In this way, Musk isn’t just another player in the game. He’s reshaping the very field on which democracy operates. By controlling the infrastructure of public communication while simultaneously directing government functions through DOGE, he demonstrates how private power can capture public institutions without the messy business of electoral politics. It’s a techno-autocratic playbook that circumvents traditional democratic safeguards entirely—and worse, makes it look like innovation rather than what it truly is: an old-fashioned power grab using new technological tools.

The historical pattern is unmistakable for those willing to see it. Every pathway to autocracy begins with the deliberate erosion of the idea that power must explain and justify itself. Viktor Orbán didn’t announce his intention to dismantle Hungarian democracy—he simply treated democratic constraints as optional, selectively ignoring them while maintaining their outward forms. Vladimir Putin didn’t openly declare his rejection of legal limits—he simply acted as if they didn’t apply to him, daring anyone to stop him. The playbook isn’t complicated: treat constraints as suggestions, norms as obsolete traditions, and accountability as an unnecessary courtesy.

What makes our current moment particularly dangerous is how this approach has been intellectualized and justified through sophisticated theorizing. Curtis Yarvin doesn’t just critique democratic inefficiency—he provides a comprehensive framework for rejecting the very premise that power should be bound by anything other than its own exercise. His neoreactionary vision, where governance is reimagined as corporate management rather than democratic deliberation, offers intellectual cover for what amounts to the systematic dismantling of constitutional constraints.

For the first time in decades, European leaders face a US commander-in-chief who doesn’t care for Cold War-era pieties

If Donald Trump’s earlier characterization of Volodymyr Zelenskyy as a “dictator” and his repeated refusal to offer any disobliging description of Vladimir Putin had left any mystery as to where his affinity lies, he eliminated all doubt within 10 minutes on Friday at the tail end of a supposed diplomatic breakthrough in U.S.-Ukrainian relations. Joining with his vice president, JD Vance, in a tag-team humiliation of the Ukrainian president, Trump openly expressed his kinship with Putin as a fellow victim in “a phony witch hunt,” presumably referring to the well-established Russian intelligence and influence campaign to get Trump elected the first time. The American president further blamed Zelenskyy’s “tremendous hatred” of Putin as the main obstacle to peace rather than Russia’s continued bombardment or occupation of Ukrainian cities. Ukraine’s future as a sovereign country, Trump indicated, was not a matter of strategic imperative or American interest or principle, but rather a favor only Trump could bestow upon it if Zelenskyy played his “cards” right. (Casino metaphors are never far from Trump’s lips.)

For Europeans watching, one thing became clear. Washington now regards Kyiv as an adversary from which concessions must be wrung and terms of conditional surrender imposed, while it sees Moscow as an ally-in-the-making and the more justifiably aggrieved party in the war of conquest Moscow started three years ago.

Reaction in Europe was swift and virtually unanimous, with leaders rushing to social media to offer their unqualified support for Ukraine and Zelenskyy. Kaja Kallas, the former Estonian prime minister and new EU foreign minister, offered the starkest rebuke of the United States and Trump personally: “Today it became clear,” she posted on X, “that the free world needs a new leader. It’s up to us, Europeans, to take this challenge.”

For years, musicians have complained that they can’t make a living on the royalties from music streaming sites like Spotify. The way those royalties are distributed has been a point of contention for many artists, including Taylor Swift who pulled her catalog from Spotify in the 2010s to protest its low royalties. Today, an artist gets paid between $0.003 – $0.005 per stream.

Spotify’s business relies on music from millions of artists around the world, but it is neither governed nor controlled by those artists. Its governance, as a public company, looks far different from that of a local co-op or credit union.

But such cooperative business models might represent the future of the streaming industry. New streaming entrants like Resonate are formed as data cooperatives (co-ops), where profits are more fairly distributed and control is more evenly shared.

Rapid technological advancements and the rise of a data-driven economy have led to the creation of data co-ops, which provide individuals with new opportunities to own and control their personal data.

In this week’s newsletter we draw from a report published in January, How Can Data Cooperatives Help Build a Fair Data Economy?, by Project Liberty Institute and Decentralization Research Center.

Drawing on interviews with 16 key experts in data cooperatives, digital rights, data governance, and the digital economy, the report summarizes the current state of data co-ops and sets the agenda to examine the potential for cooperatives to help transform today’s digital economy.

