Week 15 — Lecture Outline · Political Economy & Global Issues

Introduction to Political Science · POLS 1 Fall 2026 · Prof. Halloran Fictional sample

Course: Introduction to Political Science (POLS 1) · Silver Oak University (fictional sample) · Prof. Halloran
Objectives covered: Objective 8 — explain the major theories of international relations and the basics of the international system, international organizations and law, and global political economy, presenting competing theories and contested global questions evenhandedly.
SLOs touched: A (source and evaluate political texts and data) · B (build an evidence-based political argument)
Meeting pattern: 2 sessions × 75 min = 150 min. Segment minutes below total ~150; scale to your own pattern.

Week at a Glance


The week's big question	"When politics and markets meet on a global scale — trade, poverty, climate, migration — what does the evidence actually show, and where does the debate turn from facts to values?"
By the end of the week, students can…	(1) place a real economy on the states-markets spectrum using varieties-of-capitalism terms, without ranking systems; (2) distinguish comparative advantage (descriptive) from trade policy (normative) and state trade's documented aggregate gains and distributional costs; (3) state the climate collective-action problem and its empirical basics plainly, and present climate policy responses evenhandedly; (4) read a real global-poverty chart (Our World in Data) for what population/period/line it covers and what it does and does not show.
Key vocabulary	political economy, mixed economy, varieties of capitalism (liberal market economy / coordinated market economy), comparative advantage, trade policy, globalization, absolute vs. relative poverty, between-country vs. within-country inequality, collective-action problem, the international poverty line, migration (documented patterns vs. policy)
Materials	slides (Deck 15), the week's readings + the linked Our World in Data page, one approved chatbot (Gemini / Claude / ChatGPT) for the AI-critique moment and the tutorial
Timing note	8 segments, ~150 min total. Session 1 = Segments 1–4 (~75). Session 2 = Segments 5–8 (~75).

Segment 1 — Hook & the Promise (8 min) · Session 1 opens

Hook. Put one number on a slide, with no context: "10%." Ask: "Ten percent of what? Guess before I tell you." Take a few guesses, then reveal: as of 2025, roughly one in ten people on Earth lives on less than $3 a day — the World Bank's current International Poverty Line, the threshold the United Nations uses to track extreme poverty (verified live at ourworldindata.org/poverty, 2026-07-02). Let that sit for a second, then flip it: in 1820, the figure was closer to eight in ten (Moatsos 2021 historical reconstruction, cited at ourworldindata.org/extreme-poverty-in-brief). "That decline — from roughly 80% to roughly 10% — is one of the best-documented facts in economic history. This week we ask two political-science questions about it: what does that number actually mean, and what does it NOT tell us?"

The promise (write it on the board): "By Friday you'll know where a real economy sits on the states-markets spectrum, why 'countries gain from trade' and 'we should cut this tariff' are two completely different kinds of claim, what the climate collective-action problem is, and how to read a real chart on global poverty without being fooled by it — or by an AI that garbles it."

Why it matters line (memory hook): "Politics decides who bears the cost and who gets the benefit — nowhere more than in the global economy."

Segment 2 — States and Markets: The Spectrum of Real Mixed Economies (20 min)

Plain language first. No real economy is "pure capitalism" or "pure socialism." Every economy on Earth mixes markets (private exchange, prices, competition) and states (taxation, regulation, public provision, redistribution) — the interesting political-science question is how much of each, and how they're organized, not which pole a country sits at.

Varieties of capitalism (name factually, neutrally — this is comparative political economy's standard typology, associated with Peter Hall and David Soskice's influential 2001 framework):
- Liberal market economies (LMEs) — coordination happens mainly through competitive markets and prices; relatively flexible labor markets, shareholder-oriented firms, less centralized wage bargaining. Commonly cited examples: the United States, the United Kingdom, Canada.
- Coordinated market economies (CMEs) — coordination happens more through non-market institutions: employer associations, unions, and long-term relationships between firms, banks, and workers; more centralized wage bargaining, stronger vocational training systems. Commonly cited examples: Germany, Japan, the Nordic countries (which also add extensive welfare states).
- The clarification students always need: LME vs. CME is a description of how coordination happens, not a ranking of outcomes. Both are real, functioning, wealthy-country models; each has documented trade-offs (LMEs: often faster job creation and reallocation, more income volatility; CMEs: often stronger vocational training and job security, sometimes slower adjustment to shocks). Political scientists describe institutional design; whether a given trade-off is worth it is a normative judgment.

