By Malia Mendez, Los Angeles Times

According to relationship scientist Paul Eastwick, online dating is a market where there are dramatic winners and losers. “I think our modern existence happens to pull from modes of interaction that really amp up the importance of mate value,” Eastwick said. “But it does not have to be this way, and for a long time, it was not this way.”

This is the genesis of Eastwick’s decades-long research about how people initiate and maintain close relationships. His new book “Bonded by Evolution: The New Science of Love and Connection” argues against evolutionary psychology’s philosophy of dating and relationships — debunking ideas like money matters most to women, looks matter most to men and everyone has an inherent objective “mate value.” In his work, the University of California Davis psychology professor offers a dating and relationships alternative in which compatibility trumps all.

His new book “Bonded by Evolution: The New Science of Love and Connection” argues against evolutionary psychology’s philosophy of dating and relationships— debunking ideas like money matters most to women, looks matter most to men and everyone has an inherent objective “mate value.” (Handout/Crown/TNS)

Since the dawn of his career, Eastwick has had more than one bone to pick with evolutionary psychology.

The theoretical approach, which studies human behavior, cognition and emotions as products of natural selection, depicts relationship formation as sales-like, highly gendered and strategy-based. That model, which Eastwick calls the “EvoScript,” has never squared with his view of close relationships.

The researcher has long viewed the EvoScript as outdated and exaggerated if not completely incorrect. But it was only a few years ago, when online communities of so-called incels started latching onto evolutionary psychology’s story of close relationships that he began to see the EvoScript as dangerous.

“It was upon realizing that there’s this fun house mirror version of [evolutionary] psych out there that I was like, I think it’s time,” Eastwick said. “There was a wake-up call for me that, we need a scientific book out there that’s going to bring the most contemporary science to people.”

In his work, Eastwick argues that desirability is subjective and unpredictable — and that all anyone really wants is a secure attachment bond that sustains them through good and bad seasons.

The Times talked to Eastwick about how to reimagine the dating “numbers game,” tips for better dates and why men and women ultimately want the same thing.

This interview has been condensed and edited for clarity.

You write in your book that “online dating can bring the worst parts of dating to the fore by exaggerating gender differences and making you feel like a clearance item at the bottom of the bin.” What are the long-term and short-term psychological effects of that on people as they go through their dating lives?

“It makes dating feel a little bit like a job, like you’re making sales pitches, and you can set your sights high, but ultimately you’re going to have to settle. It makes the whole thing feel like you’re trying to get a deal, and I just think these are bad metaphors, especially if we want to be happy in the long run. But there is a slow burn approach that feels more like finding connection, opening oneself up, spending time getting to know other people sometimes just for the sake of getting to know other people. Part of what I want to do in the book is remind people that there are other ways — and those other ways also happen to be more democratic, for lack of a better word there — that pull for more idiosyncrasy and give more people a chance to find partners that will really appeal to them.

If you’re trying to tackle the EvoScript, as you call it, what is your thesis about dating?

My thesis is that, if we want to think about the nature of human relationships, how did people evolve to form close relationships, I would describe it as a search for compatibility in small groups. What people classically have looked for and what classically makes for the best, most satisfying pairings are finding and building something compatible with another person from a pretty limited range of options.

OK , so I need to meet people in person. I need to make friend groups. Where do you go to do that now, when things are expensive and a lot of life is online?

For somebody who’s heterosexual, if you’re a woman, it’s like, “OK, where am I gonna meet guys? Where are the guys out there?” Don’t worry if the guys are going to be there, because oftentimes when people meet partners, it’s like, friends of friends of friends, right? It’s all making connections. Maybe it’s sports, maybe it’s activities, maybe it’s a cooking class, maybe it’s a dancing class. Maybe it’s just calling back up the people from your last job that you haven’t seen in a while, getting together over drinks and making it a regular thing. I get it, people are really busy, and everything online is a draw. But the importance of hanging out with people in person, those loose acquaintances, that’s where so much of the magic happens.

People talk a lot about how it’s just a numbers game: You have to go on more dates, you have to swipe on more people. What’s your response to that?

