The 9-11 unasked question

When I learned about the September 11 terrorist attack I was having breakfast in Vail, Colorado, following my morning run. In hearing what was happening in New York City, the first thought that came to my mind was “Years of humiliation and punishment brought against the Palestinian population is the root cause of these attacks”.

By and large America didn’t perceive that angle of the devastating attack. Fueled by its righteousness and its ingrained sense of exceptionalism, it became self-indignant saying “How can someone attack us in this manner, this is totally unfair, we absolutely didn’t deserve that kind of treatment.” Nowhere, have I heard “Why did someone inflict that horrible punishment to us?” 

True, asking WHY would have made sense, but remained conspicuously absent from our national response. At least that’s how I understood it. Absolutely no comprehensive post-mortem, but instead a “well-deserved”, twenty year war of vengeance against Afghanistan first, and almost simultaneously another one, almost as costly in lives and resources, against Iraq. 

A tragedy for all that is also a powerful reminder, that in order to learn from a catastrophe we should always get to the root cause of the situation by asking a simple “Why?”

A satisfying day!

My adventures in Spanish began in 2015 but were quickly abandoned because of my flimsy commitment, but July 2024 and the prospect of a trip to Andalusia restarted them, this time very seriously. The tool was Duolingo, a system that left my Assimil methods of my youth for English, German and Italian literally in the dust... 

Last July, I graduated from Duolingo into TalkPal, an AI system powered by Chat-GPT. Fast-forward to a few days ago and I was frankly astounded by my progress in conversation that confirmed, if needed, that I had made the right choice.

Sure, the new method is much easier on an old brain like mine, but it still can’t quite compress the assimilation and learning time as fast as we could wish. 

It’s comparable to growing vegetables, time shortcuts are very hard to come by or have consequences, and for language learning as well, the information needs to settle and slowly percolate before revealing its wonderful results. 

That way of taking its time to coalesce into a satisfying result is precisely what happened to me a few days ago. This was just a fantastic differed gratification making me both proud and happy!  

The curse of the “Night-Person”

As we were walking against the heavy traffic coming to town at about 7:55am, I was thinking about all these folks that are not early risers and are struggling every morning to get to work at an ungodly early hour on time. What a torture! 

An early bird myself, and as a young executive I dreaded that 4:30pm meeting that would extend late into the evening when my brains had become totally useless. As a form of reciprocity, when I became a boss, I was the one having early morning meetings to the damn of my night owls associates… Talk about a total lack of memory and compassion! 

Some people (including me) would believe that “Morning Person” vs. “Night Person” is a 50/50 distribution, but this isn’t true at all. In reality, about 15% of people are morning people, 15% are night people, and the remaining 70% fall somewhere in the middle. 

Morning folks (often nicknamed larks or lions) make up one out of six or seven people. They wake up easily and reach peak energy early in the day. There’s the same proportion of night people (owls or wolves) who prefer staying up late and reaching peak alertness at night. 

Then there’s the rest, the so-called intermediate types (sometimes called bears or third birds) that represent the balance or seven out of ten persons (or over half, depending on the specific classification model). They follow a more flexible middle ground aligned with standard daylight hours. 

But these categories aren’t set in stone, as the preferences change significantly over time. If only about 7% of young adults are morning larks (less than the 15% of the general population), by age 60, the vast majority shift toward becoming morning types, so the landscape is a moving one. In fact it’s amazing how age and gender are able to shift these numbers. 

While genetics establish our baseline, our internal clock naturally evolves as we age. There is a distinct biological shift toward late-night wakefulness around age 20. Roughly 32% of teenagers qualify as night owls. On the other hand, as they age, adults see their internal clocks naturally shift earlier. By age 60, over 63% of people identify as morning types, and only about 7% remain night owls. 

As far as gender differences are concerned, large-scale genetic studies note that more women (48.4%) identify as morning people compared to men (39.7%). Our natural sleep timing (what’s called a chronotype) is largely dictated by our biology and internal clock rather than a conscious choice. 

Now that you’ve read this, you no longer have any excuse for not treating your fellow workers, friends and family according to the requirements of their chronotypes!

