district
> write.csv(Tamil.Nadu, "TN_db_raw.csv") # Write output as CSV

Fortunately, the names for the districts in the GADM dataset mostly match with those from the Indian census, so matching the data is quite straightforward. I’ve gone ahead and uploaded the combined information to Google Docs.

Let’s load this new file.

> TN.DB = read.csv("http://news.mrdwab.com/tnpop", header=T)
> names(TN.DB) # check to get variable names
[1] "NAME_2"     "Total_HH"   "Total_Pop"  "Male_Pop"   "Female_Pop"
[6] "Sex_Ratio"  "Area"       "Pop_Dens"

And now, let’s create a map. While it might be tempting to create a map of, say, total population, that’s not really how choropleth maps should be used. From the data here, without doing any further calculations, the only variable that makes sense to map is population density. I’ll start by doing a quick summary and plot to see what the data look like

# Use "digits=" to make sure that R doesn't round our results
> summary(TN.DB$Pop_Dens, digits=6)
     Min.   1st Qu.    Median      Mean   3rd Qu.      Max.
  278.870   343.480   416.850  1291.610   605.765 24963.500
> plot(TN.DB$Pop_Dens)

Notice the outlier. This will definitely affect our data if we don't deal with it.

From our plot, I can see that there is an outlier in the data. This is useful to know since if I simply went ahead and created our “bins” with that data point included, I wouldn’t end up capturing the variance between the lower values: they would most likely all be put into one bin.

In this map, I’m going to be lazy and simply divide the population density range into bins that are (more-or-less) equal sizes. You can also use quartiles if you prefer.

# Set your lower and upper limits, excluding the outlier, and length 
# equal to one more than the number of bins you actually want.
> TNPopDense = c(round(seq(from=0, to=1100, length=8), digits=0),
+              round(max(TN.DB$Pop_Dens)))
> TNPopDense # Preview our breaks
[1]     0   157   314   471   629   786   943  1100 24964
# Use our breaks to put each of the values in the "Pop_Dens" column
# into its corresponding bin.
> PopDenseRange = as.factor(as.numeric(cut(TN.DB$Pop_Dens, TNPopDense)))
> PopDenseRange # Preview which bins the districts fall into.
 [1] 3 8 4 4 2 3 3 5 7 3 5 4 3 3 2 2 2 4 2 5 3 5 4 3 4 3 3 4 3 3
Levels: 2 3 4 5 7 8

Note that this may not have been the best way to do this–I wanted to put each district in one of eight levels, preferably using all levels, but they only fall into six levels with this particular set of data.

Now, using the levels that we got in the previous step, we can work on our “legend” for the map. We can use “> 157″, “157 – 314″, and so on as our legend entries. After that, we merge a column into our TN.DB object to store these new values.

> levels(PopDenseRange) = list("< 157"="1", "157 - 314"="2", "315 - 471"="3",
+                         "472 - 629"="4", "630 - 786"="5", "787 - 943"="6",
+                         "943 - 1,100"="7", "> 1,100"="8")
> TN.DB$PopDenseRange = PopDenseRange # Merging info
> shadePopDense = brewer.pal(8, "Blues") # Setting up the coloring scheme
> Tamil.Nadu$PopDenseRange = PopDenseRange
# And now we plot it!
> PopDensePlot = spplot(Tamil.Nadu, "PopDenseRange", col="blue",
 +               col.regions=shadePopDense,
 +               main="Tamil Nadu population density by district")
> PopDensePlot

Here's our final map of population density.

And that’s pretty much it! I’m sure there’s a lot of room for improvement in the code and the process, but overall, not too bad for just a few lines of syntax in R. [R also exports really nice PDF files.]

Aside from referring to the typical R documentation, this example really helped me to figure out what I needed to do.

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Seriously, people. This is no laughing matter!

At least that’s what one of my former students told me at Tata-Dhan Academy’s third convocation, during which I got to dress up in a very white shirt and a long white dhoti.

The convocation was an interesting event. It was organized on pretty short notice, but it was still very well attended by the local community. It was also a little bit of an adventure. Just around lunchtime, when we were doing our final rehearsal walk, it suddenly started pouring, and the heavy wet cotton tent covering the seating area soon blew over and collapsed–while we were in there!

Where are ACEDRR or DAMN It! when you need them?

As soon as the rain let up and we had finished eating, it was “disaster response” time. We decided to ditch the tent cover (we had clouds blocking the sun anyway, so it wasn’t super hot) which meant that most of the graduating students had to be put to work. Seriously… we make them work hard for this degree!

Like I said, don't smile! (Or maybe they are so tired because they had to do a lot of disaster relief work in a short period of time.)

Near disaster aside, the rest of the day went quite smoothly. India’s Chief Election Commissioner was our guest at the event and he gave quite a good speech about the different ways in which our graduates can help promote democracy in India by ensuring that people are registered to vote and so on.

