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I did get a plausible-sounding explanation of the design process from Tom Bohan, who heads up Menupages, the fantastic site that lists menus of restaurants in several large cities. "Say you're a designer and you've got to demo a site you've spent two months creating," Bohan explains. "Your client is someone in their 50s who runs a restaurant but is not very in tune with technology. What's going to impress them more: Something with music and moving images, something that looks very fancy to someone who doesn't know about optimizing the Web for consumer use, or if you show them a bare-bones site that just lists all the information? I bet it would be the former—they would think it's great and money well spent."

The vanguard is already here in Siri and Google Now.  Each of these represents a type of agent that knows a few things about us.  Google Now will tell you, without your asking, the time it takes to get home from work.  Siri and Google Now both will take your voice input and perform actions that would normally be fairly complicated through a series of interfaces.

Not all of us have access to complex and robust voice recognition libraries and a network of camera-equipped cars.  Many of us are, however, in a position to collect or analyze large sets of data.

App collects data, sends output to wearable tech.

“Universal” background checks won’t work. The fact is we have them now. Anytime a law-abiding citizen purchases a gun from a brick-and-mortar or online retailer, pawn shop owner or private dealer—essentially any licensed dealer who sells more than a handful of firearms per month—he or she must submit to a background examination via the National Instant Check System.

Even as creating engaging experiences on the web is mandatory, the metric called Engagement is simply an excuse for an unwillingness to sit down and identify why a site exists.

Each business is unique and each website is trying to accomplish something unique.

It is nearly impossible to define engagement in a standard way that can be applied across the board.

At the heart of it engagement tries to measure something deeply qualitative.

One of my personal golden rules is that a metric should be instantly useful. This one is not.

Most of all engagement is a proxy for measuring an outcome from a website.

In Summary: The reason engagement has not caught on like wild fire (except in white papers and analyst reports and pundit posts) is that it is a "heart" metric we are trying to measure with "head" data, and engagement is such a utterly unique feeling for each website that it will almost always have a unique definition for each and every website.

Step One: Define why your website exists. What is its purpose? Not a five hundred word essay, rather in fifteen words or less. If it helps complete this statement: "When the crap hits the fan the only purpose of my website is to ……….".

Step Two: If you did a great job with it then the above statement contains the critical few metrics (three or less) that will identify exactly how you can measure if your website is successful at delivering against its purpose.

Step Three: If you have a ecommerce website then revenue or conversion is probably one of your critical few. But one of the critical few is what your senior management might call engagement. Work hard to define exactly what that metric is (see below for ideas).

"Are you engaged with us?"

Likelihood to recommend website

Use primary market research

Customer retention over time

# of Visits per Unique Visits, Recency of Unique Visitors

In Summary : When most people measure "engagement" they have not done due diligence to identify what success means for their online presence. In absence of that hard work they fall into measuring engagement, and then measure something that is hard to action or something that will rarely improve the bottomline. Avoid this at all costs. Think very carefully about what you are measuring if you do measure engagement. If engagement to you is repeat visitors by visitors then call it Visit Frequency, don't call it engagement. Don't sexify, simplify! :) If you want to measure "engagement" then think of new and more interesting ways to measure that (see list above). Engagement at its core a qualitative feeling. It really hard to measure via pure clickstream (web analytics data). Think different.

Visitor Loyalty: During the reporting time period how often do "people" ("visitors") visit my website?

For example you update your website ten times each month. If you have 100% loyal visitor base then they should be visiting your website ten times each month. Are they? What's your number? Is it going up over time?

Action: 1) Identify a goal for your non-ecommerce website for the # of visits you expect from the traffic to your website in a given time period (say week, month etc). 2) Measure reality using above report. 3) Compare your performance over time to ensure you are making progress, or potentially not as in my case…

Recency: How long has it been since a visitor last visited your website? Sounds confusing? Don't worry it is cool (it even has a psychedelic border! :)……

As would be the case for a jobs site. Or craigslist. Or any website that wants lots lots of repeat visits. Using this simple report you can now see how you are doing when it comes to the distribution of visitors in terms of their propensity to visit your site.