// What is a data co-op?

One in eight people globally is a member of a co-op. That’s 12% of humanity. In total, three million co-ops employ nearly 10% of the global adult workforce, or 280 million people.

Co-ops have been around for hundreds of years. They originated in the 18th century. Today, major companies like REI, Land O’Lakes, Best Western, and even the AP (Associated Press) are all co-ops.

The International Cooperative Alliance defines a cooperative as “an autonomous association of persons united voluntarily to meet their common economic, social, and cultural needs and aspirations through a jointly owned and democratically controlled enterprise.”

Building upon this definition, Project Liberty Institute defines a data cooperative as “a form of cooperative organization based on the ownership and governance of data.”

Here is how it works:

1. Members of a cooperative consent to have a third party (the co-op) hold copies of their data.
2. The third-party entity is cooperatively governed by its members who participate in decision-making and oversight.
3. This entity can safeguard its members’ data or represent its members in negotiations over how their data is used and sold.

It’s a simple concept, but the implications are enormous—particularly when considering how data is owned and governed on the internet today.

Vast amounts of data are owned and controlled by a few large tech companies that practice “extractive, feudalistic business models.” The billions of users on platforms like Facebook or TikTok don’t own or control the content they produce, and the data generated from their online activity is often harnessed by profit-seeking, attention-grabbing algorithms to drive engagement. The result? An internet defined by poor data privacy, monopolistic business practices, and hyper-centralized control.

A data co-op upends this and returns control to users to manage their data: Members of a data co-op actively participate in democratic governance, voting on how their data is used, managed, and monetized.

Data co-ops differ from data trusts (a more top-down structure where trustees make decisions on behalf of people who contribute their data) and data commons (a structure where data is pooled and shared as a common resource but often lacking individual rights).

“Data co-ops give individuals a financial stake, distributing economic returns directly to members,” the report noted. “Unlike data trusts and data commons, which focus on protection or collective access, co-ops uniquely prioritize member ownership, autonomy, and shared prosperity.”

However, the best model for ensuring that people have voice, choice, and stake in their digital lives may lie at the crossroads of these models. Looking at these hybrid models is precisely what PLI and DRC will explore in the second phase of their collaboration.

// Examples of data co-ops

Mei Lin Fung, the Co-Founder of People-Centered Internet, believes that “Data co-ops are an idea whose time has come. Because we’re so aware now of the consequences of irresponsible data use.”

Here are five examples of data co-ops.

1. MiData is a health data cooperative that empowers individuals to securely store, manage, and control access to their personal health data.
2. Swash is a browser extension and digital wallet that allows its users to get paid for browsing the internet. Considered the largest data union in the world, it allows people to exercise their data rights and make money from the value of their data.
3. The Driver’s Seat Cooperative was a worker-owned ride-hailing platform aimed at distributed data governance and improved working conditions for gig-economy workers. However, the co-op model ended up not being financially sustainable, and it now exists as part of a research initiative at Princeton University.
4. Salus.coop is a co-op from the Catalonia region of Spain that pools members’ health data.

Sylvie Delacroix, the Inaugural Jeff Price Chair in Digital Law and Director of the Centre for Data Futures, believes that these early experiments in data co-ops will inform future models that could become more scalable.

“I think that in the future, we’re going to see a lot more experimentation with different models of data ownership and governance,” she said. “Data cooperatives are going to be one of the most promising models. But I think that we’re also going to see a lot of hybrid models, like data trusts and data commons. The key is going to be to find models that are both fair and sustainable.”

// Addressing the core challenges of data co-ops

The report highlighted insights from its 16 interviews on core challenges that data co-ops must address to be successful.

Together, these core challenges form an agenda for future research on designing and managing effective data co-ops. Here are four (but the report outlined several more):

1. Bridge the gap between theory and practice. The abundance of academic literature and conceptual frameworks surrounding data co-ops stands in stark contrast to the scarcity of successful operational models. A more pragmatic approach is needed that prioritizes building functional data cooperatives that deliver tangible benefits.
2. Interrogate the actual value of data. Many experts interviewed for the report challenged the idea that data holds intrinsic value. Its value is context-specific and depends on how it’s used. Finding these use cases is crucial for data co-ops to become financially sustainable.
3. Focus on aligning incentives. To ensure the success of data cooperatives, it’s essential to align incentives for both data contributors and data buyers. Beyond financial rewards, co-ops can offer members access to valuable insights derived from aggregated data, thereby enhancing their decision-making capabilities. Additionally, by pooling data, members can gain collective bargaining power, enabling more favorable negotiations with companies or institutions seeking to utilize their information. This collaborative approach not only fosters stronger community ties but also promotes the sharing of high-quality data, which in turn increases the cooperative’s overall value and revenue potential.
4. Establish better legal and regulatory frameworks. The lack of clear legal definitions and supportive policies creates challenges when setting up data co-ops. Better legal and regulatory frameworks at the local level will reduce the friction standing in the way of more experiments.