Are they smiling? Some people don't listen to instructions.

And, of course, it was great to see many of my former students in one place together….

Here’s an article about some of the things that Navin B Chawla had to say at our convocation.

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I was feeling a little bored, so I decided to use the zimmertwins site to give an example of the kinds of charming lunchtime discussions we occasionally have.

The ODF Campaign

The text moves by a bit too quickly, and I couldn’t get better sound. Maybe I’ll get around to uploading a different version with some rockin’ DWAB background music.

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Honestly, I had no idea where to start with this, and by the end of the day, I was still rather confused. This was the first time I heard the expression “grassroots democracy” and part of me was afraid that we were just using it because of the word “grassroots.” Representative democracy? Sure. I remember that from my political science course. The same goes for direct democracy. (I must say, though, that I was not too impressed with the liberal cut-and-paste from Wikipedia for the first couple of pages of the reading materials that were distributed. When I’m constantly battling with my students over getting them to properly cite information, it’s pretty frustrating when a colleague models bad behavior.)

The discussions today were difficult. Many of the “leads” for discussion really didn’t apply to most of the people in the sub-group I was in because we are a little bit more removed from direct field action. So, given the opportunity, I thought it would be good to try and clarify some of the concepts.

Here’s what I can understand. Grassroots democracy is still “unit” based but decisions are made at the level of the smallest unit (but not at the individual). Translate that to DHAN structures, and it would mean that the smallest unit is the self-help group. What is not clear to me, though, is how that is different from simply saying representative democracy at the group level. Perhaps the only real difference that I can see is that representative democracy does not have to be a “proxy” system where each voter is represented while grassroots democracy strives to make decisions based on consensus.

Which brings up another point: it seemed like many people I spoke to throughout the day misunderstood consensus. In particular, they seemed to confuse consensus with unanimous. I don’t remember where I read it, but I remember reading someone’s definition of consensus as “I guess that’s fine with me” rather than a convincing affirmative response. In other words, not all respondents would necessarily agree that the decision being made is the best decision, but they also wouldn’t have any problem or major complaint if that was the decision taken.

When trying to explain these concepts to others, I couldn’t help but be reminded of the start of Term 1 for PDM 10 students. One of the first things we do is select different committee members. The process is supposed to be a consensus democratic system–no elections allowed. For the PDM 10 students, when it came to selecting the class representative, one “candidate” (can you even have candidates if you’re not having an election?) essentially said “I want to be the class representative. I’m very stubborn, and you’re not going to be able to change my mind.”

Eventually “consensus” was achieved, but I think that, at that point, most people just didn’t want to get confrontational. In a way, it was the opposite of the “tyranny of the majority” that you hear when people are discussing direct democracy.

What I think is interesting about that event is that it really highlighted one of the “propositions” for grassroots democracy outlined in our reading materials: building social capital for promoting grassroots democracy. In the description of that proposition, values such as trust, mutuality, and solidarity were presented. To me, a nice summary of that proposition could be “people need to be ready for a democratic system.”

With my students, it is clear that they were not ready for a democratic system. Trust, mutuality, and solidarity were definitely not the words you’d use to describe them at that point because they barely knew each other. Whether or not they would end up with the same class representative today is irrelevant. What is more important for reflection is that we were supposed to be promoting a democratic process, but ultimately succumbed to a form of “tyranny” (of the individual who commanded the most “leadership” [or brattiness, depending on your perspective] among the group). I was actually more impressed with the grace with which the opponent backed down; to me, that was a good example of not just maturity, but also of what consensus means. (By the way, despite my disappointment with the democratic process for selecting the class representative, I think the class representative is doing a very good job.)

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I’ll start by being vague. The discussions were “interesting.”

But, they weren’t as interesting as they could have been. I found them to be quite predictable and somewhat tame.

“Alcoholism leads people into poverty.” “Daily wage earners are poor.” “Increasing savings reduces poverty.” “The poor are poor because they are poor.” (I hear that one all the time–I don’t totally understand it.) “Lack of education leads to poverty.”

Throughout the discussion (which took place in lots of small groups), there seemed to be a hidden force driving participants to try to answer a list of lead discussion questions with tidy compact answers–but that’s not really how life is, right?

But what I felt was really “interesting” was that the pair of charts that we were provided as a base for discussion seemed to go against some of the fundamental statements that are regularly made by many DHANites (and statements that are also part of the curriculum at the Academy). Yet, we seemed to glaze over this.