Length of Visit: During the reporting period what is the quality of visit as represented by length of a visitor session in seconds.

But it has always been frustrating to me how hard it is to get away from the average and measure the distribution of the visits to check if the average time on site is 50 seconds because one person visited for one second and the other person for 100 seconds. The average hides so much. Here's a better alternative……

Ain't that better? I think so. So many things jump out at me, but notice that either I lose 'em right away or if some how I can suck them in for one minute then they tend to stay for a long time. Hurray! I have a better idea of how to interact with my visitors.

1) Identify what the distribution is for your website for length of visits. 2) Think of creative ways to engage traffic – what can I do to keep you for sixty seconds because after that you are mine! 3) Should I start charging more for ads on my site – if I have 'em – after 60 seconds? 4) If you are a support website then should you be embarrassed if 20% of your audience was on the site for more than ten minutes!

Depth of Visit: During a given time period what is the distribution of number of pages in each visit to the website.

You are used to seeing average page views per visitors, above is something that is a lot more helpful. I was also able to get this exact metric from my indextools implementation…..

Action: There has been so much said about this already so I'll spare your the pain. You can easily imagine how wonderful and fantastic this data is as you go about analyzing experience of your customers (and so much more powerful, a million times more, than average page views per visitor!).

Socialize them to your key stake holders and decision makers to make the realize what is really happening on your website.

Absolutely positively work with your leadership to create goals and then measure against goals over time

Segment the data! For Visitor Loyalty or Length of Visit what are the most important acquisition sources? What are the keywords that drive valuable segments of traffic to the website?

In the remaining 58% of organizations surveyed, high performers were the most engaged, or engagement scores were about equal among the employees. In the rarest cases, Murphy said, the middle performers were the most engaged.  That segment of the workforce—the employees who are neither superstars nor slackers—tends to be ignored by managers, he said.

Low performers were also more likely than the other two groups to recommend their company as a “great organization to work for.” And in many cases, they didn’t even realize they were low performers. When asked whether the employees at the company “all live up to the same standards,” low performers were far more likely to agree with the statement than their higher-achieving counterparts.

First, the inequality of personal well-being is sharply down over the past hundred years and perhaps over the past twenty years as well.

by broad historical standards, what I share with Bill Gates is far more significant than what I don’t share with him.

Compare these circumstances to those of 1911, a century ago. Even in the wealthier countries, the average person had little formal education, worked six days a week or more, often at hard physical labor, never took vacations, and could not access most of the world’s culture.

when average people read about or see income inequality, they don’t feel the moral outrage that radiates from the more passionate egalitarian quarters of society. Instead, they think their lives are pretty good and that they either earned through hard work or lucked into a healthy share of the American dream.

There’s a great deal of hostility toward various government bailouts, but the idea of “undeserving” recipients is the key factor in those feelings. Resentment against Wall Street gamesters hasn’t spilled over much into resentment against the wealthy more generally.

their constituents bear no animus toward rich people, only toward undeservedly rich people.

in the United States, most economic resentment is not directed toward billionaires or high-roller financiers—not even corrupt ones. It’s directed at the guy down the hall who got a bigger raise.

The high status of the wealthy in America, or for that matter the high status of celebrities, seems to bother our intellectual class most. That class composes a very small group, however

Income inequality has been rising in the United States, especially at the very top.

income growth at the very top

greater inequality throughout the distribution

When it comes to the first trend, the share of pre-tax income earned by the richest 1 percent of earners has increased from about 8 percent in 1974 to more than 18 percent in 2007. Furthermore, the richest 0.01 percent (the 15,000 or so richest families) had a share of less than 1 percent in 1974 but more than 6 percent of national income in 2007. As noted, those figures are from pre-tax income, so don’t look to the George W. Bush tax cuts to explain the pattern. Furthermore, these gains have been sustained and have evolved over many years, rather than coming in one or two small bursts between 1974 and today.1

Caution is in order, but the overall trend seems robust. Similar broad patterns are indicated by different sources, such as studies of executive compensation. Anecdotal observation suggests extreme and unprecedented returns earned by investment bankers, fired CEOs, J.K. Rowling and Tiger Woods.

