The larvae in the hanging cells become queens. A queen lives for years and can lay more than a thousand eggs a day. A worker lives about six weeks in summer and usually lays none.

Food decides which. The white jelly is royal jelly, a rich food made in glands in the workers’ heads. The workers feed it to a few larvae for as long as they are larvae. The rest are switched to a plainer mix with pollen and honey in it, and become workers. Food cannot rewrite a gene. So what does it change?

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Figure 1. How royal jelly makes a queen, from SciShow (2015). Thumbnail illustration from Raydel (2026).

In 2008, a team at the Australian National University, in Canberra, tested one answer. Cells can stick small chemical marks onto some of their genes. These are called methylation marks. They help decide which genes the cell reads and which it skips. The marks work like punctuation: add a comma or a period, and the same words read differently. The team switched off one gene in newly hatched larvae: the gene for an enzyme that lays down those marks. Then they fed the larvae a worker’s diet. Most of them came out as queens, with full ovaries. Turning down the marks did what the royal jelly does. Each larva kept the genes it was born with. What changed was which of them got read.

The bee each larva became depended on what its genes were connected to: the marks, the food, and the workers who chose which larvae to feed.

Say you mail a spit sample to a DNA testing company, and the report comes back: you probably cannot digest milk as an adult. You start drinking your coffee black. You stop buying cheese, pay extra for lactose-free milk and check every label in the shop. You also lose an easy source of calcium.

Here is how the report could be wrong. For most people in the world, the body stops digesting milk after childhood, like a door that locks. Some people carry a key that keeps the door open. In Europe, most people who have a key share one version of it. Many families who kept cattle in East Africa carry a different key that opens the same door. The test only looks for the European key. If you carry the East African one, the test finds no key it knows and says the door is locked. You gave up milk for nothing. The test was right that you lack the European key. It never asked where your family came from. Systems thinking has a question for any test result you get: what else is connected to it?

Which Genes Get Read

Counting human genes started as a bet. In May 2000, at a genome meeting at Cold Spring Harbor, the geneticist Ewan Birney opened a pool on how many genes the human genome would turn out to hold. Biology was about to get its first full parts list for a person. The parts were not organs or limbs but genes, each one a recipe for a molecule the body uses. Over three years, more than 460 people placed bets. The guesses ran from about 20,000 to more than 200,000. In 2003, the count came in at 24,847. The closest guess, 25,947, belonged to Lee Rowen, who worked at the Institute for Systems Biology. She won $600 and a signed copy of The Double Helix.

Later counts settled lower, near 20,000. The worm C. elegans, about a millimeter long, has a little over 20,000 genes of its own. So the number of parts could not be what makes a person a person. In Donella Meadows’ definition of a system, the parts matter less than the rules that connect them. One deck of cards can deal poker or solitaire. The cards do not change. The rules make the game. The difference between a person and a worm lives in the rules: how the genes get used, and what they connect to.

Measuring one layer of a living thing all at once is called omics. Each layer takes the suffix -ome. There are many -omes, one for each kind of molecule a cell holds. Two of them explain the bees.

The genome is the layer the walkthrough of DNA, transcription, and translation takes apart. The epigenome is the layer the natural experiment on methylation follows. Each -ome is a list of parts. A list does not say how its parts connect.

The bees showed the epigenome at work: the same genome, different marks. And what a cell reads can turn around and change what it reads next.

How the Layers Loop

E. coli, a bacterium in the gut, leaves one of its genes unread until milk shows up. The gene makes an enzyme that digests lactose, the sugar in milk. In 1961, François Jacob and Jacques Monod worked out how the cell decides. A protein called a repressor sits on the gene and keeps it switched off. When lactose arrives, it pulls the repressor off, and the cell makes the enzyme. The enzyme breaks the lactose down. When the lactose runs out, the repressor settles back, and the gene switches off again. Jacob and Monod shared the 1965 Nobel Prize for this work, with André Lwoff.

In Meadows’ terms for feedback, that is a balancing loop: a change that comes back around and undoes itself. The gene answers to the sugar, and the sugar answers to the gene.

A loop can also cross layers. In 2012, Romain Barrès and his colleagues asked sedentary adults to ride an exercise bike at either 40 or 80 percent of their maximum effort. They took small samples of thigh muscle before the ride, right after it, and three hours later. On several genes that help build a cell’s energy supply, including one called PGC-1α, the methylation marks dropped, and the genes became more active. Both changes were larger after the harder ride, and the drop in the marks appeared to come first.

