#online-income

[webwealthcreators]

The Pillars of a Successful Online Business

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[amateurvoltaire]

For the past six years or so, this graph has been making its rounds on social media, always reappearing at conveniently timed moments…

The insinuation is loud and clear: parallels abound between 18th-century France and 21st-century USA. Cue the alarm bells—revolution is imminent! The 10% should panic, and ordinary folk should stock up on non-perishables and, of course, toilet paper, because it wouldn’t be a proper crisis without that particular frenzy. You know the drill.

Well, unfortunately, I have zero interest in commenting on the political implications or the parallels this graph is trying to make with today’s world. I have precisely zero interest in discussing modern-day politics here. And I also have zero interest in addressing the bottom graph.

This is not going to be one of those "the [insert random group of people] à la lanterne” (1) kind of posts.  If you’re here for that, I’m afraid you’ll be disappointed.

What I am interested in is something much less click-worthy but far more useful: how historical data gets used and abused and why the illusion of historical parallels can be so seductive—and so misleading. It’s not glamorous, I’ll admit, but digging into this stuff teaches us a lot more than mindless rage.

So, let’s get into it. Step by step, we’ll examine the top graph, unpick its assumptions, and see whether its alarmist undertones hold any historical weight.

Step 1: Actually Look at the Picture and Use Your Brain

When I saw this graph, my first thought was, “That’s odd.” Not because it’s hard to believe the top 10% in 18th-century France controlled 60% of the wealth—that could very well be true. But because, in 15 years of studying the French Revolution, I’ve never encountered reliable data on wealth distribution from that period.

Why? Because to the best of my knowledge, no one was systematically tracking income or wealth across the population in the 18th century. There were no comprehensive records, no centralised statistics, and certainly no detailed breakdowns of who owned what across different classes. Graphs like this imply data, and data means either someone tracked it or someone made assumptions to reconstruct it. That’s not inherently bad,  but it did get my spider senses tingling.

Then there’s the timeframe: 1760–1790. Thirty years is a long time— especially when discussing a period that included wars, failed financial policies, growing debt, and shifting social dynamics. Wealth distribution wouldn’t have stayed static during that time. Nobles who were at the top in 1760 could be destitute by 1790, while merchants starting out in 1760 could be climbing into the upper tiers by the end of the period. Economic mobility wasn’t common, but over three decades, it wasn’t unheard of either.

All of this raises questions about how this graph was created. Where’s the data coming from? How was it measured? And can we really trust it to represent such a complex period?

Step 2: Check the Fine Print

Since the graph seemed questionable, the obvious next step was to ask: Where does this thing come from? Luckily, the source is clearly cited at the bottom: “The Income Inequality of France in Historical Perspective” by Christian Morrisson and Wayne Snyder, published in the European Review of Economic History, Vol. 4, No. 1 (2000).

Great! A proper academic source. But, before diving into the article, there’s a crucial detail tucked into the fine print:

“Data for the bottom 40% in France is extrapolated given a single data point.”

What does that mean?

Extrapolation is a statistical method used to estimate unknown values by extending patterns or trends from a small sample of data. In this case, the graph’s creator used one single piece of data—one solitary data point—about the wealth of the bottom 40% of the French population. They then scaled or applied that one value to represent the entire group across the 30-year period (1760–1790).

Put simply, this means someone found one record—maybe a tax ledger, an income statement, or some financial data—pertaining to one specific year, region, or subset of the bottom 40%, and decided it was representative of the entire demographic for three decades.

Let’s be honest: you don’t need a degree in statistics to know that’s problematic. Using a single data point to make sweeping generalisations about a large, diverse population (let alone across an era of wars, famines, and economic shifts) is a massive leap. In fact, it’s about as reliable as guessing how the internet feels about a topic from a single tweet.

This immediately tells me that whatever numbers they claim for the bottom 40% of the population are, at best, speculative. At worst? Utterly meaningless.

It also raises another question: What kind of serious journal would let something like this slide? So, time to pull up the actual article and see what’s going on.

Step 3: Check the Sources

As I mentioned earlier, the source for this graph is conveniently listed at the bottom of the image. Three clicks later, I had downloaded the actual article: “The Income Inequality of France in Historical Perspective” by Morrisson and Snyder.