But that slower wage growth has afflicted large numbers of Americans, and it is conceptually distinct from the higher relative share of top income earners. For instance, if you take the 1979–2005 period, the average incomes of the bottom fifth of households increased only 6 percent while the incomes of the middle quintile rose by 21 percent. That’s a widening of the spread of incomes, but it’s not so drastic compared to the explosive gains at the very top.

The broader change in income distribution, the one occurring beneath the very top earners, can be deconstructed in a manner that makes nearly all of it look harmless. For instance, there is usually greater inequality of income among both older people and the more highly educated, if only because there is more time and more room for fortunes to vary.

Economist Thomas Lemieux at the University of British Columbia estimates that these demographic effects explain three-quarters of the observed rise in income inequality for men, and even more for women.2

Attacking the problem from a different angle, other economists are challenging whether there is much growth in inequality at all below the super-rich. For instance, real incomes are measured using a common price index, yet poorer people are more likely to shop at discount outlets like Wal-Mart, which have seen big price drops over the past twenty years.3 Once we take this behavior into account, it is unclear whether the real income gaps between the poor and middle class have been widening much at all.

And so we come again to the gains of the top earners, clearly the big story told by the data.

If wages go up, that person will respond by seeking less work or by working less hard or less often. That person simply wants to “get by” in terms of absolute earning power in order to experience other gains in the form of leisure—whether spending time with friends and family, walking in the woods and so on. Luck aside, that person’s income will never rise much above the threshold.

It’s not obvious what causes the percentage of threshold earners to rise or fall, but it seems reasonable to suppose that the more single-occupancy households there are, the more threshold earners there will be, since a major incentive for earning money is to use it to take care of other people with whom one lives.

The funny thing is this: For years, many cultural critics in and of the United States have been telling us that Americans should behave more like threshold earners. We should be less harried, more interested in nurturing friendships, and more interested in the non-commercial sphere of life. That may well be good advice.

Their data do not comprise the entire U.S. population, but from partial financial records they find a very strong role for the financial sector in driving the trend toward income concentration at the top.

The authors also relate that they shared their estimates with a former U.S. Secretary of the Treasury, one who also has a Wall Street background. He thought their estimates of earnings in the financial sector were, if anything, understated.

Finance aside, there isn’t much of a story of market failure here, even if we don’t find the results aesthetically appealing.

When it comes to professional athletes and celebrities, there isn’t much of a mystery as to what has happened.

We may or may not wish to tax the wealthy, including wealthy celebrities, at higher rates, but there is no need to “cure” the structural causes of higher celebrity incomes.

Most of the time investors will do well by this strategy, since big, unexpected moves are outliers by definition. Traders will earn above-average returns in good times. In bad times they won’t suffer fully when catastrophic returns come in, as sooner or later is bound to happen, because the downside of these bets is partly socialized onto the Treasury, the Federal Reserve and, of course, the taxpayers and the unemployed.

Does that kind of pattern sound familiar? It happens in finance, too. Betting against a big decline in home prices is analogous to betting against the Wizards. Every now and then such a bet will blow up in your face, though in most years that trading activity will generate above-average profits and big bonuses for the traders and CEOs. To this mix we can add the fact that many money managers are investing other people’s money.

And let’s say the whole thing does blow up in your face? What’s the worst that can happen? Your bosses fire you, but you will still have millions in the bank and that MBA from Harvard or Wharton.

They gain on the upside, while the downside, past the point of bankruptcy, is borne by the firm’s creditors.

