Who Gets What and Why

Bueno de Mesquita and Smith’s The Dictator’s Handbook was one of the inspirations for this series of posts. Their model of how people get and hold power isn’t as cynical as it first appears, and it helped me make sense of some of the company politics I’ve endured (and been part of) over the years. Reading outward from that lucky find led to the post below.

We’re All Family Here

In November 2022, after laying off about a third of its original workforce, Elon Musk sent an email to the remaining Twitter employees asking them to click a button to confirm that they were committed to working “hardcore” for the company’s next phase. Those who did not click by the deadline would be treated as having resigned. A few months earlier, Twitter’s former leadership had described it as a family.

The family metaphor is endemic to tech. Amazon has “Day 1 culture”, while Google offered free meals, nap pods, and climbing walls, and expected employees to treat the campus as home. The metaphor does real work: it extracts commitment, discourages outside offers, and makes employees (particularly younger ones) feel that the relationship is something other than a transaction. What it does not do is change what the relationship actually is.

Families (at least, those outside organized crime) do not terminate members for underperformance. They do not eliminate positions when margins tighten, or ask you to sign a noncompete agreement before letting you in. In most of the United States, and in varying degrees elsewhere, employment is at-will: either party can end it, at any time, for any reason not specifically prohibited by law. This means that the “family” exists at the employer’s pleasure.

The political scientist Harold Lasswell defined politics in 1936 as the study of “who gets what, when, how.” His definition contains no implication that the getting is fair, no assumption that what gets distributed is material, and no requirement that the process be democratic. It is simply a description of how groups make binding decisions about the allocation of things people want.

Politics is what happens when a group of people who do not fully agree on goals or values nonetheless need to act together. The alternative to politics is not harmony—it is coercion. Isaiah Berlin argued that this disagreement is not a temporary condition awaiting the right institutional fix [Berlin1991]. The goods people pursue—liberty and equality, security and freedom, efficiency and fairness—are genuinely plural and irreconcilable: you cannot maximize all of them simultaneously, and no rearrangement will make the conflict disappear. Liberal democracy is not a system for finding the right answer. It is a system for managing the permanent tension between right answers that contradict each other. A group that appears to have no politics is usually one in which someone has already won so decisively that further fighting seems pointless.

Both definitions apply to workplaces. An organization contains people who disagree about what matters, what to build, who to hire, where to cut, and who should lead. Those disagreements do not disappear because the employee handbook calls everyone a family. They get resolved through decisions that favor some people’s views and interests over others. That process is workplace politics.

Bueno de Mesquita and Smith developed a framework called selectorate theory to explain why leaders behave the way they do [BuenodeMesquita2011]. The core observation is simple: leaders of countries, companies, and volunteer organizations need enough support to stay in power. They get that support by distributing benefits to a minimum necessary winning coalition.

The winning coalition is not the whole organization: it is the subset of people whose support the leader actually requires. In an autocracy, this might be the military brass, a security service, and a handful of oligarchs. In a publicly traded company, it is the board, major institutional shareholders, and a small number of indispensable senior executives. Everyone else—the people who are told they are family, and that the company’s success is their success—is interchangeable. They are what the theory calls the selectorate: large enough to give the winning coalition options if any member defects, but not powerful enough to claim a significant share of private benefits.

This is why perks, mission language, and family rhetoric are so common in organizations that also behave ruthlessly when conditions change. The perks are cheap ways to signal belonging to people who are not actually in the winning coalition. The rhetoric costs nothing but extracts real commitment. When the company faces a genuine crisis, the winning coalition keeps their jobs. The family discovers it was not, in fact, the family.

This is where a common misreading needs correction. The people who use family rhetoric are not, for the most part, cynical manipulators who despise their employees. Nor are they altruists who genuinely believe the metaphor and are simply wrong about how the world works. Most are somewhere in between: people who have genuine beliefs about what the organization should do, who also benefit when those beliefs prevail.

Jeffrey Pfeffer, in decades of research on organizations, found that political skills like the ability to build coalitions, read organizational dynamics, and time moves correctly are stronger predictors of career advancement than technical competence [Pfeffer1992]. The engineer who wants to rewrite the legacy codebase genuinely believes it needs rewriting, and also gets promoted if the project goes ahead under her leadership. The VP who champions a reorganization genuinely thinks it will improve outcomes, and also ends up at the top of the new structure.