PGC-1α is a master switch for building mitochondria, the parts of a cell that burn fuel. Over months of training, more mitochondria mean more capacity for the next ride. Follow the loop around. The ride changes the marks on the genes. The marks change which genes get copied into RNA, a layer called the transcriptome. The copies change which proteins get made, the proteome. The proteins change what the body can do on the next ride. No one layer holds the whole of what exercise does.

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Figure 2. What more mitochondria do for a cyclist, from Pedaling to the Top (2025). Thumbnail illustration from Wild Rose College (2025).

Milk runs through a much slower loop in people. Babies make their own enzyme for lactose, called lactase. In most mammals, the body stops making lactase after weaning. In about a third of adults alive today, it keeps making it. The difference is not in the lactase gene itself. A short stretch of DNA near the gene works as a dial for it, and after childhood the dial turns the gene down. That is the locked door from the DNA kit. The European key is a single changed letter in that dial, and it keeps the gene on for life.

The East African keys are other one-letter changes nearby, and each arose on its own. In 2007, the geneticist Sarah Tishkoff and her colleagues traced the most common of them, carried by many herding peoples in Kenya and Tanzania. That key had spread fast, over roughly the last seven thousand years. The team tied the spread to keeping animals and drinking their milk as adults.

Milk and the key ran in a loop of their own. Herds put fresh milk within reach. Adults who carried the key could digest it, got more food from it, and more of their children lived to carry the key too. The more people could drink milk, the more a herd was worth, and herding spread further. This is the other kind of loop, a reinforcing one: a change that feeds itself. Even this loop has a ceiling. A herd can grow only as large as the grass and water around it allow. Past that point, more cows mean less for each cow, a balancing loop that slows the spiral. Neither loop is written in anyone’s DNA. A DNA sample can show whether someone carries a key. It cannot show the herds that made the key worth carrying, or the grass and water that capped the herds.

What the Data Leaves Out

The physiologist Denis Noble wrote about the heart: “all the proteins involved in cardiac rhythm are encoded by the genome, but these alone would not generate rhythm.” The rhythm comes from the proteins acting together, in a cell, over time. The psychiatrist and systems scientist Felix Tretter calls molecular systems medicine “holistic but still reductive.” It measures as many molecules as it can, then tries to rebuild the organism from the bottom up, one part at a time.

Time is the first thing a single sample loses. Many omics studies draw blood from each person once. Peter Senge defines systems thinking as seeing “patterns of change rather than static ‘snapshots.’” A single blood draw is a snapshot. The exercise study needed three samples in one afternoon to see which change came first.

Even a study that samples over time can lose the pattern. A balancing loop with a delay can overshoot and swing back. A radiator in an old house is slow. It keeps warming the room after the thermostat shuts it off, and it takes a while to warm up once the heat comes back on. So the room swings too warm, then too cool. Read that room’s temperature every hour, and the numbers rise and fall around the setting. An analysis that expects a steady level averages the swing away as noise, and the loop that made it disappears with it.

The connections are the second thing lost. The most common way to analyze the data takes the list of parts and tests each part on its own. A study of methylation can run hundreds of thousands of separate tests, one for each marked site on the genome, each asking whether that one site differs between two groups, such as people with a disease and people without. Each test looks at its site alone, as if each site had its own story. But many sites share a cause. In the bees, the marks differ between queen and worker larvae on more than two thousand genes. Test those sites one at a time, and each shows up as a separate hit. The food that sent the two larvae down different paths never appears. The analysis hands back a list of sites with no lines drawn between them.

That one-at-a-time test, run on DNA, has mapped human height. In 2022, a study led by the geneticist Loïc Yengo pooled the genomes of 5.4 million people. It found 12,111 variants tied to height, each with a tiny effect. Together, in people of European ancestry, they account for about 40 percent of how much heights differ. In people of other ancestries, the share falls to about 10 to 20 percent.

Height also changes faster than a genome can. In the 1800s, Dutch soldiers averaged about 165 centimeters, shorter than men in most of Europe. Dutch men are now the tallest in the world, about 20 centimeters taller. A rise that fast points to food, health, and living conditions, not to new genes.