In short, there is an unholy dynamic of short-term trading and investing, backed up by bailouts and risk reduction from the government and the Federal Reserve. This is not good.

But more immediate and more important, it means that banks take far too many risks and go way out on a limb, often in correlated fashion. When their bets turn sour, as they did in 2007–09, everyone else pays the price.

The more one studies financial theory, the more one realizes how many different ways there are to construct a “going short on volatility” investment position.

In some cases, traders may not even know they are going short on volatility. They just do what they have seen others do. Their peers who try such strategies very often have Jaguars and homes in the Hamptons. What’s not to like?

If you’re wondering, right before the Great Depression of the 1930s, bank profits and finance-related earnings were also especially high.8

The moving-first phenomenon sums to a “winner-take-all” market. Only some relatively small number of traders, sometimes just one trader, can be first. Those who are first will make far more than those who are fourth or fifth.

Since gains are concentrated among the early winners, and the closeness of the runner-ups doesn’t so much matter for income distribution, asset-market trading thus encourages the ongoing concentration of wealth. Many investors make lots of mistakes and lose their money, but each year brings a new bunch of projects that can turn the early investors and traders into very wealthy individuals.

Still, every now and then Goldman will go bust, or would go bust if not for government bailouts. But the odds are in any given year that it won’t because of the advantages it and other big banks have.

In any given year, this practice may seem tolerable—didn’t the bank earn the money fair and square by a series of fairly normal looking trades?

It remains to be seen whether the new financial regulation bill signed into law this past summer will help.

The bill does have positive features.

What about controlling bank risk-taking directly with tight government oversight? That is not practical. There are more ways for banks to take risks than even knowledgeable regulators can possibly control

It’s also not clear how well regulators can identify risky assets.

It’s no longer obvious that the system is stable at a macro level, and extreme income inequality at the top has been one result of that imbalance. Income inequality is a symptom, however, rather than a cause of the real problem.

Once a financial crisis arrives, politicians will seek to limit the damage, and that means they will bail out major financial institutions.

One worry is that banks are currently undercapitalized and will seek out or create a new bubble within the next few years, again pursuing the upside risk without so much equity to lose.

A second perspective is that banks are sufficiently chastened for the time being but that economic turmoil in Europe and China has not yet played itself out, so perhaps we still have seen only the early stages of what will prove to be an even bigger international financial crisis.

A third view is perhaps most likely. We probably don’t have any solution to the hazards created by our financial sector, not because plutocrats are preventing our political system from adopting appropriate remedies, but because we don’t know what those remedies are.

They are sitting on money rather than lending it out. The biggest risk today is how few parties will take risks, and, in part, the caution of banks is driving our current protracted economic slowdown. According to this view, the long run will bring another financial crisis once moods pick up and external scrutiny weakens, but that day of reckoning is still some ways off.

This unavoidable tradeoff between false positive and false negative errors is a well-known property of all statistical-prediction applications. Circling back to check all the factors involved in the problem might have helped the authors avoid this mistake.

How could an experienced journalist and a widely respected researcher slip up in so many ways? Some possible answers to this question offer insights for the would-be pop-statistics writer.

Cases in which forgeries that intuitively appear real but later are discovered through analysis to be frauds are fairly common in the art world.

Intuition means different things to different people. To some it refers to a sudden flash of insight, or even the spiritual experience of discovering a previously hidden truth.

The idea that hunches can outperform reason is neither unique nor original to Malcolm Gladwell, of course. Most students and professors have long believed that, when in doubt, test-takers should stick with their first answers and "go with their gut." But data show that test-takers are more than twice as likely to change an incorrect answer to a correct one than vice versa.

The finding that people fail to notice unexpected events when their attention is otherwise engaged is interesting. What is doubly intriguing is the mismatch between what we notice and what we think we will notice.

If you believe you will notice unexpected events regardless of how much of your attention is devoted to other tasks, you won't be vigilant enough for possible risks.