The first thing I noticed while skimming through the article? The graph itself is nowhere to be found in the publication.

This is important. It means the person who created the graph didn’t just lift it straight from the article—they derived it from the data in the publication. Now, that’s not necessarily a problem; secondary analysis of published data is common. But here’s the kicker: there’s no explanation in the screenshot of the graph about which dataset or calculations were used to make it. We’re left to guess.

So, to figure this out, I guess I’ll have to dive into the article itself, trying to identify where they might have pulled the numbers from. Translation: I signed myself up to read 20+ pages of economic history. Thrilling stuff.

But hey, someone has to do it. The things I endure to fight disinformation...

Step 4: Actually Assess the Sources Critically

It doesn’t take long, once you start reading the article, to realise that regardless of what the graph is based on, it’s bound to be somewhat unreliable. Right from the first paragraph, the authors of the paper point out the core issue with calculating income for 18th-century French households: THERE IS NO DATA.

The article is refreshingly honest about this. It states multiple times that there were no reliable income distribution estimates in France before World War II. To fill this gap, Morrisson and Snyder used a variety of proxy sources like the Capitation Tax Records (2), historical socio-professional tables, and Isnard’s income distribution estimates (3).

After reading the whole paper, I can say their methodology is intriguing and very reasonable. They’ve pieced together what they could by using available evidence, and their process is quite well thought-out. I won’t rehash their entire argument here, but if you’re curious, I’d genuinely recommend giving it a read.

Most importantly, the authors are painfully aware of the limitations of their approach. They make it very clear that their estimates are a form of educated guesswork—evidence-based, yes, but still guesswork.   At no point do they overstate their findings or present their conclusions as definitive

As such,  instead of concluding with a single, definitive version of the income distribution, they offer multiple possible scenarios.

It’s not as flashy as a bold, tidy graph, is it? But it’s far more honest—and far more reflective of the complexities involved in reconstructing historical economic data.

Step 5: Run the numbers

Now that we’ve established the authors of the paper don’t actually propose a definitive income distribution, the question remains: where did the creators of the graph get their data? More specifically, which of the proposed distributions did they use?

Unfortunately, I haven’t been able to locate the original article or post containing the graph. Admittedly, I haven’t tried very hard, but the first few pages of Google results just link back to Twitter, Reddit, Facebook, and Tumblr posts. In short, all I have to go on is this screenshot.

I’ll give the graph creators the benefit of the doubt and assume that, in the full article, they explain where they sourced their data. I really hope they do—because they absolutely should.

That being said, based on the information in Morrisson and Snyder’s paper, I’d make an educated guess that the data came from Table 6 or Table 10, as these are the sections where the authors attempt to provide income distribution estimates.

Now, which dataset does the graph use? Spoiler: None of them.

How can we tell? Since I don’t have access to the raw data or the article where this graph might have been originally posted, I resorted to a rather unscientific method: I used a graphical design program to divide each bar of the chart into 2.5% increments and measure the approximate percentage for each income group.

Here’s what I found:

Now, take a moment to spot the issue. Do you see it?

The problem is glaring: NONE of the datasets from the paper fit the graph. Granted, my measurements are just estimates, so there might be some rounding errors. But the discrepancies are impossible to ignore, particularly for the bottom 40% and the top 10%.

In Morrisson and Snyder’s paper, the lowest estimate for the bottom 40% (1st and 2nd quintiles) is 10%. Even if we use the most conservative proxy, the Capitation Tax estimate, it’s 9%. But the graph claims the bottom 40% held only 6%.

For the top 10% (10th decile), the highest estimate in the paper is 53%. Yet the graph inflates this to 60%.

Step 6: For fun, I made my own bar charts

Because I enjoy this sort of thing (yes, this is what I consider fun—I’m a very fun person), I decided to use the data from the paper to create my own bar charts. Here’s what came out:

What do you notice?

While the results don’t exactly scream “healthy economy,” they look much less dramatic than the graph we started with. The creators of the graph have clearly exaggerated the disparities, making inequality seem worse.

