Courses

A first, serious encounter with how social knowledge is made: from a vague curiosity to a question that can be answered, and from raw numbers to a claim you could defend before a skeptic.

"Statistics is not calculation; it is argument under uncertainty. Every number in this course is treated as a claim that must survive objection."

The spine of the course is a single original research project each student carries from question to defense, not a series of prepared problem sets with known answers. Every technique is taught twice: once as a procedure, and once as a claim a skeptic could attack. The goal is not the correct output but the defensible conclusion.

• The logic of comparison: why a finding means nothing without the case it is being compared against.
• Sampling as a theory of the missing: every sample is an argument about who was left out.
• Simpson's paradox & the ecological fallacy: how the same data reverses its verdict depending on the group you look through.
• What a p-value is not: the most consequential misunderstanding in the social sciences.

The sociological imagination: learning to see private troubles as public issues, and to trace how society shapes the self we mistake for our own creation.

"The course has one demand: stop explaining the social by the individual. Every private trouble is followed back to a public structure."

Organised not as a march through topics but around a single, unsettling question: why do patterned outcomes persist across millions of "free" individual choices? Mills's sociological imagination runs through every week as the working tool, not a first-lecture slogan.

• Mills, the sociological imagination: the hinge between biography and history.
• The individual-versus-structure problem: the argument the whole discipline is built to win.
• Du Bois on the color line: sociology as the study of a divided society, from the beginning.
• The reproduction of institutions: how family, school, and work quietly hand outcomes down.

The architects of social thought: Marx, Durkheim, Weber, and the traditions they set in motion, read closely and put to work on the present.

"The classics are read as living instruments, not monuments; each theorist a different set of eyes on the same street."

Durkheim's Suicide is taught as a methods text, not merely a theory; evidence that the founders were empirical scientists, not armchair philosophers. Each theorist is then tested against a live contemporary case, so theory has to earn its keep.

• Marx: alienation, the commodity, and value as a social relation.
• Durkheim's Suicide: the most private act, explained by social facts.
• Weber: the problem of cause, and how ideas move history.
• The micro-macro problem: the fault line that still runs through the field.

The craft of empirical inquiry across the qualitative and quantitative traditions: designing studies that could, in principle, prove the researcher wrong.

"A study is only as good as the ways it could have failed. Design begins not with a hypothesis but with a search for disconfirmation."

Every design is stress-tested for its blind spots before a single datum is collected; students learn to name the study they didn't run and the voice it left out. Qualitative and quantitative are taught as answers to different questions, never as rival camps to pick sides in.

• Question-method fit: the choice that quietly decides everything downstream.
• Validity as the central virtue: measuring what you claim to measure.
• The ethics of the unheard: who gets studied, who gets to speak.
• What triangulation actually buys, and what it cannot.

Statistical reasoning built specifically for social data: its messiness, its categories, and the inferences it will and will not bear.

"Every technique is taught twice: once as a formula, once as an argument someone could dispute."

The course refuses the button-pushing model. For every test, students must state what would have to be true for the result to mislead: the assumption that, if it fails, quietly voids the whole conclusion. The normal curve is treated as an assumption to be earned, not a gift to be assumed.

• Measurement as theory: every variable encodes a claim about the concept.
• The sampling distribution: the quiet engine that makes inference possible at all.
• Regression as controlled comparison: "holding constant" as an argument, not a command.
• Simpson's paradox: the reversal that punishes anyone who skips the structure.

A first course in statistical thinking: less about formulas than about what it means to reason honestly from data.

"The goal is not to compute the answer but to know when the answer is lying to you."

Built around reading real published claims and asking a single question: could this be an artifact? Statistical literacy is framed as a civic defense against being misled, useful to a voter and a juror as much as to a researcher.

• Describe before you test: most errors are made before any test is run.
• Probability and coincidence: why rare things are certain to happen to someone.
• Why samples deceive: the difference between a number and the truth it stands for.
• Correlation, cause, and the third variable: the oldest trap, still catching people.

How societies name, produce, and respond to their problems, from poverty and inequality to addiction and crime, and why the very definition of a problem is a social act.

"A social problem is not a fact of the world but a claim about it. The first question is always: who named this a problem, and why now?"

Problems are studied as contests over definition, not natural disasters; a condition becomes a "problem" only when someone with standing says so. Each problem is paired with the policy that failed to solve it and the evidence that was on hand and ignored.

• The social construction of problems: why the same condition is invisible in one era and urgent in the next.
• Poverty as a structure, not a trait: the shift from blaming the poor to explaining poverty.
• The war on drugs: a case study in policy that manufactures the problem it fights.

The structured inequality of class, status, and power: how advantage is produced, transmitted across generations, and made to seem deserved.

"Inequality's deepest trick is to make itself look like merit. This course takes the trick apart."

Built around the argument at the heart of the field, the Davis-Moore debate: is inequality a functional necessity, or a story the advantaged tell to justify their position? Students interrogate the birth-lottery model directly, seeing how much of an outcome is fixed before a person acts.

• Marx versus Weber on class: ownership against life-chances, the two founding maps of inequality.
• The Davis-Moore thesis and its critics: the debate over whether inequality is necessary at all.
• Bourdieu and reproduction: how advantage disguises itself as taste, talent, and merit.
• The birth lottery: how much of a life is decided by coordinates, before choice begins.

The social construction of race and ethnicity and its hard material consequences, from prejudice and discrimination to the architecture of institutional inequality.

"Race is a social invention with entirely real effects. The course holds both truths at once, without flinching from either."

The course distinguishes relentlessly between individual prejudice and institutional structure, and uses the ecological fallacy to show precisely why group statistics are so easily, and so consequentially, misread in this domain. Du Bois's color line is the organising frame, not a footnote.

• Du Bois and double consciousness: the founding text of the sociology of race.
• Construction with consequence: how something "invented" still shapes wealth, health, and life expectancy.
• Institutional versus individual: why ending prejudice would not end inequality.
• The ecological fallacy in racial data: the statistical trap that fuels the worst misreadings.

Substance use as a social phenomenon rather than a private failing: shaped by culture, distributed by inequality, and governed by policy that is anything but neutral.

"Which drugs are crimes and which are medicine is a decision societies make, not a fact chemistry hands them."

Use is studied as a mirror of inequality and power: why the same behaviour is treated as a disease in one neighbourhood and a felony in another. The war on drugs runs through the course as a sustained case study in how policy can manufacture, and racialise, the very problem it claims to fight.

• The social versus medical model: is addiction a moral failure, a disease, or a social position?
• Set, setting, and distribution: why the same substance means different things in different lives.
• The racialised history of drug law: how the same molecule carried very different sentences.
• Harm reduction versus prohibition: the policy argument that decides who lives.