The bigger point: "socialism vs. capitalism" as a binary is mostly a rhetorical frame, not an accurate map of any real economy (Week 3's ideology-neutrality lesson returns here). What varies across real mixed economies is the mix and its institutional form — how much is provided publicly (health care, pensions, education), how markets are regulated, and how coordination happens. This is genuinely comparative political economy — the bridge between Weeks 13's comparative method and this week's global lens.

Segment 3 — Comparative Advantage (Descriptive) vs. Trade Policy (Normative) (22 min)

Set it up: "Here's this week's sharpest empirical/normative test — because the two get blurred constantly, in the news and by chatbots."

Comparative advantage — stated as the descriptive economic concept it is: the classical insight (associated with David Ricardo, 1817) that countries (or people) tend to gain from specializing in producing what they can produce at a relatively lower opportunity cost, and trading for the rest — even if one country is better at producing everything in absolute terms. This is a positive/descriptive claim: a logical and empirical proposition about how specialization and exchange can raise total output, testable in the same way any economic model's predictions are testable. Political scientists don't referee whether the underlying economic logic is sound (that's economics' job) — but they DO study who wins, who loses, and how governments respond, which is squarely political.

The documented empirical picture on trade (state plainly, not both-sided): international trade is associated with aggregate gains — lower consumer prices, wider variety, productivity gains from specialization — AND with documented distributional costs: specific industries, regions, and workers can be genuinely harmed when import competition displaces them, sometimes for extended periods (a well-studied finding in trade economics, e.g., research on regional manufacturing-employment effects following import competition). Both of these are empirical findings, not competing opinions — the aggregate-gain finding and the concentrated-cost finding coexist in the same body of research.

Trade POLICY is where it turns normative — present evenhandedly:
- Proponents of freer trade argue the aggregate gains are large and widely shared over time through lower prices and growth, protectionism tends to raise costs for consumers and downstream industries, and the right response to dislocation is domestic policy (retraining, adjustment assistance) rather than blocking trade itself.
- Critics/proponents of trade restrictions or managed trade argue that concentrated, geographically clustered losses are real, slow to heal, and politically and socially costly even if aggregate gains are positive; that adjustment assistance has often been underfunded or slow in practice; and that strategic industries or national-security-relevant production may justify deliberate protection regardless of the efficiency case.
- Both positions accept the same descriptive economics; they weigh the same documented gains and costs differently, and add different priorities (aggregate efficiency vs. concentrated harm; consumer welfare vs. worker/community stability; economic efficiency vs. strategic autonomy). Neither side denies the other's facts — they weigh them differently. That is precisely the empirical/normative distinction from Week 1, back at full strength.

Segment 4 — Misconceptions + Quick Interaction (25 min) · Session 1 closes (~75)

Name the misconceptions out loud, then cure each:

❌ "A country is either capitalist or socialist."
✅ Cure: every real economy mixes markets and states; the honest comparative question is the mix's size and institutional form (LME vs. CME), not a binary label.
❌ "If trade has losers, comparative advantage must be wrong."
✅ Cure: comparative advantage describes aggregate gains from specialization; it has never claimed everyone gains automatically — the distributional-cost finding is a separate, equally real empirical result, not a refutation.
❌ "Poverty and inequality are the same thing."
✅ Cure: poverty is about people falling below some absolute or relative threshold of resources; inequality is about the spread of the whole distribution. A country can cut poverty while inequality rises, or vice versa — they're different measurements answering different questions (this week's workshop tracks poverty; W12's polling data touched opinion, not inequality — don't conflate the pockets).
❌ "Climate change being a scientific finding means the POLICY response is also settled science."
✅ Cure: the physical basics (rising greenhouse-gas concentrations, their warming effect) are an empirical, scientifically documented finding, stated plainly per the scientific record. What to do about it — carbon taxes vs. cap-and-trade vs. regulation vs. subsidies vs. adaptation vs. some mix, and how fast, and who pays — is a normative and political question with real, defensible disagreement. Conflating the two is exactly the is/ought smuggling error from Week 1.