Edgar Grospiron’s woes

Recent news regarding Edgar Grospiron centers on his termination as president of the Organizing Committee for the 2030 Winter Olympic and Paralympic Games (COJOP) in the French Alps. Edgar Grospiron had taken the helm of the organizing committee following Martin Fourcade’s withdrawal in early 2025 due to disagreements with local authorities.

The former Olympic moguls champion brought to the table his career as a motivational speaker and his prior involvement in Annecy’s bid for the 2018 Winter Olympics—a bid that had ended in a crushing failure and a decisive defeat against the South Korean city of Pyeongchang. That earlier steering body had suffered from a slow start, local power struggles, and the departure of key figures—most notably Grospiron’s own resignation as CEO in late 2010. 

In this context, the choice of Grospiron a was highly questionable one—as I noted last March—because, aside from professional experience that offered nothing relevant to the complex logistical undertaking of Games spread across the entire French Alps, he lacked the exceptional and wide-ranging experience required for such a challenging mission. 

Grospiron was the quintessential individualist, not the team player needed for the Olympic job. Furthermore, he did nothing to quell significant internal turmoil, particularly the persistent friction between the State, the host regions (Auvergne-Rhône-Alpes and PACA), and the committee regarding budget decisions and the final map of event venues. 

Regarding internal management, the organization saw a succession of staff departures and operational delays, as well as the commissioning of an audit into the workplace climate within COJOP. Among other issues, parliamentarians and the CNOSF publicly questioned the committee’s management and transparency, precipitating a crisis of confidence. 

Faced with all this and the risk of a deadlock less than four years before the Games, the COJOP executive board met yesterday to approve a major governance restructuring, effectively pushing the former Olympic champion out. 

Gini index and happiness (Part Two)

If we were to compare the United States, France, Switzerland, and the Nordic Countries, we’d find that places with low inequality (low Gini) tend to score higher on the Happiness Index, but the relationship is not perfectly linear. 

Still, the pattern becomes very clear: Nordics and Swiss combine low inequality with very high happiness, France sits in the middle, and the US shows high happiness despite high inequality, thanks to strong GDP growth and public‑goods effects. Below is a structured, country‑by‑country comparison grounded in the best available research. 

United States:  

• High inequality, stable happiness The US has exceptionally high income inequality, rising over the last four decades. Yet average happiness has remained broadly constant, and happiness inequality has actually fallen. 
• Why? Research suggests that economic growth and the expansion of public goods (infrastructure, services) help offset the negative effects of inequality. 
• Interpretation: The US is the classic case where high Gini does not automatically mean low happiness, because growth and public goods reduce the dispersion of happiness even as inequality rises. 

France: 

• Moderate inequality, moderate happiness France’s inequality is lower than the US, but higher than the Nordics. Research from French economists (Clark, Flèche, Senik) shows that happiness inequality falls when GDP grows, even if income inequality rises. France fits this pattern: stable happiness, moderate inequality, strong public services. 
• Interpretation: France’s combination of social safety nets and moderate inequality produces middle‑of‑the‑pack happiness scores — higher than the U.S. on equality, lower than the Nordics on happiness. 

Switzerland: 

• Low inequality, very high happiness Switzerland ranks among the richest countries (GDP per capita ~$100K). It also ranks 13th in global happiness (score 6.94). Switzerland’s Gini coefficient is low, thanks to strong social cohesion, high wages, and decentralized governance. 
• Interpretation: Switzerland is a textbook case of low inequality + high happiness, consistent with the dominant global pattern. 

Nordic Countries (Finland, Denmark, Sweden, Iceland): 

• Very low inequality, highest happiness in the world Finland, Denmark, Iceland, and Sweden occupy the top four positions in global happiness rankings (scores 7.35–7.74). These countries also have some of the lowest Gini coefficients globally. Their happiness is driven by strong social safety nets, high trust in institutions, broad access to public services, low inequality and high social mobility 
• Interpretation: The Nordics are the strongest evidence that low inequality correlates with high happiness.

What this comparison shows Low inequality strongly supports high happiness (Nordics, Switzerland). Moderate inequality produces moderate happiness (France). High inequality does not always reduce happiness if growth and public goods compensate (US). 

That’s not as simple as it seems and I hope I didn’t confuse you too much!