A height score on a DNA kit report, built from those 12,111 variants, says something about height. It says less outside the ancestry it was built on, and nothing about what a childhood’s meals will add.

How Far the Map Reaches

Malaria kills close to 600,000 people a year, most of them young children in Africa. One of the main treatments for malaria is the drug artemisinin, which comes from a plant called sweet wormwood. The supply of wormwood swings. A short harvest sends the price up, so more farmers plant wormwood. Once their crops flood the market, the price falls, and the next shortage begins.

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Figure 3. Two short histories of malaria drugs, from NPR’s Skunk Bear (2012) and SciShow (2021). Thumbnails via BMRB: a wormwood plate from Köhler (1887) and the first page of the 1979 qinghaosu paper.

In 2003, a team led by the chemical engineer Jay Keasling, at Berkeley, looked for a steadier source. They gave E. coli a chain of genes from baker’s yeast and one gene from wormwood, and the bacteria made an early form of the drug. When the team pushed for more, the cells stalled. Each gene they added did its job. The trouble was their pace. Donella Meadows calls an amount that builds up or drains over time a stock, like water in a bathtub. Partway down the chain, a compound called HMG-CoA was a stock. One step filled it, the next step drained it, and the filling ran faster than the draining, so the pile rose. HMG-CoA is toxic to E. coli, and the cells grew worse. The fix was more of the draining enzyme. The pile fell, and the cells grew again. No single gene showed the jam. It showed up only in the whole chain. Finding jams like this one (which parts affect which, in what order, and how fast) is the work of systems biology.

The work moved to yeast, where a wormwood enzyme carried the early form three chemical steps closer to the drug. In April 2013, the drug company Sanofi started making artemisinin with yeast in Garessio, in northern Italy. That year, the factory made about 8 percent of the world’s supply.

By 2015, farmers had a great year. So much wormwood grew that artemisinin from the plants sold for less than $250 a kilogram. Sanofi needed $350 to $400 to break even. Why would anyone pay more for Sanofi’s artemisinin when the plant’s was cheaper? Sanofi could have sold to the other drug companies. But those companies compete with Sanofi, and they did not want to buy from it. And the world was not asking for any more of the drug than before.

“If that price is already very low and there’s a bumper crop,” Keasling said, “there’s no reason to fire up a fermenter.” The fermenter stood idle. The yeast still knew how to make the drug.

That is where even a full map of the cell stops. No layer inside the yeast held the price of wormwood. Tretter names this as one of three gaps a molecular theory cannot bridge: the gap between an organism and the world around it. The world does reach in. The exercise bike left its marks on the muscle within hours. A sample of those marks, taken alone, cannot say which ride left them. Every -ome ends at the edge of what was sampled.

Measuring every layer of a cell is a good place to start. But however closely someone studies one part, a question stays open: what else is connected to this part?

A Closing Invitation. The jelly, the bike and the price of wormwood each reached in from outside. None of them touched a gene. Each changed what the genes ended up doing.

1. A test result you acted on this year: a DNA kit report, a blood panel, a number on the scale. What did you give up because of it, and what else was connected to it that the test never asked about?
2. One step in a routine you tried to speed up this week, where something further along jammed instead. Where did the pile-up show, and who noticed it first?
3. Something in your home that still works and stays in the cupboard: a bread maker, a juicer, a bike. What around it changed?

Next time you open a packet of baker’s yeast, smell it, then split the dough between two bowls: one by a warm window, one in a cool corner. An hour later, look at both. Nothing in the packet changed.

Where This Came From

This piece carries the questions from Twenty-Three Cats into a single cell. Tretter’s paper (2019) doubts that molecules alone explain an organism; read its section on the three explanatory gaps. Konopka’s post on systems thinking (2026) suggested reading the HMG-CoA jam as a stock. For the yeast, read Peplow (2016) for why the factory stopped, and Paddon et al. (2013) for the route from yeast to drug. For the bees, Kucharski et al. (2008) is four pages; Foret et al. (2012) counts the larval genes whose marks differ between queens and workers. The hive details are standard beekeeping descriptions.