// The next step

On April 1st at the Decentralized Tech Summit at Georgetown University, Project Liberty Institute and Decentralization Research Center will convene a larger group of practitioners, technologists, and policymakers from across the cooperative, decentralized governance, and fair data realms to examine how cooperative business models might advance the goal of giving people a greater voice, choice, and stake in the digital economy. The result will be a roadmap for anyone looking to explore models of decentralized data agency.

In this way, Musk isn’t just another player in the game. He’s reshaping the very field on which democracy operates. By controlling the infrastructure of public communication while simultaneously directing government functions through DOGE, he demonstrates how private power can capture public institutions without the messy business of electoral politics. It’s a techno-autocratic playbook that circumvents traditional democratic safeguards entirely—and worse, makes it look like innovation rather than what it truly is: an old-fashioned power grab using new technological tools.

The historical pattern is unmistakable for those willing to see it. Every pathway to autocracy begins with the deliberate erosion of the idea that power must explain and justify itself. Viktor Orbán didn’t announce his intention to dismantle Hungarian democracy—he simply treated democratic constraints as optional, selectively ignoring them while maintaining their outward forms. Vladimir Putin didn’t openly declare his rejection of legal limits—he simply acted as if they didn’t apply to him, daring anyone to stop him. The playbook isn’t complicated: treat constraints as suggestions, norms as obsolete traditions, and accountability as an unnecessary courtesy.

What makes our current moment particularly dangerous is how this approach has been intellectualized and justified through sophisticated theorizing. Curtis Yarvin doesn’t just critique democratic inefficiency—he provides a comprehensive framework for rejecting the very premise that power should be bound by anything other than its own exercise. His neoreactionary vision, where governance is reimagined as corporate management rather than democratic deliberation, offers intellectual cover for what amounts to the systematic dismantling of constitutional constraints.

For the first time in decades, European leaders face a US commander-in-chief who doesn’t care for Cold War-era pieties

If Donald Trump’s earlier characterization of Volodymyr Zelenskyy as a “dictator” and his repeated refusal to offer any disobliging description of Vladimir Putin had left any mystery as to where his affinity lies, he eliminated all doubt within 10 minutes on Friday at the tail end of a supposed diplomatic breakthrough in U.S.-Ukrainian relations. Joining with his vice president, JD Vance, in a tag-team humiliation of the Ukrainian president, Trump openly expressed his kinship with Putin as a fellow victim in “a phony witch hunt,” presumably referring to the well-established Russian intelligence and influence campaign to get Trump elected the first time. The American president further blamed Zelenskyy’s “tremendous hatred” of Putin as the main obstacle to peace rather than Russia’s continued bombardment or occupation of Ukrainian cities. Ukraine’s future as a sovereign country, Trump indicated, was not a matter of strategic imperative or American interest or principle, but rather a favor only Trump could bestow upon it if Zelenskyy played his “cards” right. (Casino metaphors are never far from Trump’s lips.)

For Europeans watching, one thing became clear. Washington now regards Kyiv as an adversary from which concessions must be wrung and terms of conditional surrender imposed, while it sees Moscow as an ally-in-the-making and the more justifiably aggrieved party in the war of conquest Moscow started three years ago.

Reaction in Europe was swift and virtually unanimous, with leaders rushing to social media to offer their unqualified support for Ukraine and Zelenskyy. Kaja Kallas, the former Estonian prime minister and new EU foreign minister, offered the starkest rebuke of the United States and Trump personally: “Today it became clear,” she posted on X, “that the free world needs a new leader. It’s up to us, Europeans, to take this challenge.”