It is a numbers game, but maybe, let’s think about the numbers like this. Rather than numbers of people, it’s numbers of interactions. So you could meet 12 people one time, or you could meet three people four times. I choose the second one, right? Meet fewer people more times. We’re still talking about numbers. We’re still talking about how much time you’re out there interacting with people, figuring out whether you click. But 20-minute coffee dates really pull for a snap judgment. In a perfect world, swiping right on somebody would mean I’m going to do a coffee date with you, and then we’re going to go to some interactive class, and then we’re going to go to a concert and I’m going to spend time with you in all three settings and kind of see how that goes in total and then assess it. So it’s not that the numbers game is misguided, you do have to get out there and try different things, but we often think, “Oh, I can just sample people really briefly, and eventually I’ll get lucky.” The smaller those samples are, the more painful this whole thing gets.

Coffee dates feel like interviews to me. But from a scientific standpoint, why do you recommend an activity-based date over the classic coffee date?

The best evidence that we have for what can you do to make yourself more appealing to someone is not to share your CV and impress them with those details. Do something that reveals a little bit about who you are, how you interact, how you relate to the world, and, best of all, something a little bit vulnerable about yourself. The 36 Questions test, sometimes called the Fast Friends procedure, is truly the best tool we have. Within an hour or two of something interactive, people have gotten to the point where they’re willing to talk about things that they regret, or things that they really like about the other person that they’ve just gotten to know. And this is all in that Fast Friends procedure. So when I think about people doing activities where their attention isn’t just on interview mode, it’s like, “Oh, we’re tackling something together,” it really decreases that self-promotion instinct, which is usually misguided.

In your book, you call compatibility “curated, cultivated and constructed.” Does that mean, to you, that you can theoretically be compatible with anyone?

If you take this idea to its extreme, if you push me, ultimately I land on probably. And of all the things I say that people are going to be resistant to, I think that’s the one that people are like, “No.” Again, I go back to the people involved in small groups. They made relationships work with the limited number of options that were available, and because we are creatures who engage in motivated reasoning, it is very, very possible to be happy with who you’re with, but that does not mean that people just get to turn off all of the alternatives that exist. I think the best way to think about it is, I think a lot of pairs have compatibility potential, but I also think that the many decisions along the way matter a lot.

If the idea of romantic destiny is, as you call it in your book, “the weakest idea ever promoted by scientists,” what is your number-one dating myth you feel your personal research has debunked?

That men and women want different things out of partnerships, that they’re either pulling for different traits or look like these totally different entities, I just think the evidence for this is completely wrong. We see differences when you ask men and women, “What do you want in a partner?” But when you look at the attributes that actually matter, it’s really amazing the extent to which men and women are similar. And it’s not to say that there are no differences, like there is a difference in the strength of the sex drive thing. It’s smaller than people say, but it is there. But if you think about, what do men and women want out of a close relationship? What they really want is somebody who’s going to be supportive, is going to celebrate my successes and is going to have my back.

How do people practically apply that in their dating lives?

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Refocusing on attachment, I hope that reduces some of the heteropessimism out there in the world. We have arrived at this very bleak view of relations between men and women, like we see the world differently, we’re just always at odds. And boy, when you come at relationships with this attachment frame, and you look at the things that make people happy, men and women can absolutely build beautiful things working together, and they often do. Because we are creatures who attach, there is so much potential for genuine connection over a sustained period of time.

Do you have any predictions for what the future of dating might look like?

It certainly feels like people are getting tired of the apps and that they’re looking for more ways to socialize in person. I think that’s wonderful. I worry about what AI is going to do, like, is that going to feel so real that it causes our interactional muscles to atrophy? That’s the big question mark on the horizon. I’m not here to be grandpa, but I also hope that we don’t totally lose the ability to interact with real people.

©2026 Los Angeles Times. Visit at latimes.com. Distributed by Tribune Content Agency, LLC.

Edward Lotterman

Managing the money supply of a modern economy is a dirty job, but somebody has to do it.

For some 110 years, we have had an operating central bank, the Federal Reserve system, to do that. It could reduce harm to businesses and households from bank failures. Well thought-out, it could increase or decrease the money supply as needed to maintain credit availability without inflation.

So how has it done?

The answer is “pretty well,” at least for the first 85 years. The Fed made mistakes, especially in the 1930s and 1970s, but so did virtually all central banks around the world. Yes, central bank mistakes contributed to the Great Depression, but the causes of that went deeper.