Step 7: Understand the context before drawing conclusions

Numbers, by themselves, mean nothing. Absolutely nothing.

I could tell you right now that 47% of people admit to arguing with inanimate objects when they don’t work, with printers being the most common offender, and you’d probably believe it. Why? Because it sounds plausible—printers are frustrating, I’ve used a percentage, and I’ve phrased it in a way that sounds “academic.”

You likely wouldn’t even pause to consider that I’m claiming 3.8 billion people argue with inanimate objects. And let’s be real: 3.8 billion is such an incomprehensibly large number that our brains tend to gloss over it.

If, instead, I said, “Half of your friends probably argue with their printers,” you might stop and think, “Wait, that seems a bit unlikely.” (For the record, I completely made that up—I have no clue how many people yell at their stoves or complain to their toasters.)

The point? Numbers mean nothing unless we put them into context.

The original paper does this well by contextualising its estimates, primarily through the calculation of the Gini coefficient (4).

The authors estimate France’s Gini coefficient in the late 18th century to be 0.59, indicating significant income inequality. However, they compare this figure to other regions and periods to provide a clearer picture:

Amsterdam (1742): Much higher inequality, with a Gini of 0.69.

Britain (1759): Lower inequality, with a Gini of 0.52, which rose to 0.59 by 1801.

Prussia (mid-19th century): Far less inequality, with a Gini of 0.34–0.36.

This comparison shows that income inequality wasn’t unique to France. Other regions experienced similar or even higher levels of inequality without spontaneously erupting into revolution.

Accounting for Variations

The authors also recalculated the Gini coefficient to account for potential variations. They assumed that the income of the top quintile (the wealthiest 20%) could vary by ±10%. Here’s what they found:

If the top quintile earned 10% more, the Gini coefficient rose to 0.66, placing France significantly above other European countries of the time.

If the top quintile earned 10% less, the Gini dropped to 0.55, bringing France closer to Britain’s level.

Ultimately, the authors admit there’s uncertainty about the exact level of inequality in France. Their best guess is that it was comparable to other countries or somewhat worse.

Step 8: Drawing Some Conclusions

Saying that most people in the 18th century were poor and miserable—perhaps the French more so than others—isn’t exactly a compelling statement if your goal is to gather clicks or make a dramatic political point.

It’s incredibly tempting to look at the past and find exactly what we want to see in it. History often acts as a mirror, reflecting our own expectations unless we challenge ourselves to think critically. Whether you call it wishful thinking or confirmation bias, it’s easy to project the future onto the past.

Looking at the initial graph, I understand why someone might fall into this trap. Simple, tidy narratives are appealing to everyone. But if you’ve studied history, you’ll know that such narratives are a myth. Human nature may not have changed in thousands of years, but the contexts we inhabit are so vastly different that direct parallels are meaningless.

So, is revolution imminent? Well, that’s up to you—not some random graph on the internet.

Notes

(1) A la lanterne was a  revolutionary cry during the French Revolution, symbolising mob justice where individuals were sometimes hanged from lampposts as a form of public execution

(2) The capitation tax was a fixed head tax implemented in France during the Ancien Régime. It was levied on individuals, with the amount owed determined by their social and professional status. Unlike a proportional income tax, it was based on pre-assigned categories rather than actual earnings, meaning nobles, clergy, and commoners paid different rates regardless of their actual wealth or income.

(3) Jean-Baptiste Isnard was an 18th-century economist. These estimates attempted to describe the theoretical distribution of income among different social classes in pre-revolutionary France. Isnard’s work aimed to categorise income across groups like nobles, clergy, and commoners, providing a broad picture of economic disparity during the period.

(4) The Gini coefficient (or Gini index) is a widely used statistical measure of inequality within a population, specifically in terms of income or wealth distribution. It ranges from 0 to 1, where 0 indicates perfect equality (everyone has the same income or wealth), and 1 represents maximum inequality (one person or household holds all the wealth).

[mod2amaryllis]

uhh oh!!! unexpected hospital stay 🤪

last night i fell flat on my stomach tripping over absolutely nothing, so i went in to get checked. everything looks fine aside from a scraped hand and knee but they kept me for overnight monitoring just in case. this, of course, happened while jose is out of town, so ngl chat it was a rough time!!! baby spent the entire night gettin funky, blissfully unaware of her mom's moment of lonely mortal terror.