Interests and beliefs are not opposites. People pursue what they think is right, and what they think is right is shaped by their position in the organization. A sales leader who believes the product team should prioritize enterprise features is not lying. She is telling the truth as experienced from where she sits. She also reaps the benefits if her plan is adopted.

The family metaphor is not unique to American tech companies. Japan’s postwar lifetime employment system produced what selectorate theory would describe as a very large nominal selectorate of permanent employees with a winning coalition drawn from senior management and major shareholders. When the asset bubble collapsed in 1990 and corporations needed to cut costs, the permanent employment guarantee at the heart of the “family” bargain was broken through expansion of temporary and contract employment that covered the same work under worse conditions. The family language remained; the security it implied did not.

The phrase “we don’t do politics here” appears regularly in tech companies. It usually means one of two things. The first is a genuine belief that technical decisions should be made on technical merit, that interpersonal dynamics should not determine outcomes, and that coalition-building is a form of corruption. This belief is reasonable, but almost entirely wrong about how decisions actually get made.

The second meaning is that when the people in the winning coalition say “we don’t do politics here”, what they usually mean is that they have already gotten what they want from the current structure, so there is no need for them to engage in visible political activity. People who are well-served by existing arrangements can afford to describe those arrangements as natural and political contestation as illegitimate.

Understanding that your workplace is a political environment is not the same as deciding to become a political operator. It does not require manipulation or coalition-building for its own sake. What it does require is honesty about what is actually happening when decisions get made. Someone who believes their technical approach is correct and advocates for it strongly, who seeks allies among colleagues with aligned interests, and who times their proposal for when decision-makers are receptive is not doing something shameful. They are participating in the ordinary process by which organizations make decisions in the absence of shared goals. The person who refuses to do any of this and then wonders why their ideas never get adopted is not taking the moral high road. They are making a practical error while feeling virtuous about it.

Your organization is political. The question is not whether to participate in its politics. The question is whether to participate consciously and honestly or not [Crick2000,Runciman2014].

The Hidden Ledger

The political decisions that shape organizations do not operate in a vacuum. They interact with social categories that were themselves created through prior political decisions— categories that shape who finds it easy to enter a winning coalition and who remains part of the interchangeable selectorate.

In 1950, South Africa’s apartheid government created the Race Classification Board to assign legal racial categories to people whose status was ambiguous. The examiners used what they called the pencil test: if a pencil inserted into someone’s hair stayed in place without falling, the person might be classified as “Coloured” rather than “White.” They listened to accents, examined fingernails for pigmentation, and interviewed neighbors. Families were split: siblings were classified into different categories because they had inherited different combinations of features, giving them different legal rights and permitted occupations, and requiring them to live in different neighborhoods.

The pencil test is an extreme example of something that operates wherever racial classification exists: a social and political determination dressed as a natural fact. Race is not a biological category. This is not a political opinion—it is the settled position of geneticists, who have found more variation within conventionally defined racial groups than between them. Race has been defined and redefined by specific people for specific political reasons.

The US Census Bureau’s changing list of racial categories is a useful illustration. In 1930, Mexicans were for the first time classified as a separate racial category rather than white. A decade later they were reclassified as white again following diplomatic pressure from the Mexican government. The category “Hispanic” does not appear in census data before 1970; it was created by the Nixon administration to aggregate Spanish-speaking populations for federal programs.

The sociologists Michael Omi and Howard Winant called this process racial formation. Irish immigrants in the 1840s appeared in popular cartoons as racially distinct from Anglo-Saxons, while Italian immigrants in the early twentieth century were subject to legal discrimination partly justified on racial grounds. Each of these groups eventually became “white” through political processes that included them while excluding Black Americans [Oluo2018,Omi2015].

Understanding how racial categories are built, and by whom, is necessary for understanding how algorithmic systems operate in societies organized around race and caste. A system cannot be race-neutral or caste-neutral if it is trained on data generated by institutions that were not. A hiring model trained on historical promotion decisions learns to prefer candidates who resemble the people who were previously promoted, in organizations that excluded people by race and class. A recidivism prediction tool trained on arrest data learns patterns from policing decisions that were themselves racially disparate [Kendi2016,Wilkerson2020].