Here are some specifics: out of 10 reasons for falling into poverty, the major community-cited reasons for falling into poverty included “decreasing national/local prosperity” (22.3%) and “health/death shocks and natural disasters” (19.4%). Add in “job loss/unemployment” (7.4%), “family problems/expenses” (11.6%), and “functioning of local democracy” (2.6%) and you’ve passed the 50% mark by quite a bit. The least cited reason on the list is “gambling, alcohol, and drug addiction” which was cited by just 0.7% of the community as one of the top three reasons people are likely to fall into poverty.

Gambling, drugs, and alcohol are rarely cited as reasons for falling (click for more information)

The other chart was equally peculiar. When asked about the factors which contribute to the poor moving out of poverty, the single biggest factor (60.1%) was “individual initiative” in nonagriculture pursuits (entrepreneurship, new income sources, better jobs). Almost at the bottom of the list, a meager 0.3%, was “NGO assistance.” (“Luck”, by the way, got zero.)

Movers most frequently cite initiatives as reasons for their move out of poverty (click for more information)

But, I think that these charts are easily explained and don’t necessarily contradict what we’re saying as DHANites. For starters, is there, perhaps, a communication error? The note at the bottom of the chart clearly states that the percentages are of the “top three reasons cited” but doesn’t say anything about the rank of these results. In other words, since “decreasing national/local prosperity” found itself in the top three most often (22.3%), can we also conclude that the respondents would cite that as the number one reason? Not necessarily. Also, I would be curious to find out how the numbers changed if we looked at, instead, the top four reasons cited. Equally important is that DHAN’s big criticism of alcohol isn’t (or at least shouldn’t be) that alcohol leads people into poverty; it is more that alcohol consumption is more likely to keep people in poverty.

For the chart about coming out of poverty, along with the same logic as above, there is one more important consideration: I don’t think that most DHANites are in this line of work for the fame. And, our work is not about hand-holding people and helping them out of poverty. The work we do is more about enabling the poor to be able to show initiative, and I’m sure most people would agree that “initiative” without “ability” is unlikely to succeed. If I extend the analogy to my classroom, I like to think that my influence is somewhat invisible. I prompt my students and provoke them to think and along the way, I give them tips to improve their English. I don’t really want or expect them to turn around one day and say “Ananda is the reason I improved my English skills.” On the contrary, I would be elated if they saw their determination to succeed as the primary cause of their success. After all, what better reward is there to hard work than getting success?

Another reason that I found these pie-charts significant, and I wished we discussed this more, was that these were the outcomes of the voices of the community. At DHAN we value what people have to say, and, as such, I think it’s very important to at least try to understand the community perception of both how poverty occurs and of how people can emerge from such situations. That’s not to say that the community always knows what is best for them, but knowing this information will definitely have an impact on how successful we are in our work.

One final observation is the nature of these results themselves. For the factors for falling into poverty, a large percentage (almost 60%) of the “reasons for falling” are almost entirely out of the control of the individual. Alcohol consumption is within their control; it really doesn’t look good to blame yourself for your problems, and it probably isn’t accurate to do so anyway. I don’t know anyone who chooses a life of poverty.

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Some of you may have remembered my retreat report from last year in which I interviewed myself. This year, I decided to (predictably) do something different. And here’s what it was:

Here’s a PDF too….

So, why the title of this post? Well, the people in charge of compiling the retreat report books decided to take away all the pretty pictures, retype the text, and delete at least one important line from my report. I understand that it is not “standard format” but I did keep that in mind when I consciously decided to make it fit nicely onto a single sheet of A4 paper–I figured they could just print it out and insert it at the end of the rest of the reports or something, but I guess that would be asking too much.

Grrrr….

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Read on to find:

• Do Indians have a sense of humor AKA “Irony over the stinky river….”
• Marina Beach AKA “The sweet smelling ocean spray on Chennai’s shores….”
• Wetwo Brand AKA “Population Control, Indian Style….”
• Submission AKA “Quick, shhh! The Big-boss has just entered….”

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Sometimes, just when I begin to not have faith that Indians have a sense of humor, I run across something like this:

Near our house, there is an extremely foul river…. actually, it’s hard to even call it a river since it really seems to only flow when the cows go wading through the slush. Needless to say, it’s also a nice mosquito breeding ground too.

Anyway, a couple of months ago, the following two signs went up on either bank of the river:

Fragrances that make heads turn

There is something special in the air

And, just to give you a view of the river itself, in case you thought I was exaggerating….

All that I can say is that someone must have done really well in their marketing courses….

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Aah. Marina Beach. Great to go people watching. Good place to buy little silly plastic touristy stuff. Smell the fresh ocean breeze. Take a dip in the water to cool off.

Or should you?

Police Warning: Do not bath in sea danger to life

Well, it is a nice little spot to go and kill some time, especially when the sun is going down. The beach itself is extremely wide, and it’s the one public place where it seems like public displays of affection are not totally shocking! Plus, you get to see little fireworks displays when they make roast corn for you….

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