Intellectual Honesty Note. The stakes paragraph’s report is hypothetical, and which keys a kit tests depends on the kit. This piece reads the lactose switch as a balancing loop, the HMG-CoA jam as a stock, and lactase persistence as a reinforcing loop with a grazing ceiling. It also adds the exercise loop’s last step, “more capacity for the next ride,” the point that a sample of marks cannot name the ride that left them, and the point that testing the bees’ marks one site at a time would miss the food behind them. Two terms are simplified: the molecule that pulls the lac repressor off is allolactose, and the “dial” is an enhancer, a stretch of DNA that raises a gene’s activity. The exercise study measured one ride, over three hours. The protein step and the link from PGC-1α to mitochondria are standard physiology. The bee experiment switched the methylation enzyme off by hand; how much methylation steers caste in an ordinary hive is still debated (Oldroyd and Yagound, 2021). The video in Figure 1 draws on a 2011 study that credited one protein in the jelly, royalactin (Kamakura, 2011); a later team could not reproduce it (Buttstedt et al., 2016). The video in Figure 2 also gives training and diet tips; this piece leans only on its account of mitochondria. Part of the 60 percent of height the variants miss is genetic and not yet mapped. Tretter and Noble are quoted from their papers, Senge from The Fifth Discipline.

References

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Figure 1. Operation Cat Drop as it is usually retold, from Sustainability Illustrated (2014). Thumbnail illustration from Heart of the Art (2015).

The cats came from Kuching, the capital of Sarawak. The city’s name is often said to mean “cat.” Kuching had been asked for thirty cats and could find twenty-three. Later retellings grew the number to fourteen thousand. The cats were bound for Bario, a village high in the Kelabit Highlands, where rats were eating the rice. The plane made five test runs before the first basket went out. Hundreds of villagers watched the baskets come down into the rice fields. A month later, the village sent a message back to Kuching: “Thanks for the cats – no more trouble with rats and mice.”

The rats were the last link in a chain that started with a good idea. In the early 1950s, malaria teams sprayed DDT and other insecticides on the walls of the longhouses, the long shared houses where families slept. The spray killed the mosquitoes that carried malaria. It also killed tiny wasps. The wasps laid their eggs inside caterpillars, and that kept the caterpillars from multiplying. The caterpillars lived in the thatch, the dried leaves that made the roofs. They could sense the chemical and stayed away from it. The wasps could not, and they died. With the wasps gone, the caterpillars ate the roofs. The village cats died too. With the cats gone, the rats came in.

The spray went on the walls. The damage came later, through the roofs and then the rice. The villagers suspected the insecticide. It took a team from the World Health Organization to trace the damage back to a wasp small enough to miss.

Cities have their own version of the spray. Houston spent $2.8 billion widening the Katy Freeway to more than twenty lanes, to end its traffic jams. The new lanes did ease the jam at first. Then the wider road drew more drivers. Between 2011 and 2014, the rush-hour drive along it got 30 percent longer in the morning and 55 percent longer in the afternoon. Across American cities, economists have found that driving grows in step with new lanes.

A cheaper house farther out lowers your mortgage, and it works. It also adds an hour to your drive, each way. Someone else takes over the school drop-off. Dinner moves later, then apart. On a Friday, a friend texts about drinks. You read it in traffic, forty minutes from home, and text back no. After a few months, the texts stop coming. The mortgage really did drop.

In Sarawak, too, the spray did what it was meant to do. It was a correct answer to a question about one part. The malaria teams asked how to stop the mosquito. A better question was what else the insecticide would kill. That question splits into three, each worth asking before a fix is made, or before the papers for the cheaper house are signed. What else is connected to this part? What does it keep in check? Who decided what counts, and what did they leave out?

What a System Is

Before a concert, one oboe plays a single note, an A, and the rest of the orchestra tunes to it. If the oboe is a little sharp, the whole orchestra is a little sharp. The three questions ask about parts tied together like that. People have tried to define a system for about ninety years. Here are five of their answers, with the orchestra to test them on.

Bertalanffy was a biologist. He wanted one language for a cell, an animal, and a society. His next sentence explains what “interacting” means. Parts interact when each one behaves differently depending on what it is connected to. If they behave the same no matter what, “the elements behave independently,” and there is no system. Take a violinist. Alone, a violinist can play at any speed. In an orchestra, the same violinist listens and keeps pace with everyone else. What the violinist plays depends on who else is playing.

system, n.definition 2 of 5Wave 1

“A system is an interconnected set of elements that is coherently organized in a way that achieves something.”