Algorithmic hiring systems, insurance scoring models, and predictive policing tools share two structural features that determine their impact: they collect data without meaningful consent, and the subjects cannot see or challenge the decisions made about them. Credit bureaus are the most mature example of this model, and the clearest preview of where the others are heading.

The three major credit bureaus collect financial data about hundreds of millions of people without their active participation or consent. They do not collect data from the people whose files they maintain. They collect it from creditors like banks, credit card issuers, and debt collectors, who report account status and payment history. The person whose data is being collected is not notified when a new entry appears in their file, has no opportunity to contest it before it is recorded, and may not know it exists until they apply for credit and are denied. The bureau’s relationship is with the furnisher and the purchaser of the data, not with the subject.

Credit data determines whether people can rent housing or get a job. The companies profit whether the data they hold is accurate or not. A person whose file contains an error bears the full cost of that error while the bureau bears none. In the US, the Fair Credit Reporting Act gives consumers some rights to dispute errors, but the dispute process is designed and operated by the bureaus themselves, and has repeatedly been found to be inadequate.

Accuracy and fairness are not the same thing, and the credit bureau model conflates them. A credit score can be perfectly accurate as a summary of past borrowing behavior and still encode the effects of decades of discriminatory lending. Neighborhoods that were redlined in the twentieth century still show lower average credit scores today: not because their residents are less creditworthy, but because they were systematically excluded from the wealth-building mechanisms that credit history reflects. A score that accurately summarizes a history of exclusion still perpetuates exclusion.

In the 2017 Equifax breach, the personal financial information of approximately 147 million people was exposed, including Social Security numbers, birth dates, and home addresses. Equifax’s response was to offer credit monitoring services—sold by Equifax. The settlement reached in 2019 provided most affected consumers with a few dollars apiece, after the claims fund was overwhelmed by the number of applicants. No one at Equifax faced criminal charges.

The parallel to large technology platforms is not a stretch. Google, Meta, and others collect data about billions of people without meaningful consent and sell access to that data to advertisers, whose relationship with the platform is the commercially important one. There is no effective dispute process, and when these systems produce discriminatory outcomes, the platform does not bear a cost proportional to the harm. The credit bureau model took decades to produce Equifax. The tech industry produced the same structure at global scale in about fifteen years, and called it connecting the world [Chouldechova2017,Oneil2016,Pasquale2015].

Why Don’t You Just…

In 2013, the United Kingdom launched Universal Credit, a welfare reform ostensibly intended to simplify the benefits system by merging six separate payments into one. The new system was designed to be applied for online, but many claimants had no reliable internet access. Those who did often lacked fixed addresses, which the system required before it would register them. Without registration they couldn’t receive payments; without payments they couldn’t maintain an address, and without an address they couldn’t register.

Government officials and advice workers, when presented with this loop, would sometimes suggest that claimants “just go to the library” to use a computer. They did not know—or had not thought through the fact—that some libraries require a membership card to use their computers, that membership cards require proof of address, and that the Universal Credit application times out and loses your work if you do not complete it in a single session. The word “just” was doing an enormous amount of lifting.

“Just” does that in a lot of conversations. When someone with relative power is told about a problem they have not personally faced, a common response is to suggest an individual solution: “Why don’t you just move to a better neighborhood, just report the harassment to HR, just open a bank account, just apply for a scholarship.” The suggestion is not usually made in bad faith. It is made because the person offering it has, at some point in their life, moved, or reported, or opened, or applied, and found the process manageable. What they cannot see is what made it manageable for them and what makes it unmanageable for someone else.

Peggy McIntosh described this as an invisible knapsack: a set of advantages so routine to those who carry them that they are not experienced as advantages at all [McIntosh1989]. You do not notice that your accent marks you as non-threatening, that your name gets you callbacks, that your neighborhood has a library, or that the official you need to speak to treats you as a legitimate claimant rather than a probable fraud. The person offering the “just” solution is usually describing what they would do, which is not the same thing as what the other person can do.

The most obvious thing “just” conceals is cascading prerequisites. Many systems assume that the person using them already has a set of prior resources in place. The Universal Credit example is one illustration: online-only access built on a cascade of prior requirements, each of which depends on the one before it.