Ditto for the high inflations hitting most economies in the 1970s. The Fed under chairs Arthur Burns and G. William Miller let the money supply grow far too fast. But there also were commodity-price shocks. Prevailing economic doctrines proved flawed. However, by the 1990s, growth was strong, unemployment low and prices stable. Yes, many farm lenders had failed, as did a class of banks called “savings and loans.” But these problems had been handled. On the whole, the economy during this period was in fine fettle. But harsher challenges would present in the new millennium.

Most recently — and current Chair Jerome Powell would probably acknowledge this — the Fed misjudged how long the sharp inflation following COVID would last, and this became a political liability for President Donald Trump’s first term, and more dramatically for his successor, Joe Biden.

To understand the Fed’s role in all of this, one must understand that the key function of any central bank is to manage the money supply — not “set” interest rates. Nearly all the general public doesn’t get this. News reports stating that the Fed raised or lowered interest rates don’t tell us what’s really happening — that the central bank is actually increasing or decreasing the amount of money in circulation. Hardly anyone in politics or the media adequately explains the correlation, including virtually all reporters covering finance as well as general news. This also points to failures in the teaching of economics.

An often-used analogy is that if a driver decides to move the speedometer from 50 to 70, they have to step harder on the gas. It is the flow of fuel to the motor that is important. The speedometer only indicates the result. In the same way the flow of the money supply determines interest rates.

Next, one must understand key indicators showing how much money is in the economy. The “money supply” consists of currency, physical bills or coins, plus bank deposits. Subdivisions to various degrees, depend on which deposits count, from simple checking, to long-term CDs. The Fed has great influence over the money supply, but does not “control” it.

The “monetary base” consists of currency plus bank reserves. These are deposits not loaned out. The Fed can control this closely. Historically here and in many other countries yet today, the “reserve ratio,” or minimum percentage of deposits that must be kept in reserve, is a key variable. In the U.S. there no longer is a reserve requirement but prudent banks still keep reserves.

The money supply and monetary base look at assets, money held by banks or the general public. But the point of view of the central bank also is key. It can create or destroy money by changing the level of reserves in a nation’s banking system as a whole. This leads to an important point that takes up an entire econ class session to explain. So just understand that in a system of “fractional reserve banking,” an increase in total banking reserves by a central bank causes a much greater increase in the money supply.

A central bank has a number of ways to increase reserves.

First, it can change the required reserve ratio. Decreasing it lets banks lend more. Increasing it does the opposite. This was important when the Fed was established and still true in much of the world, but is moot for the U.S. because we no longer have required minimums.

Second, the Fed can make direct loans to banks at its “discount window.” The framers of the Federal Reserve saw this as its central function. (This was described in the Feb. 15 column.) Again, understand that when the Fed makes such loans, it creates the money out of thin air. It does not come from the U.S. Treasury or anywhere else. And when such loans are repaid, money goes poof and disappears.

Third, it can inject new money into the economy by going into open bond markets where bonds issued by the U.S. Treasury, corporations, or anyone else are traded. To increase the money supply, it buys bonds by paying for them with newly created money. To decrease money in the system it sells bonds and the money received disappears.

Historically, the Fed only bought and sold U.S. Treasury bonds. This was extended to include “repurchase agreements” or “repos” and “reverse repos.” These are derivative securities based on Treasury bonds.

Such central bank buying and selling of bonds to increase and decrease bank reserves, and thus the money supply, is called “open-market operations.” That is why Fed officials who decide how much to buy or sell make up the “Federal Open-Market Committee.” It includes the seven members of the Board of Governors that includes a Chair, currently Powell, plus the 12 presidents of Fed district banks. However, while all participate, only five of the 12 vote in any given year.

Such buying and selling is analogous to feeding more or less gas to a car. The FOMC chooses a short term interest rate to target just as a driver decides to drive at 55 mph or 70 mph. To raise interest rates, the Fed sells bonds. To lower them, it buys more.

The original Federal Reserve Act did not include such bond market actions. But discount window lending depended on banks seeking loans. If the economy needed more liquidity, but no banks came to borrow, available money did not change. Benjamin Strong, president of the New York Fed, implemented open-market operations in the 1920s. The New Deal Banking Acts of 1933 and 1935 incorporated them and created the current Fed structure. Over time, discount window lending dwindled and open-market operations dominated Fed control of the money supply.