I've never had the nuts to ask but idk how much this stay will cost and I'll be officially without an income in two weeks. anything you could throw my way would be so appreciated. 💛

[lavendercoins]

[maddybabeyxo]

is anyone trying to make money right now?? I have found a few ways with crypto how to make some, DM me before it's too late ;)

[colebabey888]

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[najmiska]

I didn't think much while putting this on, but damn, I look gooood xD The autumn vibes are on

[theambitiouswoman]

Some of my favorite ways to make money online from the comfort of my bed:

Dropshipping

Affiliate Marketing

Blogging

KDP

Trading

YT Automation

Web design

Consulting

Meme/Niche social pages

POD

The landscape for making money (and with unlimited potential) has changed. Most of these you can start with little to no money. And there are hundreds more.

Give yourself the opportunity to learn new things.

Stop thinking it does not work.

Believe in yourself.

[napping-sapphic]

At this rate i’m gonna have to start saying that neither women nor jobs want me and frankly that will just be too much to bear💀💀

[horsegamergirl]

This season's first SSO redeem code just dropped

SPOOKYSEASON

gives 20 SC

[angadgautama]

Is Tumblr can be a source of income as like YouTube and other media platforms? If it is. Then what is the criteria for eligibility?

[fjordfolk]

whenever i get to replace this camera, im throwing it out of the fucking window

[defiledtomb]

I’m PRAYING for PLEASE work out!!!! You deserve that apparment!!! God! I’m so excited!

ME TOOOOO!!!

[liskantope]

In the midst of this discussion, I have to paraphrase a bit but the following was actually expressed:

Both (straight) women and (straight) men have a problem with insisting on impossible standards in the dating market. So many women nowadays want a man who is six-foot-something, in finance making six figures, not overweight, etc., and they don't realize that it's a very small percentage of men who satisfy all of those criteria. And men make this mistake too: they want a woman who is not on the left, not taking some kind of antidepressent, not overweight...

I know it could be viewed as just a silly flippant comment by an early-20's conservative cultural commentator, but I... don't even know how to feel about our current times where it's even halfway credible to suggest the analog of "over six feet, six figures" (as an unreasonable standard) is "not on the left, not on antidepressents". That's just weird in multiple different ways, yet has enough of a vague ring of plausibility about it that someone might actually say this.

A day or two after I saw part of the above-linked podcast episode, Aella published a post which opens by mentioning a study result saying that women (in 2006!) equally value a man being 6' instead of 5'6'' and a man making an additional $175k a year. I had to double-check to make sure I wasn't misreading that salary increase figure by an order of magnitude. (The study also shows that being 5'11.5' instead of 5'8'' -- my height on a good day -- is equivalent to $138k difference in income.)

I know I'm probably just fixating on particularly dumb comments/data, but the dating world continues to look depressing, folks. Well, at least as long as it continues to be predominantly online.

[lavendercoins]

Claim it 🤞

[polysyndetonaddictsupportgroup]

Just want to say: a, I admire very much that you've figured out a healthy way to work on your fics that allows you to have fun with it. And also b, am very excited to hear that you are getting there with pez! It has fully given me brain rot ever since I read it last year, there is just such a lack of content for the highly specific trope of using time travel as a device to explore extremely unhealthy levels of self loathing.

I just adore everything you're doing in it. Neither midoriya is anywhere approaching okay for any portion of the fic and I love rereading and mining into all the subtle characterization pointing to that. It's a bit like nhtycth in that some really goofy funny stuff is often hiding some really fucking worrying things, but the fact that characters DO do that stuff—that todoroki uses his teaspoon's worth of extremely stunted social skills to bludgeon his friend's door open and help him, that a rpf shipping war is an actual source of drama despite how goofy the sentiment seems on the surface, that about half of what jon says is deeply worrying and the other half is extremely funny and there's a lot of overlap between the two—really lifts the tension and brightens the universe. It's sort of similar to what you did with gerry, in that endless misery isn't nearly as painful as the ups and downs of a life that, when you step back and zoom out, has something deeply and horribly wrong with it.