A second thing “just” hides is the cost of the transaction. Taking a day off work to stand in line costs money that people without savings cannot spare. Challenging a decision by a government agency or a platform company requires knowing how to challenge it, having the literacy and the time to fill in forms, and being willing to risk the relationship with the institution you depend on. The last point matters more than it might seem: if the institution denying you a benefit is the same institution you are hoping will pay your rent next month, asserting your rights has a price.

A third thing the word hides is cognitive load. Sendhil Mullainathan and Eldar Shafir spent years studying what poverty does to decision-making, and their conclusion was not what most people expect [Mullainathan2013]. Poverty makes people worse at decisions in the same way that keeping someone awake for twenty-four hours makes them worse at decisions: it depletes a finite resource. Managing an unpredictable income, keeping track of which bills are overdue, or calculating whether buying the cheaper item in bulk saves more than it costs to store consumes cognitive bandwidth that is then not available for navigating bureaucratic systems. The person telling someone to “just” do something is typically not paying this tax.

The pattern is particularly vicious on tech platforms. Companies routinely advise users to “just report” harassment, “just use a VPN” to avoid surveillance, or “just switch platforms” when a service degrades. Each suggestion assumes that the user has time, technical literacy, and social capital that many do not have, and none of them fix the underlying system. They transfer the cost of a structural failure onto the person least able to bear it [Eubanks2018].

Who Gets to Decide

In August 2016, the European Commission ordered Apple to repay thirteen billion euros in back taxes to Ireland. The commission had investigated Apple’s tax arrangements in Ireland and concluded that they amounted to illegal state aid: Ireland had given Apple a selective advantage unavailable to other companies, allowing the company to pay an effective tax rate of 0.005% on European profits of sixteen billion euros in 2014.

The Irish government was ordered to collect the money, and promptly announced it would appeal the ruling. Ireland did not want the thirteen billion euros; its government argued in court, alongside Apple, that the commission had made an error. This only baffled the cynical: Ireland’s unusually favorable tax treatment of multinationals was a deliberate policy to attract foreign companies.

The mechanism Apple used was a variant of a structure known as the Double Irish, which Irish tax law had made available through a combination of specific provisions and deliberate regulatory tolerance. Ireland taxes companies that are managed and controlled from Ireland. The United States taxes companies incorporated in the United States. Apple’s Irish subsidiaries were incorporated in Ireland but had their management and control located outside Ireland, so Ireland did not tax them. They were also not incorporated in the United States, so the US did not tax them either. At its peak, this arrangement sheltered tens of billions of dollars annually.

The intellectual property component made the structure self-sustaining. Apple’s valuable patents were licensed from a subsidiary in a low-tax jurisdiction. European sales flowed through Apple Sales International, which paid royalties back to the IP-holding entity. The royalties reduced taxable profit in the high-tax jurisdictions where the sales occurred. Transfer pricing (the setting of prices for transactions between subsidiaries of the same company) is supposed to follow the arm’s length principle: the price should be what unrelated parties would charge each other. In practice, there is no market price for a license to Apple’s entire product ecosystem, so whatever number Apple’s accountants put in the contract became the price. Tax authorities in each country then had to prove the price was wrong, which requires the kind of information that companies are not generally eager to provide.

Apple was not alone, and Ireland was not the only country involved. The Dutch Sandwich added a Netherlands entity to the structure, exploiting a Dutch tax provision that exempted certain royalty payments from withholding tax. Royalties would flow from Ireland to the Netherlands, then onward to the zero-tax jurisdiction, each step reducing the amount captured by any jurisdiction that might want to tax it. Luxembourg served a similar function for Amazon; by putting its European headquarters there, the company could book sales across the continent while keeping profits in a jurisdiction that had negotiated unusually favorable rulings with dozens of major multinationals. Google’s arrangement was so elaborate to have its own nickname: the Double Irish with a Dutch Sandwich [Shaxson2011].

The OECD’s BEPS project, launched in 2013, produced a fifteen-point action plan to close these loopholes. Countries that adopted its recommendations were supposed to require substance in the jurisdictions where companies claimed tax residence, limit the deductibility of interest payments used to shift profits, and require country-by-country reporting to make the overall structure visible. Ireland amended its tax law in 2015 to prevent new companies from using the Double Irish structure, but gave companies already using it a five-year phase-out period.