Gini index and happiness (Part One)

For those who don’t remember or don’t know it, the Gini index (or Gini coefficient) is a statistical tool used to measure economic inequality within a population. A zero (0) index represents perfect equality, where every single person or household earns the exact same amount of money. A one (1) index stands for perfect inequality, where a single person earns all the income and everyone else earns nothing. 

It’s not a measure you’ll see on your News feed or hear from your politician! I’ve been wondering if there was any correlation between what is published as “Happiness Index” and that measure of inequality. Obviously, there’s a correlation between a country’s Happiness Index and its Gini Index. But the relationship is not linear. 

Research shows three different patterns depending on the country, culture, and level of inequality. A large cross‑national study of 30 countries found that high inequality correlates with fewer happy people and more unhappy people. The effect is similar in magnitude to the effect of median income on happiness. As we had guessed, this is the “expected direction”: more inequality means less happiness. 

This said the relationship is NOT always linear. Major studies have found an inverted U‑shaped curve between inequality and happiness. When inequality is low, people generally see it as a sign of opportunity and upward mobility and believe that their happiness can increase. 

However, when inequality becomes high, jealousy, frustration, and reduced mobility dominate people’s lives and their happiness decreases. This pattern was confirmed in US longitudinal data and European cross‑national data. 

Therefore we could say that a little inequality can increase happiness but too much inequality reduces it. Another study shows that happiness depends on how individuals compare themselves to similar others (same gender, ethnicity, etc.). In that situation, people who can make both upward and downward comparisons feel happier in states where inequality is high, because their relative position is clearer. When inequality is low, comparisons are less meaningful, and this effect disappears. 

This means inequality affects happiness through psychology, not just economics. As we might expect, the effect of inequality on happiness varies strongly by region. Some regions show a strong negative correlation while others show weaker or mixed effects depending on social norms, welfare systems, and mobility expectations. In conclusion, there is a correlation, but it’s complex: 

When inequality is low, happiness can rise and people interpret inequality as a sign of opportunity but when inequality is high, happiness falls as people feel stuck, jealous, or pessimistic about mobility; the relationship depends on social comparison, culture, and expectations. 

This explains why Nordic countries (low Gini, high happiness) score well, while countries with very high inequality often score poorly — but also why some moderately unequal countries can still report high happiness. Next time, we’ll dig a bit deeper and take a look at some individual countries...

Rain and dirty lettuce

Because of intense recent rainfalls, the lettuce from my veggie garden has never been as dirty as it is now and I’ve been wondering if there were any tricks I could use for cleaning it properly and much faster while even using less water.

Here’s what I found based on what professional growers do. Yes, there are faster, cleaner and low‑water ways to wash very dirty garden lettuce, especially after heavy rains when soil splashes deep into the leaves. 

I should start by using a bucket if not a large bowl or salad spinner as a “wash tank”. I fill the container halfway — not full — with cold water and I’ll use the same water for the whole batch. Then, I dunk the lettuce upside down, since soil collects at the base of the leaves and turning the head upside down lets dirt fall out immediately. I follow by gently swishing for 5–10 seconds, without scrubbing as dirt will release on its own. 

Finally, I lift the lettuce out of the water and never pour the water over it. That’s the key because dirt sinks, lettuce floats and I remove a clean lettuce while the dirt stays behind. This uses very little water and cleans far better than running water. Then, a salad spinner removes the last bits of grit and moisture. 

Only if the lettuce is very muddy (like after a severe storm) will I use a “two‑stage wash” by repeating step one into a fresh half container of water. Remember to only use cold water as it makes dirt detach faster, tightens the leaves and makes them crisp. A bonus trick is to remove the outer leaves before washing as they collect the most mud. 

Another pro trick is to soak for 2 minutes with a splash of vinegar (I haven’t tried it). If the soil is sticky (clay‑rich), add 1 tablespoon of white vinegar per gallon of water. It helps release grit and kills microbes and no taste remains after spinning dry. Finally I remember to never rinse under running water as it wastes water and doesn’t remove grit. I don’t shake vigorously as it bruises leaves and never wash in a colander as dirt stays trapped. 

Now, just like me, you can eat a clean salad. Bon appétit!