(jon sort of reminds me of spider-man in that he uses human to deal with trauma and stress, except I don't think he at any point realizes how fucking funny he is. He's just there, in a home depot, gnashing his teeth because he's got so many bodies to dispose of and this cashier sure is taking her time.)

I really, really, really have had trouble finding fics that take everything midoriya has dealt with to task. It's a hell of a thing to live 14 years as a disabled minority, have it heavily shape your existence, and then one day you wake up and you realize you're...not that, or at least, nobody will ever acknowledge you as that again. You've lost all claim to it. Those experiences that shaped who you are? Dust in the wind. 14 years of pain and life might as well be buried in the ground for all the good they do you. Nobody's going to cut you any slack or quarter, you've gotta simply work harder, be better. And now when you do that you get the results you wanted, so that's fine, then. That's good. There was something wrong with the you before, and there's something right with the you now, and if the transition is a little rough, well that doesn't matter, you're the same as everyone else now, so it's your own job to fill in whatever gaps you need to.

I really can't get over how mentally fucked it must be for midoriya to run into quirkless people, run across quirkless issues, and be silently caught between, incapable of speaking his mind and too scared to do so anyway around those he can trust.

Also I should mention, I'm just very excited for bakugou to get back from the gym. He's been there like a year I hope he's getting a good workout in.

Me realizing that it’s been a year since pez dispenser debris:

I feel like there’s just this very specific type of grief that Izuku has to grapple with in the span of pez dispenser debris that I’m just obsessed with. He’s sort of silently mourning who he could have been, when 1) he has to present like there’s nothing lost to maintain his secret and 2) the entire world is constantly inundating him with the message that there was nothing lost.

Like. I don’t want to get too deep into it because it risks spoiling things and I do have major plans to continue it (I’ve loved this story for so many years before I ever even hit publish), but the emotion that Izuku’s feeling right now is so much more complex than “I hate who I used to be and want him to stop existing” or “I just want to keep my secrets.” And I think the way he interacts with Mirio is the biggest evidence of that.

Izuku’s placed himself at the very center of the Quirklessness debate with his support of Mirio. He fights for Quirkless heroes, very publicly, to the point where he’s not even graduated yet but considered to be one of the most prominent voices on the matter. If you took a poll of Quirkless people as to which hero would be most supportive of them pursing their own career in heroics, Izuku would be right at the top of the list. When it comes to Quirklessness itself, he’s nothing but supportive.

But he didn’t tell Mirio the truth of his own Quirklessness.

Out of everyone, Mirio’s the one everyone expects to know, despite him being a relatively newer relationship compared to someone like Iida or Uraraka or Todoroki. And I tried to imply that he’s sort of the one who knows the most about Izuku out of everyone save All Might.

Like, we’ll get into how much exactly Mirio knows soon, so I won’t divulge what, if anything, Izuku has told him. But we know that Mirio knows, weirdly enough, that Izuku is deeply fucking haunted. He knows that boy has many violent ghosts in his bones. He finds it hilarious and will tell their realtor about it. Izuku told him about the discontent spirits who died in a violent passion and live on inside of him before he told him about his Quirklessness.

And I just feel like one of those things is a little bit easier to discuss than the other.

Izuku has decided to keep his own Quirklessness quiet in a way that surpasses secrecy about One for All. If it was just about OfA, he could tell people he didn’t get his quirk until the entrance exam, and it wouldn’t even be a lie. He’s purposefully obscuring his own past as Quirkless even as he takes a forefront of the Quirkless hero debate with his open support of Mirio.

And the fact that he’s at the forefront of this debate in and of itself requires a difficult dichotomy. He is the world’s most vocal proponent for the first Quirkless hero. He is a known figure in the Quirkless community now.

He isn’t considered one of them anymore. He’s an outsider coming in.

It must be such a strange, odd sort of grief to come to the people you were home amongst for most of your life and be greeted as a stranger. To return home, and to be welcomed in for the first time, and to not even be able to tell people that you’ve lived here all your life and don’t need a tour.

It’s a sort of death of self, I think. And I think Izuku never expected to have to grapple with his own ghost.