The 2021 agreement among 136 countries on a global minimum corporate tax rate of 15%, negotiated under OECD auspices, went further than any previous multilateral effort. It established the principle that no matter where a multinational’s profits were booked, at least 15% would be paid somewhere. The agreement was called historic, which was accurate, and transformative, which was not, since implementation depended on each country passing domestic legislation.

Gabriel Zucman’s estimates suggest that roughly 40% of multinational profits are shifted to tax havens annually, costing governments approximately $200 billion per year in corporate tax revenue. This is money that does not fund schools, infrastructure, or healthcare in the countries where the economic activity actually occurred. The companies that benefit from this system defend it as legal, which it is. They also describe it as responsible tax planning, which is a creative use of the word responsible [Zucman2015,Schneier2023].

The money that does not reach public treasuries does not simply disappear. Some of it returns to public life through a different channel, one controlled by the same people who structured the avoidance. In June 2010, Bill Gates and Warren Buffett announced the Giving Pledge: a commitment by the world’s wealthiest people to give away the majority of their fortunes. By 2023, more than 230 billionaires from thirty countries had signed, representing combined pledges of over a trillion dollars. The press coverage was broadly admiring, and mostly did not ask who would decide where the money went.

The combination of great private wealth and public purpose is not new. Andrew Carnegie, who accumulated his fortune partly by suppressing wages and, in 1892, hiring Pinkerton detectives to break a strike at his Homestead plant that left ten workers dead, spent his final decades funding libraries, universities, and concert halls. Cities that received Carnegie libraries did so on his terms: local governments had to provide the land and commit to maintaining the buildings in perpetuity. The offer was generous; it also bypassed democratic mechanisms.

The more consequential precedent was the Flexner Report of 1910, commissioned by the Carnegie Foundation for the Advancement of Teaching. It recommended consolidating medical education around elite university-based institutions and closing the smaller proprietary schools it judged substandard. These changes raised training standards. They also closed most of the schools that had trained Black physicians or admitted women in significant numbers. Private money had shaped outcomes that no democratic process had approved [Reich2018].

Today’s private foundations differ from Carnegie’s personal giving in one critical respect: the American tax code. Since the Revenue Act of 1917, charitable contributions have been deductible from taxable income. When a billionaire transfers appreciated assets into a private foundation, they avoid capital gains taxes on those assets and receive an income tax deduction immediately. The assets remain under the effective control of the foundation’s board, which in practice consists of the donor and their chosen representatives. Private foundations are required to distribute at least five percent of assets annually, but the other ninety-five percent continues to grow tax-free under the donor’s direction. What looks like giving money away is, legally and financially, converting taxable personal wealth into a permanently controlled institutional endowment while capturing the tax benefit upfront. Donor-advised funds extend this further: the donor takes an immediate deduction but retains the ability to direct distributions to any eligible recipient for decades. In 2022, donor-advised funds held over $230 billion in assets.

In the 2000s, the Gates Foundation, working alongside the Walton Family Foundation and the Eli and Edythe Broad Foundation, channeled hundreds of millions of dollars into reshaping American K-12 education. Their preferred agenda included charter schools, standardized testing, merit pay for teachers, and the Common Core State Standards. For a period, these became the dominant policy agenda of American school reform. The decision-makers at these foundations were not elected and could not be removed by the parents, students, or teachers whose schools were being reorganized. In 2017, Gates Foundation CEO Sue Desmond-Hellmann published an open letter acknowledging that the foundation’s strategy had not produced the results it intended. She described it as a learning experience. Most of the teachers whose work and lives had been thrown into turmoil used stronger language.

This kind of philanthrocapitalism extends beyond education. For many years the Gates Foundation was the second-largest funder of the World Health Organization, behind only the United States government. During the COVID-19 pandemic, this made it an influential voice in debates about vaccine distribution, intellectual property waivers for low-income countries, and global health system priorities. The fact that this influence was exercised with what donors believe are good intentions does not change the fact that they lack the democratic legitimacy of public institutions. Who gets what, and why, is not only a question about the distribution of economic resources. It is also a question about who is allowed to shape the rules of that distribution [Giridharadas2018].