Interaction — Descriptive or Normative? (rapid-fire, ~10 min):
Put claims on a slide; students call descriptive (is) or normative (ought), solo (15 sec), compare with a neighbor, then vote: "Rising greenhouse-gas concentrations trap additional heat in the atmosphere" (E — the physical basics) · "Wealthy nations should bear a larger share of the cost of cutting emissions" (N) · "Countries that lowered trade barriers in the postwar era generally saw growth in trade volume" (E — comparative, testable) · "Free trade agreements are good for workers" (N — contested, and too broad to test as stated) · "Extreme poverty, measured at the World Bank's international line, has declined since 1990" (E — this week's dataset) · "Rich countries have a moral duty to admit more migrants" (N) · "Migration flows respond to wage differences and labor demand between origin and destination countries" (E — a documented, testable pattern). Land the week's central move again: the same global topic generates both kinds of claims — never let a speaker smuggle an ought inside an is.

Segment 5 — A Worked "Think-Like-a-Political-Scientist" Moment: Reading the OWID Poverty Chart (24 min) · Session 2 opens

Hook back in: "Last session: the concepts. Today: the toolkit — on a real, current global dataset you'll analyze yourself in this week's workshop."

The dataset: Our World in Data, "Poverty" (ourworldindata.org/poverty; chart data collated from the World Bank's Poverty and Inequality Platform), which tracks the share of the world's population living below several poverty lines over time. Verified live 2026-07-02.

Walk the read-the-data scaffold out loud (this is the workshop's method, modeled):
- What is measured? The share of the world's population whose income or consumption falls below a stated poverty line, expressed in international dollars (a purchasing-power-adjusted unit — one international-$ buys what one US-$ buys in the United States, so poverty lines are genuinely comparable across countries).
- Which line, and what does it mean right now? As of June 2025, the World Bank's International Poverty Line is $3.00 per day (2021 international-$), used by the U.N. to track extreme poverty worldwide. This is a recent change — the line was $2.15/day (2017 int-$) before that, and $1.90/day (2011 int-$) before that. (Flag for students: an AI trained on older material, or a slightly out-of-date article, may still say "$2.15" or "$1.90" — you must check the CURRENT figure at the source, dated.)
- Over what population and period? The whole world's population, from 1990 to the present for the current-line series (World Bank PIP data), and further back — to 1820 — for a separate long-run historical reconstruction (economic historian Michail Moatsos, 2021, using a "cost of basic needs" method and an older $1.90-equivalent line, published via the OECD).
- What does it show? Two real, dated, documented figures (verified live at ourworldindata.org/poverty and ourworldindata.org/extreme-poverty-in-brief, 2026-07-02): (1) at the modern World Bank $3/day line, the global extreme-poverty rate fell from about 44% in 1990 to about 10% in 2025; (2) over the long historical run, Moatsos's reconstruction puts the rate at roughly 79% in 1820, falling to roughly 9% by 2018. Both series, independently constructed with different methods and lines, point the same direction: a large, real, long-run decline.
- What does it NOT show? That the decline is inevitable (it required sustained economic growth that some of the world's poorest economies have not achieved, and the rate rose during the COVID-19 pandemic before resuming its decline); that $3/day represents an acceptable standard of living (at higher poverty lines the world looks far poorer — the same source reports 24% below $5/day, 52% below $10/day, 81% below $30/day, current figures); or a verdict on why the decline happened for some regions and not others (that's a genuinely contested explanatory question — Week 13's modernization/institutions/culture debate, revisited). Correlation vs. causation: the chart shows a trend over time, not a controlled experiment — attributing the decline to any single policy (e.g., "trade" alone, or "aid" alone) requires further argument the chart alone doesn't supply.