The ability to create new bank reserves and thus more money is how central banks quelch financial crises of the type that plagued the U.S. economy prior to 1913. It can stop chains of bank failures that were once common. But this creates huge danger. If any central bank steps in too often and too drastically, it creates “moral hazard,” incentivizing banks to lend carelessly and excessively. Large banks that are deemed “too big to fail” get a “heads we win and tails the Fed loses” mentality. Which brings us to today. Such perverse incentives have plagued the U.S. financial system for 40 years.

Yes, the Fed failed to intervene effectively in the 1930s, contributing to the Great Depression. It let the money supply grow too fast in the 1970s, contributing to inflation. But then, in 1984, when Continental Illinois, the seventh largest U.S. bank, was going bust, the Fed and the Federal Deposit Insurance Corp. intervened to bail it out. This led critics, especially at the Minneapolis Federal Reserve and in key university economics departments, to warn of the enormous moral hazard thus created.

They were right. New legislation was intended to limit this, but in 1998, the Fed stepped in when a hedge fund, Long Term Capital Management, went broke. It later flooded the economy with liquidity after 9/11. And then, when a financial crisis in very short term lending broke out in August 2007, followed by the failure of investment banks Bear Stearns in March 2008, and Lehman Brothers that October, a panicked Fed opened money taps to an unprecedented degree. This included creating ways to directly buy mortgage-backed securities rather than only Treasury bonds.

It more than tripled its holdings of securities, Treasury and private, from about $900 billion in August 2008 to $2.9 trillion in August 2011. Then, fighting a recession that regulatory failures had helped create, it lifted this total to $4.5 trillion by late 2014. Pausing, it let its holdings ebb to $3.6 trillion in mid-2019. But the outbreak of COVID in 2020 prompted even greater injections, reaching $7 trillion in June 2020 and $9 trillion in mid-2022. What happens to all this extra money? In this case, it caused the inflation that ejected Trump, then Biden four years later, from office and stoked the roaring stock market, crypto, “private debt” and “private equity” bubbles dominating financial news today, as well as inflated house prices benefitting baby boomers at the cost of anyone younger. In short, moral hazard on steroids.

The monetary base has fallen from a peak in late 2021, but remains nearly seven times as high as in March 2008. The broader M2 money supply, currently at $22.4 trillion, is three times as high over the same period. Gross domestic product, the total value of all goods and services produced, has only doubled.

Kevin Warsh, Trump’s nominee to be the next Fed chair, has been outspoken in calling for the Fed’s balance sheet to be reduced. This means selling off many of the securities the Fed gorged on in a stair-step of crises over the last 18 years. Yet such a move would raise interest rates and slow the economy. Trump wants him to do the opposite. How this will play out is unknown.

The media, blind to the central role of the money supply, fails to see this conundrum. We’ve gotten pretty good at predicting and responding to disastrous weather events, but nearly everyone ignores looming financial storms to our perhaps greater, and longer-lasting, peril.

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St. Paul economist and writer Edward Lotterman can be reached at stpaul@edlotterman.com.

By Darius Tahir, Lauren Sausser, KFF Health News

It’s the rare policy question that unites Republican Gov. Ron DeSantis of Florida and the Democratic-led Maryland government against President Donald Trump and Gov. Gavin Newsom of California: How should health insurers use AI?

Regulating artificial intelligence, especially its use by health insurers, is becoming a politically divisive topic, and it’s scrambling traditional partisan lines.

Boosters, led by Trump, are not only pushing its integration into government, as in Medicare’s experiment using AI in prior authorization, but also trying to stop others from building curbs and guardrails. A December executive order seeks to preempt most state efforts to govern AI, describing “a race with adversaries for supremacy” in a new “technological revolution.”

“To win, United States AI companies must be free to innovate without cumbersome regulation,” Trump’s order said. “But excessive State regulation thwarts this imperative.”

Across the nation, states are in revolt. At least four — Arizona, Maryland, Nebraska, and Texas — enacted legislation last year reining in the use of AI in health insurance. Two others, Illinois and California, enacted bills the year before.

Legislators in Rhode Island plan to try again this year after a bill requiring regulators to collect data on technology use failed to clear both chambers last year. A bill in North Carolina requiring insurers not to use AI as the sole basis of a coverage decision attracted significant interest from Republican legislators last year.