Meadows split her definition into three things to look for. The elements are the things in the system. The interconnections are how they affect each other. The function, or purpose, is what the whole does. In an orchestra, the elements are the players and their instruments. The interconnections are the score, the conductor, and the players listening to each other. The purpose is music for the people in the seats.

Figure 2. The three things Meadows says to look for in a system: elements, interconnections, and function or purpose.

Meadows also ranked the three. The elements matter least. Replace every player on a football team, and it is still a football team. The interconnections matter more. Change the rules to basketball’s, and it is a new game (p. 16). The purpose matters most. She called it “often the most crucial determinant of the system’s behavior” (p. 17), and it is the hardest to see. To find it, watch what the system does: “Purposes are deduced from behavior, not from rhetoric or stated goals” (p. 14). An orchestra may say its purpose is great music. If it plays the same safe pieces every season because they sell tickets, its behavior says the purpose is selling tickets.

system, n.definition 3 of 5Wave 2

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“A system is a whole that cannot be divided into independent parts.”

Ackoff reached that sentence in three steps. A system has two or more parts. Each part can change how the whole behaves, but never alone. What one part does depends on at least one other part. This holds for any group of parts too. Take the violins out of an orchestra, and the rest do not play the old symphony minus the violins. Every other part now sounds different.

Senge studied system dynamics, the modeling school Meadows came from, at MIT. His book put it in plain words for managers. He defines a skill. Systems thinking is the habit of asking what else a change touches, and when. A snapshot of an orchestra catches one chord. The music is the pattern of chords over time.

Senge also listed laws for what happens without that habit. The first is “Today’s problems come from yesterday’s ‘solutions.’” Another is “Cause and effect are not closely related in time and space.” Houston’s wider freeway fits both.

Co-implying means each needs the other. Nothing is a part unless it belongs to a whole. Nothing is a whole unless it has parts. For the Cabreras, seeing systems is one of four moves a mind makes. The other three are telling things apart, relating them, and taking a point of view. Ask it of the violinist. Is the violinist part of the orchestra, the string section, or a quartet that plays weddings on weekends? Each whole makes the violinist a different part.

Where They Meet

All five definitions would call the orchestra a system. They agree on four points, though not every definition makes every point.

1. A system is not a pile. Meadows’ example is sand scattered on a road. Add sand or take some away, and it is still sand on a road (p. 12). Bertalanffy and Ackoff make the point from the other side. In a pile, the parts act independently.

2. A system is held together by its connections. Bertalanffy says “interacting,” Meadows says “interconnected,” and Senge says “interrelationships rather than things.” Ackoff’s parts depend on other parts. The Cabreras relate one thing to another. All five point at the links between the parts.

3. A system changes over time. Meadows writes that systems produce “their own pattern of behavior over time” (p. 2).

4. A system is for something. Meadows’ system “achieves something.” The malaria program was for killing mosquitoes. The longhouse was for a dry, safe place to sleep.

Grapefruit juice and some cholesterol pills show all four points. The pill and the juice are not a pile: together, they do something neither does alone. They are held together by an enzyme in the gut that normally breaks the drug down. Grapefruit juice blocks it. A statistician has a name for this: an interaction effect. Two things interact when the effect of one depends on the level of the other. Here, the pill’s effect depends on how much juice someone drinks.

The change also builds over time. The juice disables the enzyme, and the gut has to make new enzyme to replace it. A day after one glass, a quarter of the effect is still there. In one study, three glasses a day for a week doubled the effect on a blood pressure drug. Too much of the cholesterol drug stays in the body. And judged by what it does, the pair is no longer just a cholesterol treatment. It also raises the risk of liver and muscle damage. This is the first question from the opening. What else is connected to this part? For the cholesterol pill, the answer is a glass of juice.

How a System Moves

Yesterday’s glass of juice is still at work today. A credit card has a delay too: the spending happens now, and the bill comes weeks later. The bill can also push back on the spending that made it. Meadows calls it feedback when a change comes back around to push on itself.

There are two kinds of feedback loop, and the same card shows both. A reinforcing loop feeds itself. Interest adds to the debt, and the bigger debt earns more interest. Meadows calls this kind “amplifying, reinforcing, self-multiplying, snowballing” (p. 30). A balancing loop pulls a system back toward where it was. The monthly statement shows the balance, and the cardholder cuts back. Meadows calls balancing loops “both sources of stability and sources of resistance to change” (p. 30).