Land the key idea: a political scientist doesn't read a chart's headline and stop — she asks what exactly is measured, over what population and period, what line was used and whether it changed, and what the trend does and does not prove. The chart is real and the decline is real; what to conclude about policy from it is a separate, normative step.

Segment 6 — Global Challenges, Stated Plainly and Argued Evenhandedly (18 min)

Inequality — between vs. within countries (a distinction political economy needs precisely):
- Between-country inequality — the gap in average incomes across countries (e.g., a high-income country's average vs. a low-income country's average). Global economic growth, concentrated especially in Asia over the past several decades, has been associated with a narrowing of between-country inequality on many standard measures — a documented, if contested-in-detail, empirical finding.
- Within-country inequality — the spread of incomes inside a single country. This has risen in many (not all) countries in recent decades on standard measures, a separate and also well-documented empirical pattern.
- The clarification students always need: "global inequality is rising" and "global inequality is falling" can BOTH be defensible depending on which of these two components — or which combined global measure — is being discussed. Precision about which inequality avoids a classic confusion.

Climate change as a collective-action problem — state the empirical basics plainly, per the scientific record: rising atmospheric concentrations of greenhouse gases (CO₂ and others) trap additional heat, and the global scientific assessment process (national academies of science worldwide, the IPCC's assessment reports) documents that human activity is the dominant driver of warming observed since the mid-20th century. This is a collective-action problem in the classic political-science sense: the atmosphere is a shared, non-excludable resource; any single country's restraint benefits everyone, but its costs fall on that country alone — creating an incentive to free-ride, the same structural logic as Week 14's security dilemma, applied to emissions instead of arms.
- Policy responses — present evenhandedly: carbon pricing (taxes or cap-and-trade) — proponents argue it lets markets find the cheapest reductions and raises revenue; critics argue it can be regressive and politically fragile. Direct regulation (efficiency standards, mandates) — proponents argue it delivers certain, verifiable reductions; critics argue it can be less cost-efficient than pricing. Subsidies for clean technology — proponents argue they accelerate deployment and build domestic industry; critics argue they can be costly and favor politically connected firms. Adaptation investment — proponents argue some warming is now unavoidable so resilience matters regardless of mitigation policy; critics worry adaptation-first framing can reduce urgency on mitigation. International coordination (treaties, pledges) — proponents point to the collective-action logic requiring joint action; critics note enforcement is weak and free-riding remains a live risk (Week 14's international-law lesson, applied again). All five are real, live policy debates with serious people and evidence on multiple sides.

Migration — documented patterns plainly, policy evenhandedly: migration flows are empirically well-studied and respond to measurable factors — wage and opportunity differentials between origin and destination, labor demand, conflict and displacement, family networks, and policy itself (visa rules, enforcement). That's the descriptive picture. Migration POLICY is where it turns normative and contested: proponents of more open migration policy argue it raises global output, fills labor-market gaps, and reflects a moral claim about freedom of movement; proponents of more restrictive policy argue it protects wages/jobs for some existing workers, preserves capacity to absorb and integrate arrivals, and reflects legitimate national self-governance over borders. Both invoke real economic findings and real values; they weigh them differently.

Segment 7 — Political Economy as the Subfield Bridge (15 min)

Go one level deeper — connect the week to the whole term:
- Political economy is not a sixth subfield — it's the name for work that sits at the seam of comparative politics (how do different mixed economies organize markets and states domestically? — Segment 2), international relations (how do states cooperate and compete economically, and manage shared problems like climate? — Segments 3 and 6), and political theory (what do we owe each other across borders, and how should gains and costs be distributed? — the normative layer running through every debate this week).
- The empirical/normative distinction, one more time, at its highest stakes: nearly every global-issues debate is the Week 1 "sandwich" again — a documented empirical claim (trade raises aggregate output; the poverty rate has fallen; greenhouse gases trap heat) + a normative principle (efficiency matters; growth matters; national sovereignty matters; global equity matters) → a policy conclusion. Good political analysis never lets the normative conclusion borrow the empirical claim's certainty. A number on a chart cannot, by itself, tell you what a country should do.
- The two failure modes, one final time: smuggling (presenting "we should adopt this trade policy" as though the poverty chart alone settled it) and shrugging (treating "well, people disagree about trade" as proof there's no fact of the matter about whether poverty actually declined). The discipline rejects both, right through the end of the term.