DeSantis, a former GOP presidential candidate, has rolled out an “AI Bill of Rights,” whose provisions include restrictions on its use in processing insurance claims and a requirement allowing a state regulatory body to inspect algorithms.

“We have a responsibility to ensure that new technologies develop in ways that are moral and ethical, in ways that reinforce our American values, not in ways that erode them,” DeSantis said during his State of the State address in January.

Ripe for Regulation

Polling shows Americans are skeptical of AI. A December poll from Fox News found 63% of voters describe themselves as “very” or “extremely” concerned about artificial intelligence, including majorities across the political spectrum. Nearly two-thirds of Democrats and just over 3 in 5 Republicans said they had qualms about AI.

Health insurers’ tactics to hold down costs also trouble the public; a January poll from KFF found widespread discontent over issues like prior authorization. (KFF is a health information nonprofit that includes KFF Health News.) Reporting from ProPublica and other news outlets in recent years has highlighted the use of algorithms to rapidly deny insurance claims or prior authorization requests, apparently with little review by a doctor.

Last month, the House Ways and Means Committee hauled in executives from Cigna, UnitedHealth Group, and other major health insurers to address concerns about affordability. When pressed, the executives either denied or avoided talking about using the most advanced technology to reject authorization requests or toss out claims.

AI is “never used for a denial,” Cigna CEO David Cordani told lawmakers. Like others in the health insurance industry, the company is being sued for its methods of denying claims, as spotlighted by ProPublica. Cigna spokesperson Justine Sessions said the company’s claims-denial process “is not powered by AI.”

Indeed, companies are at pains to frame AI as a loyal servant. Optum, part of health giant UnitedHealth Group, announced Feb. 4 that it was rolling out tech-powered prior authorization, with plenty of mentions of speedier approvals.

“We’re transforming the prior authorization process to address the friction it causes,” John Kontor, a senior vice president at Optum, said in a press release.

Still, Alex Bores, a computer scientist and New York Assembly member prominent in the state’s legislative debate over AI, which culminated in a comprehensive bill governing the technology, said AI is a natural field to regulate.

“So many people already find the answers that they’re getting from their insurance companies to be inscrutable,” said Bores, a Democrat who is running for Congress. “Adding in a layer that cannot by its nature explain itself doesn’t seem like it’ll be helpful there.”

At least some people in medicine — doctors, for example — are cheering legislators and regulators on. The American Medical Association “supports state regulations seeking greater accountability and transparency from commercial health insurers that use AI and machine learning tools to review prior authorization requests,” said John Whyte, the organization’s CEO.

Whyte said insurers already use AI and “doctors still face delayed patient care, opaque insurer decisions, inconsistent authorization rules, and crushing administrative work.”

Insurers Push Back

With legislation approved or pending in at least nine states, it’s unclear how much of an effect the state laws will have, said University of Minnesota law professor Daniel Schwarcz. States can’t regulate “self-insured” plans, which are used by many employers; only the federal government has that power.

But there are deeper issues, Schwarcz said: Most of the state legislation he’s seen would require a human to sign off on any decision proposed by AI but doesn’t specify what that means.

The laws don’t offer a clear framework for understanding how much review is enough, and over time humans tend to become a little lazy and simply sign off on any suggestions by a computer, he said.

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Still, insurers view the spate of bills as a problem. “Broadly speaking, regulatory burden is real,” said Dan Jones, senior vice president for federal affairs at the Alliance of Community Health Plans, a trade group for some nonprofit health insurers. If insurers spend more time working through a patchwork of state and federal laws, he continued, that means “less time that can be spent and invested into what we’re intended to be doing, which is focusing on making sure that patients are getting the right access to care.”

Linda Ujifusa, a Democratic state senator in Rhode Island, said insurers came out last year against the bill she sponsored to restrict AI use in coverage denials. It passed in one chamber, though not the other.

“There’s tremendous opposition” to anything that regulates tactics such as prior authorization, she said, and “tremendous opposition” to identifying intermediaries such as private insurers or pharmacy benefit managers “as a problem.”

In a letter criticizing the bill, AHIP, an insurer trade group, advocated for “balanced policies that promote innovation while protecting patients.”