In the vast majority of cases in which DNA evidence exonerated a death-row inmate, the original conviction was based largely on the testimony of a confident eyewitness with a vivid memory of the crime. Jurors (and everyone else) tend to intuitively trust that when people are certain, they are likely to be right.

To determine whether two events are truly associated, we must consider how frequently each one occurs by itself, and how frequently they occur together. With just one or a few anecdotes, that's impossible, so it pays to err on the side of caution when inferring the existence of an association from a small number of examples.

But more than a dozen large-scale epidemiological studies, involving hundreds of thousands of subjects, have shown that children who were vaccinated are no more likely to be diagnosed with autism than are children who were not vaccinated. In other words, there is no association between vaccination and autism. And in the absence of an association, there cannot be a causal link.

The kouros example is effective because it capitalizes on our tendency to generalize from a single positive association, leading to the conclusion that intuition trumps reason. But in this case, a bit of thought would show that conclusion to be unlikely, even within the confined realm of art fakery. Think about how often experts throughout history have been duped by forgers because intuition told them that they were looking at the real thing. It is ironic that Gladwell (knowingly or not) exploits one of the greatest weaknesses of intuition—our tendency to blithely infer cause from anecdotes—in making his case for intuition's extraordinary power.

People will be puzzled at what they find when they open the time capsule, said Rauber. “In 25 years people will be astonished to see how little time must pass to render data carriers unusable because they break or because you don’t have the devices anymore,” he said. “The second shock will probably be what fraction of the objects we can’t use or access in 25 years and that’s hard to predict.”

15 of the 25 worst mass shootings in the last 50 years took place in the United States. Time has the full list here. In second place is Finland, with two entries.

Lots of guns don’t necessarily mean lots of shootings, as you can see in Israel and Switzerland.*

*Correction: The info is out-of-date, if not completely wrong. Israel and Switzerland have tightened their gun laws substantially, and now pursue an entirely different approach than the United States. More details here. I apologize for the error.

Of the 11 deadliest shootings in the US, five have happened from 2007 onward.

Kieran Healy, a sociologist at Duke University, made this graph of “deaths due to assault” in the United States and other developed countries. We are a clear outlier.

“The most striking features of the data are (1) how much more violent the U.S. is than other OECD countries (except possibly Estonia and Mexico, not shown here), and (2) the degree of change—and recently, decline—there has been in the U.S. time series considered by itself.”

In a subsequent post, Healy drilled further into the numbers and looked at deaths due to assault in different regions of the country. Just as the United States is a clear outlier in the international context, the South is a clear outlier in the national context:

“For all the attention given to America’s culture of guns, ownership of firearms is at or near all-time lows,” writes political scientist Patrick Egan. The decline is most evident on the General Social Survey, though it also shows up on polling from Gallup, as you can see on this graph:

The Harvard Injury Control Research Center assessed the literature on guns and homicide and found that there’s substantial evidence that indicates more guns means more murders. This holds true whether you’re looking at different countries or different states. Citations here.

Higher populations, more stress, more immigrants, and more mental illness were not correlated with more deaths from gun violence. But one thing he found was, perhaps, perfectly predictable: States with tighter gun control laws appear to have fewer gun-related deaths. The disclaimer here is that correlation is not causation. But correlations can be suggestive:

Since 1990, Gallup has been asking Americans whether they think gun control laws should be stricter. The answer, increasingly, is that they don’t. “The percentage in favor of making the laws governing the sale of firearms ‘more strict’ fell from 78% in 1990 to 62% in 1995, and 51% in 2007,” reports Gallup. “In the most recent reading, Gallup in 2010 found 44% in favor of stricter laws. In fact, in 2009 and again last year, the slight majority said gun laws should either remain the same or be made less strict.”

An August CNN/ORC poll asked respondents whether they favor or oppose a number of specific policies to restrict gun ownership. And when you drill down to that level, many policies, including banning the manufacture and possession of semi-automatic rifles, are popular.

