Not sure why but for some reason over lunch I got interested in old labor songs. This one was particularly bleak. Apparently, it is intended to be sung over “My Bonnie Lies Over The Ocean.” As our administration erodes labor and environmental protections for the inexplicable sake of bringing back coal mining, it pays to have a look back at how bad it really was.
Song: My Children are Seven in Number
Lyrics: Eleanor Kellogg(1)
Music: to the tune of “My Bonnie Lies Over the Ocean”
My children are seven in number,
We have to sleep four in a bed;
I’m striking with my fellow workers.
To get them more clothes and more bread.
Shoes, shoes, we’re striking for pairs of shoes,
Shoes, shoes, we’re striking for pairs of shoes.
Pellagra(3) is cramping my stomach,
My wife is sick with TB(4);
My babies are starving for sweet milk,
Oh, there as so much sickness for me.
Milk, milk, we’re striking for gallons of milk,
Milk, milk, we’re striking for gallons of milk.
I’m needing a shave and a haircut,
But barbers I cannot afford;
My wife cannot wash without soapsuds,
And she had to borrow a board.
This song was originally posted on protestsonglyrics.net
Soap, soap, we’re striking for bars of soap,
Soap, soap, we’re striking for bars of soap.
My house is a shack on the hillside,
Its doors are unpainted and bare;
I haven’t a screen to my windows,
And carbide cans do for a chair.
Homes, homes, we’re striking for better homes,
Homes, homes, we’re striking for better homes.
They shot Barney Graham(5) our leader,
His spirit abides with us still;
The spirit of strength for justice,
No bullets have power to kill.
This song was originally posted on protestsonglyrics.net
Barney, Barney, we’re thinking of you today,
Barney, Barney, we’re thinking of you today.
Oh, miners, go on with the union,
Oh, miners, go on with the fight;
For we’re in the struggle for justice,
And we’re in the struggle for right.
Justice, justice, we’re striking for justice for all,
Justice, justice, we’re striking for justice for all.
We are entering into one of the most chaotic chapters of modern history, though the geographic space of this chaos is smaller than it has ever been. While most countries are experiencing less terror, Mid-Eastern terrorist have never been busier or more successful.
I downloaded data from the Global Terrorism Database, which comprises more then 125,000 individual acts of terror and found that, since 2010, the number of weekly terror events when from somewhere around 10 to more than 40, and the trend doesn’t look like it’s ending anytime soon.
Moreover, while terror events are becoming more frequent, they are becoming more and more unpredictable.
While the world was shocked over Charlie Hebdoe, the troubling scale up in the number of terror events seems to have mostly gone unnoticed. Terrorists strike Islamic countries far more than they do France, and kill more than just cartoonists and policemen.
It is unproductive to view all terror groups and even acts of terror as being the same. Terror has turned into a morass of competing groups, with differing political aims and the loose nature of Al Qaeda has led to an outsourcing of terror by any local thug with a gun.
It is also unproductive to view Mid-East terror as simply restricted to the angry victims of drone attacks. Islamic terrorism has a deep history with roots going back decades, a history which seems to be widely ignored. It is also important to note that ISIS’ membership consists of a frighteningly large number of Westerners and a careful watch of their videos reveals that English, rather than Arabic, is a common language among its followers.
Where will this go? No one knows, but Charlie Hebdoe will be just a blip on the pattern on terror.
African countries are blessed with ample cropland and resources, but suffer from crippling and unforgivable levels of poverty, have some of the shortest lifespans on the planet and the highest rates of infant mortality in the world. Meanwhile, Japan, Korea, Sweden, Switzerland and Singapore are wholly the opposite, yet mostly lacking in everything that Africa has. Clearly, the picture is more complicated than merely having access to a natural resources.
However, within countries, the picture might be different. African countries are complex and diverse places. Poverty is often confined to the most unproductive regions, areas with poor soils, poor rainfalls or dangerous terrains.
I was just working with some socio-economic data from one of our field sites, and noticed some interesting patterns (note the map up top). In Kwale, a small area along the Coast, socio-economic levels vary widely, but neighbors tend to be like neighbors and patterns of socio-economic clustering emerge.
Note that the poorest of the poor are concentrated to an area in the middle, which I know to be extremely dry, difficult to get to, difficult to farm and generally tough to live in.
I tried to see if socio-economic status (as measured through a composite material wealth index a la Filmer and Pritchett but using multiple correspondence analysis rather than PCA) was related to any environmental variables that I might have data for.
I fit a generalized additive model using the continuous measure of of wealth from the MCA as an outcome. Knowing that very few things in nature or human societies are linear, I also applied smoothing to the predictors to relax these assumptions. The results can be seen in the plot at the bottom.
A few interesting things came out. While it is hard to tell much about the poorest of the poor, we can tell something about the most wealthy. The richest in this poor area, tend to live in areas with the richest vegetation (possibly representing water), a high altitude (low temperature), high relief (no standing water) and in locations distant from a wildlife reserve (far from annoying and dangerous wildlife).
I’m not sure the wildlife reserve is meaningful (unless the reserve was an area undesirable for human habitation to begin with), but the others might be and represent a trend seen in other Sub-Saharan contexts. Areas without malarious swamps and ample farm land tend to do the best. Central Province, one of the most developed areas of Kenya, would be an example.
But the question has to be, does a harsh environment doom people to poverty, or do people self shuffle into and compete for access to more favorable areas? Is environmentally determined poverty (or wealth) an accident of birth, or the result of competitive selection?
Alright, back to work. Oh wait, this is my work. Well….