While researching for this article, I ran across a 2013 NYT piece on Pew’s finding that in 40% of U.S. families the sole or primary earner is the Mom. In a quarter of married households, the woman is the sole or primary wage earner.
I was surprised recently when I learned that almost every country has federal laws that require paid parental leave. Apparently, there are only four that do not. They are Suriname, Lesotho, Papua New Guinea and The United States. I’m including here the per capita Gross Domestic Product (GDP) of each country and their Gini coefficient, both of which seem relevant for considering the U.S. position on this issue.
Per Capita GDP: $16,623
Per Capita GDP: $1,091
Papua New Guinea
Per Capita GDP: $2,517
Per capita GDP: $57,220
The Gini coefficient is a mathematical measure of a nation’s wealth distribution. The lower the value, the more equitable their economy. Higher values indicate an economy that favors people who are already wealthy at the expense of the poor.
Here is a list of the eleven top ten developed countries with their Gini indexes. Canada and the U.S. are tied for #10. The graph compares the wealth distribution of these eleven countries by their standard deviations from the mean.
The newly elected Chairman of the Democratic National Committee made headlines Sunday by saying to a gathering in New Jersey that Republicans “don’t give a s**t about people.”
Political discorse in American is not designed to convince people to buy your plan. It’s designed to make you hate the people who haven’t bought it. And it works. People are not so motivated to go to the polls for an ideal that they think should be happening anyway. They will, however, proudly march there in self-defense. Perhaps we can’t do any better.
But what lights the gasoline is when we start diverting money for the sake of hate mongering. Also in the news on Sunday was reporting on Trumps submission to negotiations over efforts to avert a partial government shutdown at the end of next month. He proposes cutting $1.2 billion from the National Institutes of Health research grants, $1.5 billion from community development block grants and $500 million from transportation project grants. He’s leaving, however, the $3 billion he asked for previously to start his wall between the U.S. and Mexico.
Considering our everyday lives, divorced from the manipulative rhetoric we watch on TV, what should we care about more, cancer research and safe bridges, or immigrants and refugees, looking for a better life – and who are statistically less of a threat to us than people born here.
Sources: http://thehill.com/node/326876, https://goo.gl/CvlMGi, https://goo.gl/G5JpIz
One example of this preemption of local power was provisions to S.B. 279, slipped into the bill on the last day of 2015’s 76-day extended legislative session. Those provisions prevented city governments from passing higher minimum-wage laws, establishing affordable-housing mandates, or instituting rules about landlord-tenant relations. Other examples were wrestling from cities their control of local airports, waste and water systems, local redistricting, utilities and fracking. Fortunately, many of these legislative take-overs have been blocked by the Judicial Branch. But it all points to a political ideology that seems intent on stretching or breaking the founding principals of our government in order to further the interests of the campaign contributing class – the moneyed-elite.
It seems to me that the biggest part of our conversations among educators about how AI may affect us regards our own job security. I’m not worried about that. It won’t make teaching obsolete, in my opinion, in spite of the list below. We’ll just spend less time teaching stuff to our students and more time teaching how to use stuff – essentially, how to use information to solve problems and accomplish goals.
This was all brought back to mind when I ran across this FastCompany article today about brick laying machines and other jobs that AI/Automation may replace. Thinking more about the implications, especially to education, I sought out similar articles. Here’s a list of jobs that some have suggested can be done by machines.
|Retail Sales People||Security Guards||Farmers|
|Cattle Raisers||Pharmacists||Delivery Drivers|
|Telephone Sales People||Construction Workers||Accountants|
|Tour Guides||Mixologists & Bar Operators||Librarians|
|Hospital Administrators||Teachers||Truck Drivers|
|Taxi Drivers||Insurance Adjusters||Construction Workers|
|Customer Service Representatives|
I doubt that all chefs will be replaced nor that all factory work with be done by robots. The FastCompany article suggested that a brick laying machine would do what three humans can do in a day, but one person would be needed for the more nuanced work. But autonomous vehicles alone will likely mean the jobs of 5 million Americans, who currently make a living driving taxis, buses, vans, trucks and e-hailing vehicles. According to Lawrence Katz, a labor economist at Harvard, most of these drivers are not dissimilar to the millions of factory workers who have lost their jobs since 2000 – men without college degrees. Like drivers, manufacturing jobs did not go to China, but to Fanuc, Yaskawa, ABB and Kawasaki, the top producers of industrial robots. While factories were laying off millions of American workers, U.S. manufacturing output has actually grown by almost 18% since 2006.
What will be the consequences of this much unemployment, not to mention this much uncertainty. Nearly every article suggested that the effect on society will be HUGE and that the direction of policy makers will determine whether those consequences were bad or good.
Are we assuring ourselves of leadership that is creative enough to turn what seems horrible to most of us today into something that could actually be quite wonderful.