Shootings don’t tend to substantially affect views on gun control. That, at least, is what the Pew Research Center found:

Dark energy, a mysterious force thought to be responsible for accelerating the expansion of the Universe, accounts for less than previously thought.

The Planck data also set a new value for the rate at which the Universe is expanding today, known as the Hubble constant. At 67.15 kilometers per second per megaparsec, this is significantly less than the current standard value in astronomy. The data imply that the age of the Universe is 13.82 billion years.

oldest light in our Universe, imprinted on the sky when it was just 380 000 years old.

This cosmic microwave background (CMB) — shows tiny temperature fluctuations that correspond to regions of slightly different densities at very early times, representing the seeds of all future structure: the stars and galaxies of today.

According to the standard model of cosmology, the fluctuations arose immediately after the Big Bang and were stretched to cosmologically large scales during a brief period of accelerated expansion known as inflation.

The asymmetry and the cold spot had already been hinted at with Planck’s predecessor, NASA’s WMAP mission, but were largely ignored because of lingering doubts about their cosmic origin.

Begin the process by downloading Fancy Cache (~2MB) software. After installation and starting up the program, the software interface would list out the storage mediums connected to your pc. Select your SSD from the list and configure a cache size for it (Refer the image). The cache size may be set to suit your needs. We’ve allocated currently 3192 MB of RAM as the cache and the defer caching has been also set to enabled. After setting the cache size for your SSD and related options on fancy cache, click Start Caching and you’re ready with the caching setup for your SSD.

The TRIM Command The very first step after setting up an SSD is to enable the TRIM Command in Windows. Windows 8 has the TRIM command already enabled if you are using an SSD. It is important to have the TRIM command enabled on your system as it helps to maintain the SSD’s life by optimizing the garbage collection in windows.

3) Enabling TRIM Command to Optimize SSD From the Start Menu, type CMD in the search box. Right click the command prompt icon and choose Run as Administrator. Now type fsutil behavior query disabledeletenotify and press Enter. If its shows you disabledeletenotify = 0, the TRIM command is enabled in windows and you don’t have to make any modifications. If not, it would display, disabledeletenotify = 1. If TRIM is not enabled, type fsutil behavior set disabledeletenotify 0 The TRIM Command would now be set to enabled.

Drive defragmentation helps in organizing the fragmented data and helps in improving the performance of a hard disk. But drive defragmentation doesn’t speed up SSD, as these drives doesn’t contain any rotating parts and defragmenting a drive would involve the transfer of data i.e. more read/write cycles which actually shortens the life span of the SSD. So, its always good to disable drive defragmentation in windows.

So its better to disable them if you have 4GB or less memory. If you have plenty of RAM installed, enabling them might give an iota of boost and would speed up SSD performance.

Bring up the Registry Editor in Windows by Typing regedit on RUN Window (WIN + R) and pressing Enter. Now navigate to “HKEY_LOCAL_MACHINESYSTEMCurrentControlSetControlSessionManagerMemory ManagementPrefetchParameters“ You’ll see Enable Prefetcher and Enable Superfetch options being list out on the right window pane. Double click each and set the value from 3 to 0. Now restart your system for the changes to be enabled.

SSDs are speedier than hard drives and have an access time of 0.1 milli second. Drive indexing results in increasing the number of file write operations doesn’t really speed up SSD and its better to have it turned off. Open My Computer and just right Click Your SSD and choose properties. Just untick the Allow files on this drive to have contents indexed in addition to file properties option. You’ll be prompted with warnings just after clicking Apply. Proceed by pressing Ignore All and it would show you a processing window and would take a few minutes for the changes to be applied.

Google’s founding ideas came from Page and Brin, world-class developers in their own right. In the late 1990s they built PageRank, an algorithm for returning the most relevant results to a given search query. The focus on relevance put Google on a course to surpass Yahoo, AltaVista, and the day’s other leading search engines. But as the upstart grew in popularity, it faced a tremendous computing challenge. “We couldn’t deploy machines fast enough” to keep up with demand, Dean recalls.