The card’s delay is a few weeks. In Sarawak, the rats took years to come. A balancing loop with a delay can overshoot and swing back. Someone who opens a frightening bill cuts spending too hard, then splurges when the next bill looks fine. A statistician would see that swing in the data as a cycle. Months close together look alike. Months half a cycle apart move in opposite directions.

This answers the second question from the opening. What does this part keep in check? The answer is usually a balancing loop. Balancing loops are the easiest part of a system to miss, because when they work, nothing happens. Swap the paper statement for an app nobody opens, and the balancing loop is gone. The interest keeps growing.

Why Ask Before the Fix

In Sarawak, every link the spray broke was a balancing loop. Without the wasps, nothing held the caterpillars back, and the roofs sagged. Without the cats, nothing held the rats back, and they reached the rice. The twenty-three cats in wicker baskets were a balancing loop, flown back in by hand.

The malaria program counted mosquitoes. It did not count wasps, roofs, or cats.

The five definitions disagree on one point. For Bertalanffy, a system is out in the world, whether or not anyone maps it. For the thinkers after him, it is also a map someone draws, and that person decides where it ends. Meadows wrote that “boundaries are of our own making” (p. 99). Sarawak shows both. The wasps were real whether anyone counted them or not. Whether they got counted was up to the people drawing the map.

No program can count every insect in Borneo, so something always gets left off. The people who live with what was left off tend to notice first. In Sarawak, those people were the villagers. That is the third question from the opening. Who decided what counts, and what did they leave out?

None of the three questions says to skip the fix. Houston may still have needed its lanes. The cheaper house may still be the right one. The questions add one step before each fix. For the lanes, the step is asking who will move in along the new road. For the house, it is counting the hour each way in the car, and the Friday drinks it will cost.

A Closing Invitation. Every fix in this piece worked the way the spray did. It solved the problem it was aimed at. Its cost came later, and somewhere else. The three questions work on your own fixes too.

1. Notice the sag. Pick the fix that worked and still cost you the most. The cheaper car that kept breaking down. The rule at home that ended one fight and started a quieter one. When the cost came, what did it look or sound like? A knock from the engine on cold mornings. A door shut a little harder. How long did it take you to notice?
2. Find the wasp. What did the old way keep in check without anyone noticing? The coworker who caught mistakes before they went out, until the day they left. The weekly call with an old friend that kept small worries small. Can you bring it back this week, the way the cats were flown in?
3. Walk to the roof before the next spray. Take the decision in front of you now: a job offer, a new hire, a change to how your team works. Who will live with it a year from now? Did anyone ask them? Ask them before you decide.

Over Bario in 1960, the baskets came down under their parachutes while hundreds of villagers watched. Twenty-three cats were on their way to answer the question about the spray, years late.

Where This Came From

Each of the five definitions comes from one of four waves of systems thinking. The first wave, from the 1950s, wanted to predict and steer. It brought Bertalanffy’s general system theory, Norbert Wiener’s cybernetics, and Jay Forrester’s system dynamics. A first-wave team would have modeled the village: so many cats per rat, so many wasps per caterpillar. The second wave, from the 1970s, began when people inside a system wanted different things from it. A second-wave team would have asked whose village it was. The third wave, from the 1980s, asked the third question: who gets left out. A third-wave team would have started with the families under the thatch. The fourth wave, proposed in 2021 by the Cabreras and Gerald Midgley, is still unsettled.

Figure 3. The four waves of systems thinking, after Cabrera, Cabrera and Midgley (2021).

Intellectual Honesty Note. Four readings are this piece’s own. Two are about Sarawak: the malaria teams asking how to stop the mosquito, and the story as broken balancing loops. The other two are the malaria program and the longhouse as two purposes, and the grapefruit pair as an interaction effect. The cheaper house is a hypothetical. The fourteen thousand cats of later retellings do not appear in the 1960 press. The video in Figure 1 tells the popular version, which dates the cat drop to the 1950s and adds plague; this piece follows the 1960 record. Tom Harrisson’s account, that the cats ate cockroaches killed by DDT, is unconfirmed. Other accounts have the cats licking DDT off their paws. Senge’s page number comes from later citations. The wave dates are approximate, and the 2021 chapter went unchecked.

References

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