The sources: MSN, Quartz Media, Forbes, Futurism, The Guardian, LA Times, Fortune
Links to some of the articles
A friend of mine (not to mention world traveler, master educator, keynote speaker, master photographer) once said in one of his photography workshops, that there was a difference between TAKING a picture and MAKING a picture. It’s the reason for the title of this blog article. I struggled between “The Process..” and “A Process..” The rolled better though it is not the more accurate phrasing. Each photograph that I publish on Facebook, Instagram, Flickr or that I choose to print, is developed by a process that depends on the particular challenges it presents and the outcome that I am working toward. So the follow is the process for making a particular picture of a Great Blue Heron.
First is the original photo that I took while walking along the Mine Creek Trail, part of the Capital Area Greenway in Raleigh. This is one of about 20 photos taken as I followed the bird trying to get clear shots through the trees and other growth between us. Of those, I picked images to post process based on classic and also unique positions or postures. This one I liked because of the classic posture, but also the motion that the rising left leg implied.
Blue Heron 1
Blue Heron 2
This is a fine snapshot of a Great Blue Heron. However, I want to celebrate its Heron-ness, and there is too much distracting space in the photo that prevents the viewer to from subject. So I use Lightroom to crop the photo down to a 1×1 ratio, a square.
There is still too much activity around the bird that is distracting. It is mostly the leaves and pine needles. So I load the image into Photoshop and use the healing tool to remove them. Sounds like magic? The software takes a marked object find imagery near it that matches its surrounding and then stamps that over the object. I also used the healing tool to enlarge the surface of the moss.
Blue Heron 3
Blue Heron 4
In image four, I have used a blurring filter in Photoshop to make the background less interesting / less distracting. This probably seems strange since I blurred the entire image. But that’s going to be fixed by one of the coolest tools at the photographers fingertips.
Before blurring the image (4), I had made a copy of the clearer version. These two versions were layered on top of each other. Of course, the layers top is what I saw and would would be saved. To re-clarify the parts of the image that I did not want blurred, I created a mask. This is essentially an additional layer that is all white. The white doesn’t show. However, any part of the mask layer that is painted black essentially creates a hole through which the layer beneath shows. So using a black digital paint brush I painted the rocks, water, under wash of the bank and part of the moss. Then I carefully painted in the bird’s head and neck so that they would be detailed. What’s cool about this process is that if you make a mistake and blacken too much, then you simple fix your mistake by painting the problem white.
Blue Heron 5
Blue Heron 6
|In image six, I wanted to punch up parts of the image with more color. To do this, duplicated my working layer and then turned up the color saturation on the layer beneath.|
|7.||For seven, I asked the top, less colorful layer and then I painted through only the parts I wanted to increase the color for – the rocky sandbar and the bird.||
Blue Heron 7
Blue Heron 8
For image eight, I didn’t like the dark area at the top, so I cropped that out.
|9.||I’m close now, simply fixing small things that bother me, such as the unexplainable dark area in the top left corner. So for version nine, I used the healing tool to bring in some more moss. I also made a duplicate layer, increasing the exposure on the bottom layer, making it brighter. Finally, I used the masking tool to paint in the parts of the bird that I wanted to brighten up. I also decreased the color saturation after bringing it back into Lightroom, to make it a little more real.||
Blue Heron 9
Like so many things, you are never done. There is always something else you can do to make it better, especially when you come back to it hours or days later. But typically, I am done when the photo interests me, when I’ve come close to capturing what it was that inspired me to take the picture.
A few days ago my son posted this short statement on Facebook:
We weren’t ready for the Internet
He got some affirming comments and I just added,
Because of the Internet and other advances in telecommunications and broadcasting, we have become a world of nations divided by ideology instead of nations divided by borders. You can’t “storm the beaches” of the ideas that are contrary to yours.
This is actually something that I’ve thought about for quite a few years and the reason I spent the last 15 years trying to convince teachers to redefine literacy.
The fact is that we believe what we read on the Internet, because we were taught to believe what we read. Our schooling was purposely limited to textbooks, compelling (and not so compelling) lectures and library resources selected by librarians with advanced education. We try to limit our students’ learning to what is reliably accurate. As a result, our notion of what it is to be literate is limited. Can you “read and understand what someone, who you trust, has handed you to read.” ..and can you answer questions about it on a test?
In my efforts, I respelled the 3 Rs with 3 Es. Instead of teaching children to read, we should be helping them learn to Expose what is true. To expose what is true, you must learn to read it. But being able to search for, find and synthesize the information, and select that which is most appropriate to your situation, has become just as critical as being able to read it.
I use to suggest to teachers that they should, at every occasion, ask their students, “How do you know that’s true?” I added that students should be free to ask their teachers, “How do you know that’s true?” I suspect that if political candidates were regularly asked, “How do you know that?” and we demanded answers, our leadership might be quite different.
The other Es were:
- Learning to Employ information, instead just teaching students to calculate numbers
- Learning to Express Ideas Compelling, instead of just teaching students to write a coherent paragraph
- There was a 4th E – exposing, employing and expressing information with respect for and devotion to what is true, Ethically using information to answer question, solve problems and accomplish goals.
The official name was WFL-26, or Wetter-Funkgerät Land-26. It was an automated weather station installed in Northern Laborador in 1943 and labeled as the property of the “Canadian Weather Service.” Fact: There was no “Canadian Weather Service” in 1943.