China’s peak is truly spectacular — a marvel of state capacity and resource mobilization never seen before on this planet. In just a few years, China built more high-speed rail than all other countries in the world combined. Its auto manufacturers are leapfrogging the developed world, seizing leadership in the EV industry of the future. China has produced so many solar panels and batteries that it has driven down the cost to be competitive with fossil fuels — a huge blow against climate change, despite all of China’s massive coal emissions, and a victory for global energy abundance. China’s cities are marvels of scale — forests of towering skyscrapers lit up with LEDs, cavernous malls filled with amazing restaurants and shops selling every possible modern convenience for cheap, vast highways and huge train stations. Even China’s policy mistakes and authoritarian overreaches inspire awe and dread — Zero Covid failed in the end, but it demonstrated an ability to control society down to the granular level that the Soviets would have envied.

But it’s still an open question whether China will be as creative as the great civilizations of the 20th century. Many people (including myself) compare early 21st century China to early 20th century America. But by the start of World War 1, Americans had already invented the airplane, the light bulb, the telephone, the record player, air conditioning, the automatic transmission, the machine gun, and the ballpoint pen. And the country had already given rise to jazz music, Hollywood movies, and lots of well-known literature. Japan’s cultural explosion came a bit later, but was every bit as impressive.

Once, I was part of a team of four people at 18F that saved the Department of Defense $500 million with a single, three-day project. 18F projects saved many millions of dollars as a matter of course, while delivering better results for Americans. Another time I was part of a two-person team (our billing worked out to about half an FTE, as I recall) that partnered with a court for 18 months to help them build, from scratch, an open source case management system to drive the operations of the entire court. The whole thing cost them just a few million bucks, vastly less than they’d been spending on their old system, and today their cost of operating it is a rounding error compared to their old infrastructure costs. All the work 18F did for all their agency partners was open source. Public money should produce public software, for public inspection.

In short, 18F works just how Musk and team pretend that they want government to work. But when his team found it, they destroyed it. 18F’s work is evidence that government works well, which undermines their message that it doesn’t. 18F’s parent agency, the U.S. General Services Administration, turns a profit as an agency. So it has to be destroyed too.

Democrats and Republicans don’t just disagree about policy; they disagree about what kind of political system we have

But we’re seeing the consequences of this every day right now. Republicans are governing in a way generally considered highly politically dangerous; the Trump administration is damaging the functioning of many government services people rely on (like Social Security!) and raising tariffs and laying off enough federal employees to trigger or worsen a recession. People notice stuff like that. Republicans are doing it anyway, under the belief that worrying about electability is a sucker’s game.

Meanwhile, Democrats’ responses to this have been all over the place. Some (particularly those in safe districts) are trying to raise the alarm about what the White House is doing. Others are mostly keeping quiet, or just focusing on a few minor issues, so they don’t look too extreme in next year’s midterm elections. Democrats are convinced of the importance of electability.

I would argue that these two perspectives are toxic in combination. You can have two parties worried about electability and the democratic system can still operate. You can have two intransigent parties and the democratic system can still operate, more or less. But one intransigent party and one party focused on electability means the country will continue to drift in one direction, away from public opinion, away from representative democracy.

The president lacks basic decency, and loathes people who do

Trade policy mavens sometimes use numeric shorthand that refers to relevant parts of the Trade Act of 1974, which spells out situations in which the president has the right to impose tariffs. There’s Section 201, giving temporary relief to an industry that is being hurt by an import surge. There’s Section 232, protecting an industry vital to national security. There’s Section 301, responding to subsidies or other practices that give foreign producers an unfair advantage.

The tariffs Donald Trump just imposed on Canada and Mexico — nations with whom he himself signed a free trade agreement — don’t fit any of these categories. Maybe they’re Section 000, meaning that the president has simply lost his mind. Or maybe they’re Section 666: he’s just evil.

The newspapers this morning all contain analysis pieces trying to explain why Trump is imposing 25 percent tariffs on Canada and Mexico. You can see the writers struggling, because this is a profoundly self-destructive move — it will impose huge, possibly devastating costs on U.S. manufacturing, while significantly raising the cost of living — without any visible justification. Yet the conventions of mainstream journalism make it hard to say directly that the president’s actions are just vindictive and senseless.

I hope Jeff Bezos lives up to what he’s saying he’ll do

Regardless, my instinct when I heard the announcement was to say that we should not leap to assume either interpretation of bad faith on Bezos’ part. Bad faith may be in play here and this may be the launch of a transformation of the opinion section into an arm of the MAGA movement.