Ghemawat helped lead a team that built the Google File System, which allowed for huge files to be efficiently distributed across thousands of cheap servers. Then Dean and Ghemawat developed a programming tool called MapReduce that allowed developers to efficiently process gargantuan data sets with those machines working in parallel.

Most airstrikes from these aircraft use Hellfire missiles, which cause less collateral damage.

The modern battlefield -- and the ancient as well -- has been marked by anonymity. The enemy was not a distinct individual but an army, and the killing of soldiers in an enemy army did not carry with it any sense of personal culpability. In general, no individual soldier was selected for special attention, and his death was not an act of punishment. He was killed because of his membership in an army and not because of any specific action he might have carried out.

Open insignia is fundamental to the rules of war. It was instituted after the Franco-Prussian war, when French snipers dressed as civilians fired on Germans. It was viewed that the snipers had endangered civilians because it was a soldier's right to defend himself and that since they were dressed as civilians, the French snipers -- not the Germans -- were responsible for the civilian deaths.

In a method of war where the individual is the prime unit and where lack of identification is a primary defensive method, the conduct of intelligence operations wherever the enemy might be, regardless of borders, follows. So do operations to destroy enemy units -- individuals. If a country harbors such individuals knowingly, it is an enemy. If it is incapable of destroying the enemy units, it forfeits its right to claim sovereignty since part of sovereignty is a responsibility to prevent attacks on other countries.

If we simply follow the logic we laid out here, then the critics of unmanned aerial vehicle strikes have a weak case. It is not illegitimate to target individuals in a military force like the jihadist movement, and international law holds them responsible for collateral damage, not the United States.

since al Qaeda tried in the past to operate in the United States itself, and its operatives might be in the United States, it logically follows that the United States could use unmanned aerial vehicles domestically as well. Citizenship is likewise no protection from attacks against a force hostile to the United States.

The first is that the outrage at targeted killing is not, in my view, justified on moral or legal grounds.

The second is that in using these techniques, the United States is on a slippery slope because of the basis on which it has chosen to wage war.

The broader the engagement, the greater the perception of U.S. hostility to Islam, the easier the recruitment until the jihadist forces reach a size that can't be dealt with by isolated airstrikes.

In the long run, it is not clear that the cost is so little. A military strategy to defeat the jihadists is impossible. At its root, the real struggle against the jihadists is ideological, and that struggle simply cannot be won with Hellfire missiles.

Large organic farms are typically monoculture fields just like large conventional farms, though more crop rotation is required. Industrial organic poultry and beef farms also look oddly similar to conventional industrial feedlots, even if the animals are eating organic feed. In fact, both organic and conventional industrial farms are often owned by the same mega-corporations, and share the same bottom line of profit. There’s no reason to suspect that these industrial organic foods would be markedly more nutritious than conventionally grown foods.

Interestingly, despite the wide range in the quality of foods that qualify as organic, the Stanford study did find some significant differences. Organic produce contained significantly more phenols, the cancer fighting chemicals found in red wine, green tea, chocolate and many fruits and vegetables. However, this finding was glossed over in favor of the non-significant differences found between vitamin C, betacarotene and vitamin E levels in organic versus conventional foods.

Soil quality and weather (the raw ingredients) are by far the biggest factors in the nutrient levels of produce, with freshness and storage methods being next in line.

The Stanford study confirms organic agriculture has substantially fewer pesticide contaminations, but for some reason this finding was also glossed over since the conventional produce levels “didn’t exceed maximum allowed limits.” Logically, however, if limiting pesticide exposure is important to you (as it should be) organic produce is the better option.

The animal studies were even more encouraging. Small but significant improvements in fatty acid profiles were found for organic milk and chickens, which contained more healthy omega-3 fatty acids. More importantly, antibiotic resistant bacteria, the kind that are becoming more common (and deadly) in our own hospitals, were 33% more likely to be found on conventional meat products than on organic meat.