The weather station was established by a team from the German submarine U-537, anchored in Martin Bay. During World War II, Germany lost access to international weather data, and needed information about conditions over Russia and Northern Europe for air operations. To help disguise the installation, they labeled it as Canadian and scatter American cigarette packs around the area. Today, the only Wikipedia article about the site, Hutton Peninsula, is in it’s Swedish version – a pretty good place to hide a covert weather station.
The weather station was not discovered until a historian for equipments manufacturers, Siemens Corporation, found its description in corporate archives.
WFL-26 represented the only German armed military operation carried out on the mainland of North America of World War II.
By the way, WILT stands for “What I Learned Today.”
Budanovic, N. (2016, April 3). The Secret Nazi German Weather Station In Canada, Discovered 38 Years After It Was Built – Page 2 of 2 [Web log post]. Retrieved from https://www.warhistoryonline.com/featured/weather-station-kurt.html/2
Winter, J. (2013, March 24). Weather Station Kurt [Web log post]. Retrieved from https://xefer.com/2013/03/kurt
Political scientists, Andrew Reynolds (UNC) and Jorgen Elklit (Aarhus University, Denmark), have designed a method for evaluating the democratic quality of elections around the world. Based on their work in setting up elections in Afghanistan, Burma, Egypt, Lebanon, South Africa, Sudan and Yemen, their method has been adopted by the Electoral Integrity Project, who have used it to measure 213 elections in 153 countries.
A North Carolinian, Reynolds was unpleasantly surprised to find that his own state rated poorly on the democracy scale — on the level of Cuba, Indonesia and Sierra Leone. It’s measures of legal framework and voter registration ranked NC with Iran and Venezuela.
North Carolina’s districting for legislative elections was the worse in the U.S. – and worse than any other country — worse in the world and worse ever recorded.
According to a compilation of all indicators, North Carolina’s government can no longer be classified as a full democracy.
We should hang our heads in shame, that we have allowed this to happen.
Reynolds, A. (2016, December 22). North Carolina is no longer classified as a democracy. News & Observer [Raleigh].http://www.newsobserver.com/opinion/op-ed/article122593759.html
|“Playing with data is as fun as playing with Legos”|
Even though I suspect that most Americans, Republican and Democrat, believe in mostly the same things. The political gap seems to have much to do with your neighborhood – that is to say, how far you live from your neighbors.
I did a little figuring with the population density of each state and the percent of votes cast by its residents for Donald Trump. The correlation coefficient (yes, I’m college educated) was -.46, which apparently is a moderate downhill or negative relationship (see chart #1). In other words, the higher the population density (urban) the less likely you and your neighbors were to vote for Trump. The lower the density (rural), the more likelihood of Trump votes in your neighborhood.
But this gap seems to have been magnified by the U.S. Constitution, as the document describes the Electoral College. North Dakota, 47th in density ranking, cast 216,133 votes for Trump. That amounted to only 72,044 votes for each of the state’s 3 electoral votes for the Republican candidate. In Massachusetts, the 3rd most densely populated state, it took over 100,000 more votes for Clinton (178,615) to earn one of the state’s 7 electoral votes for the Democrat (see chart #2).
What surprises and disturbs me is the education gap. The graph below, from Pew Research Center, indicates that among all voters, those with college degrees or more voted for Hillary Clinton by 9 points, while voters with some college or less chose Donald Trump by 8 points. The education gap widens when looking at white voters only, a gap of 35 points.1
There are many ways to read meaning into this, and I’m going to be thinking pretty hard about it. But we might assume that free college education, as provided in many European countries, is pretty much off the table here at home.
I woke up early again this morning, all worried about this upcoming election. I started mucking around my old 2009 Macbook Pro and found the Federal Elections Commission web site and their downloadable files with details on campaign contributors by state. Data makes my skin tingle.
So I downloaded all 27 megabytes of North Carolina data (4/15/15-10/31/15), loaded the csv file into Open Office Calc and started tinkering. My seven year old MacBook was huffin’ and puffin’.
One of the questions that got my mind going this morning was the money that is so essential to political campaigns today. To date, the 2016 presidential campaigns have generated $1,000,058,201 from individual donations alone. More to the point of my sleeplessness was, “Who’s paying for these campaigns?” or “Who’s buying our government?”
So I used Calc to parse the 133,100 contributions by range categories: less than $100, $100 to $999 and more than $1000 and more. It shouldn’t be a surprise that more North Carolinians were donating less than $100 than the other two combined.
What struck me as especially critical to my worries was the total amounts of campaign money generated from each category. Look at the data and graph.
|Donations||Number of Contributors||Total Amount Contributed|
|Less than $100||101,388||$2,737,190.87|
|Between $100 & $1000||28,427||$5,454,833.10|
|More than $1000||3,285||$6,226,996.52|
What’s wrong with this picture? Well, let’s say you are an incumbent, or even a challenger. With so much money out there, constituting a elections industry, the only way that you can keep your seat, or oust the incumbant is with a lot of money.
Where do you go for the money?
Look at the diagram again. Where’s the money? To get elected, you have to convince rich people and corporations to contribute. What will they want from you for that money?
It’s their government. Not ours.
keep looking »