But on their face, individual liberty and free markets are not bad causes to defend.

The libertarian magazine, Reason, is more right-wing than I am on many economic issues and also more left-wing than I am on various criminal justice issues. But it’s reliably a good read. And you’ll find there things like stories about how the Trump-appointed Acting US Attorney for DC is menacing free speech rights, how the Trump FTC appears to be contemplating a new era of anti-woke censorship, and about an alarming Montana bill that would criminalize interstate travel for the purposes of seeking an abortion.

For years, musicians have complained that they can’t make a living on the royalties from music streaming sites like Spotify. The way those royalties are distributed has been a point of contention for many artists, including Taylor Swift who pulled her catalog from Spotify in the 2010s to protest its low royalties. Today, an artist gets paid between $0.003 – $0.005 per stream.

Spotify’s business relies on music from millions of artists around the world, but it is neither governed nor controlled by those artists. Its governance, as a public company, looks far different from that of a local co-op or credit union.

But such cooperative business models might represent the future of the streaming industry. New streaming entrants like Resonate are formed as data cooperatives (co-ops), where profits are more fairly distributed and control is more evenly shared.

Rapid technological advancements and the rise of a data-driven economy have led to the creation of data co-ops, which provide individuals with new opportunities to own and control their personal data.

In this week’s newsletter we draw from a report published in January, How Can Data Cooperatives Help Build a Fair Data Economy?, by Project Liberty Institute and Decentralization Research Center.

Drawing on interviews with 16 key experts in data cooperatives, digital rights, data governance, and the digital economy, the report summarizes the current state of data co-ops and sets the agenda to examine the potential for cooperatives to help transform today’s digital economy.

// What is a data co-op?

One in eight people globally is a member of a co-op. That’s 12% of humanity. In total, three million co-ops employ nearly 10% of the global adult workforce, or 280 million people.

Co-ops have been around for hundreds of years. They originated in the 18th century. Today, major companies like REI, Land O’Lakes, Best Western, and even the AP (Associated Press) are all co-ops.

The International Cooperative Alliance defines a cooperative as “an autonomous association of persons united voluntarily to meet their common economic, social, and cultural needs and aspirations through a jointly owned and democratically controlled enterprise.”

Building upon this definition, Project Liberty Institute defines a data cooperative as “a form of cooperative organization based on the ownership and governance of data.”

Here is how it works:

1. Members of a cooperative consent to have a third party (the co-op) hold copies of their data.
2. The third-party entity is cooperatively governed by its members who participate in decision-making and oversight.
3. This entity can safeguard its members’ data or represent its members in negotiations over how their data is used and sold.

It’s a simple concept, but the implications are enormous—particularly when considering how data is owned and governed on the internet today.

Vast amounts of data are owned and controlled by a few large tech companies that practice “extractive, feudalistic business models.” The billions of users on platforms like Facebook or TikTok don’t own or control the content they produce, and the data generated from their online activity is often harnessed by profit-seeking, attention-grabbing algorithms to drive engagement. The result? An internet defined by poor data privacy, monopolistic business practices, and hyper-centralized control.

A data co-op upends this and returns control to users to manage their data: Members of a data co-op actively participate in democratic governance, voting on how their data is used, managed, and monetized.

Data co-ops differ from data trusts (a more top-down structure where trustees make decisions on behalf of people who contribute their data) and data commons (a structure where data is pooled and shared as a common resource but often lacking individual rights).

“Data co-ops give individuals a financial stake, distributing economic returns directly to members,” the report noted. “Unlike data trusts and data commons, which focus on protection or collective access, co-ops uniquely prioritize member ownership, autonomy, and shared prosperity.”

However, the best model for ensuring that people have voice, choice, and stake in their digital lives may lie at the crossroads of these models. Looking at these hybrid models is precisely what PLI and DRC will explore in the second phase of their collaboration.

// Examples of data co-ops

Mei Lin Fung, the Co-Founder of People-Centered Internet, believes that “Data co-ops are an idea whose time has come. Because we’re so aware now of the consequences of irresponsible data use.”

Here are five examples of data co-ops.