“Health plans recognize that AI has the potential to drive better health care outcomes — enhancing patient experience, closing gaps in care, accelerating innovation, and reducing administrative burden and costs to improve the focus on patient care,” Chris Bond, an AHIP spokesperson, told KFF Health News. And, he continued, they need a “consistent, national approach anchored in a comprehensive federal AI policy framework.”

Seeking Balance

In California, Newsom has signed some laws regulating AI, including one requiring health insurers to ensure their algorithms are fairly and equitably applied. But the Democratic governor has vetoed others with a broader approach, such as a bill including more mandates about how the technology must work and requirements to disclose its use to regulators, clinicians, and patients upon request.

Chris Micheli, a Sacramento-based lobbyist, said the governor likely wants to ensure the state budget — consistently powered by outsize stock market gains, especially from tech companies — stays flush. That necessitates balance.

Newsom is trying to “ensure that financial spigot continues, and at the same time ensure that there are some protections for California consumers,” he said. He added insurers believe they’re subject to a welter of regulations already.

The Trump administration seems persuaded. The president’s recent executive order proposed to sue and restrict certain federal funding for any state that enacts what it characterized as “excessive” state regulation — with some exceptions, including for policies that protect children.

That order is possibly unconstitutional, said Carmel Shachar, a health policy scholar at Harvard Law School. The source of preemption authority is generally Congress, she said, and federal lawmakers twice took up, but ultimately declined to pass, a provision barring states from regulating AI.

“Based on our previous understanding of federalism and the balance of powers between Congress and the executive, a challenge here would be very likely to succeed,” Shachar said.

Some lawmakers view Trump’s order skeptically at best, noting the administration has been removing guardrails, and preventing others from erecting them, to an extreme degree.

“There isn’t really a question of, should it be federal or should it be state right now?” Bores said. “The question is, should it be state or not at all?”

©2026 KFF Health News. Distributed by Tribune Content Agency, LLC.

DICAMILLO/LANGEMO: Award-winning Minnesota writer Kate DiCamillo and musician Jimmi Langemo team up for stories, music, inspiration and connection to benefit Joyce Uptown Foodshelf. Tickets required. For information, visit redballoonbookshop.com. 1 p.m. March 1, Judson Memorial Baptist Church, 4101 Harriet Ave., Mpls.

NINA McCONIGLEY: Colorado-based writer introduces her debut novel “How to Commit a Postcolonial Murder,” in conversation with Minnesotan V.V. Ganeshananthan. Free. 2 p.m. Saturday, Plymouth library, 15700 36th Ave. N., Plymouth, in partnership with Valley Bookseller of Stillwater.

SCOTT MESLOW: Presents “A Place Both Wonderful and Strange: The Extraordinary Untold History of Twin Peaks.” 7 p.m. Wednesday, Magers & Quinn, 3038 Hennepin Ave. S., Mpls.

IMANI PERRY: National Book Award winner of “South to America,” which argues you must understand the South to understand America, and “Black in Blues: How a Color Tells the Story of My People” discusses her writing in Friends of Hennepin County Library’s Pen Pals series. 7:30 p.m. Thursday, 11 a.m. Friday. Hopkins Center for the Arts, 1111 Mainstreet, Hopkins. $59-$49 in-person, $35 virtual. Call: 612-542-8112.

What else is going on

(Courtesy of Routledge)

Christopher Danielson, St. Paul author and educator, won the national Simons Laufer Mathematical Sciences Institute Mathical Book Prize for his picture book “How Did You Count?” for grades K-2. Images were taken by Minneapolis photographer and educator Asha Belk.

In the announcement the Mathical committee writes: “Young readers … are invited to share their thought process — and sometimes whimsical ways — for tallying things up — as they explore colorful photos featuring mathematical groups of everyday objects.”

Danielson, a former teacher at Normandale Community College and in St. Paul public schools, is director of strategic projects at CPM Educational Program. He’s the founder of Math On-a-Stick, an outdoor family math play event that takes place during the Minnesota State Fair. The Mathical prize is awarded in partnership with the National Council of Teachers of English, and the National Council of Teachers of Mathematics in coordination with Children’s Book Council. The winning book also has a companion teachers’ guide.

Attention all Barbara Kingsolver fans (and who isn’t?) Her new novel, “Partita,” releases in October. It’s the story of a gifted woman pianist who finds solace in music after her brother’s death. When she meets a mysterious man her life takes a turn to self-discovery and love.

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