1. MiData is a health data cooperative that empowers individuals to securely store, manage, and control access to their personal health data.
2. Swash is a browser extension and digital wallet that allows its users to get paid for browsing the internet. Considered the largest data union in the world, it allows people to exercise their data rights and make money from the value of their data.
3. The Driver’s Seat Cooperative was a worker-owned ride-hailing platform aimed at distributed data governance and improved working conditions for gig-economy workers. However, the co-op model ended up not being financially sustainable, and it now exists as part of a research initiative at Princeton University.
4. Salus.coop is a co-op from the Catalonia region of Spain that pools members’ health data.

Sylvie Delacroix, the Inaugural Jeff Price Chair in Digital Law and Director of the Centre for Data Futures, believes that these early experiments in data co-ops will inform future models that could become more scalable.

“I think that in the future, we’re going to see a lot more experimentation with different models of data ownership and governance,” she said. “Data cooperatives are going to be one of the most promising models. But I think that we’re also going to see a lot of hybrid models, like data trusts and data commons. The key is going to be to find models that are both fair and sustainable.”

// Addressing the core challenges of data co-ops

The report highlighted insights from its 16 interviews on core challenges that data co-ops must address to be successful.

Together, these core challenges form an agenda for future research on designing and managing effective data co-ops. Here are four (but the report outlined several more):

1. Bridge the gap between theory and practice. The abundance of academic literature and conceptual frameworks surrounding data co-ops stands in stark contrast to the scarcity of successful operational models. A more pragmatic approach is needed that prioritizes building functional data cooperatives that deliver tangible benefits.
2. Interrogate the actual value of data. Many experts interviewed for the report challenged the idea that data holds intrinsic value. Its value is context-specific and depends on how it’s used. Finding these use cases is crucial for data co-ops to become financially sustainable.
3. Focus on aligning incentives. To ensure the success of data cooperatives, it’s essential to align incentives for both data contributors and data buyers. Beyond financial rewards, co-ops can offer members access to valuable insights derived from aggregated data, thereby enhancing their decision-making capabilities. Additionally, by pooling data, members can gain collective bargaining power, enabling more favorable negotiations with companies or institutions seeking to utilize their information. This collaborative approach not only fosters stronger community ties but also promotes the sharing of high-quality data, which in turn increases the cooperative’s overall value and revenue potential.
4. Establish better legal and regulatory frameworks. The lack of clear legal definitions and supportive policies creates challenges when setting up data co-ops. Better legal and regulatory frameworks at the local level will reduce the friction standing in the way of more experiments.

// The next step

On April 1st at the Decentralized Tech Summit at Georgetown University, Project Liberty Institute and Decentralization Research Center will convene a larger group of practitioners, technologists, and policymakers from across the cooperative, decentralized governance, and fair data realms to examine how cooperative business models might advance the goal of giving people a greater voice, choice, and stake in the digital economy. The result will be a roadmap for anyone looking to explore models of decentralized data agency.

Like many other Americans at the time, I spent the afternoon of the bicentennial — July 4, 1976 — at a cookout. In my case the cookout was in a park in Lisbon, Portugal, hosted by the American ambassador, who read to us a special message from Gerald Ford. I’ve always wondered how the embassy managed to find hot dogs — not exactly a Portuguese staple — for the occasion.

There were few Americans in Portugal at the time. Lisbon in 1976 was a sleepy backwater — not the tourist and mobile worker hotspot that it is today. And the U.S. deliberately kept a low profile. Portugal had overthrown its fascist dictator only two years earlier, and many people there were obsessed with the idea that Henry Kissinger, who had warned that Portugal might go Communist, would try to engineer a coup like the one that overthrew Chile’s Salvador Allende in 1973. There were graffiti on the walls saying “Morte ao CIA” (death to the CIA) although some of them added, in fresher paint, “e o KGB.”

So America tried to stay out of the limelight. In fact, there were so few official representatives of the U.S. government around that the cookout had to be filled out with lots of staffers from other Western embassies.

Did anyone else see the horrific display in the Oval Office last Friday as a ritual exercise in male domination? I don’t want to insult great apes, but I’ve seen similar performances at the zoo. Trump and Vance sought to humiliate Zelensky, treating him with the same disrespect they treat .. well, women.

Trump, Vance, and Musk inhabit what’s been termed the “manosphere” — a place where the main events are dominance and submission. The whole point is to humiliate weaker men — and to subjugate women.

Women — especially women of color — have distinguished themselves in standing up to Trump, maybe because they’re less intimidated by him than are many men, and because Trump has shown himself particularly fearful of strong women.