Quick interaction (~4 min): give the sandwich one last squeeze — "Extreme poverty has fallen sharply since 1990 (E); the countries that grew fastest were generally the ones most integrated into global trade (E — contested in its details, but broadly documented); therefore developing countries should prioritize trade integration over other development strategies (N-conclusion resting on further, arguable E-claims about causation and on a normative priority)." Have students label each layer, then ask: which layers could more data settle, and which layer is a values choice no dataset can make for you? (The first two are E-claims further data or research design could sharpen; the last is a policy priority — genuinely contested, and this week's assignment asks you to argue one side of exactly that kind of question, charitably.)

Segment 8 — Technology Workflow + AI-Critique, Callback & Hand-off (18 min) · Session 2 closes (~75)

Technology workflow — the data-reading habit, on demand:
1. Open any chart or statistic a chatbot, article, or classmate hands you. Before reacting, write three headers: What's measured / Line or definition used / Year(s).
2. Fill them in from the source's own page — not your memory of "a stat I've heard."
3. Note one thing the chart doesn't show (a limitation, a gap, an unstated cause).
4. Only then: your evaluation — and keep any policy conclusion clearly labeled as your own normative step, not something "the data proved."

AI-critique moment (students verify, not consume):

Paste this to an approved chatbot: "What percentage of the world lives in extreme poverty today, and what poverty line is currently used to define it?"
Then check its work against the real Our World in Data page linked in this module. The classic slips to catch: the chatbot naming an outdated poverty line ($1.90 or $2.15 instead of the current $3.00/day, updated June 2025) — a very easy mistake for any AI trained before the update, or for a chatbot that read an older article without noticing its own "last updated" note; inventing a precise percentage or "study" that isn't traceable to the source; sliding from "poverty fell" to "trade caused it" (or "aid caused it," or "capitalism caused it") without acknowledging that's a separate, contested causal claim; or taking a side on globalization, trade policy, or migration policy as though the data settled the normative question. Your job all term: the tool drafts, you verify against the source. This is exactly how the weekly Lecture Tutorial and the Political Analysis Workshop work — you catch the model, not trust it.

Callback + tease:
- Callback: "Everything this term comes together this week — the toolkit from Week 1 (concept application, argument analysis, evidence evaluation, comparison), the empirical/normative line that's run through every module, and now the read-the-data scaffold you've built across four quantitative pockets (Weeks 11, 12, 13, and today)."
- Tease next week: "Next week is our last: the cumulative Final Review. We'll walk back through all eight objectives — the discipline and its methods, power and the state, ideologies and theory, regimes and constitutions, institutions, the American case, participation and comparison, and international relations and political economy — and you'll show, one more time, that you can take any political claim apart: what kind of claim is it, and what's the evidence?"

Hand-off (the week's graded work):
- Lecture Tutorial 15 (AI tutor, share-link submission) — states and markets, comparative advantage vs. trade policy, climate as collective action, migration.
- Quiz 15, Discussion 15 ("Has Globalization Been a Net Good?"), and Assignment 15 ("Institutions or Transfers?" — a short thesis-driven policy argument using the OWID poverty data).
- Political Analysis Workshop 15 — Our World in Data, extreme poverty — read the chart, work the scaffold, then catch the AI's mistakes about it.

Instructor FAQ — Common Stumbles

Student says / does	Quick cure
"So is capitalism or socialism the right system?"	The course doesn't rank systems. Real economies mix markets and states in different ways (LME vs. CME); the comparative question is the mix and its institutions, not a label.
"If some workers lose from trade, comparative advantage is wrong."	Comparative advantage is about aggregate gains from specialization; distributional costs are a separate, equally real, well-documented finding — not a refutation.
Confuses poverty and inequality.	Poverty = below a threshold; inequality = spread of the whole distribution. A country can move on one without moving the same way on the other.
"Climate change is settled, so the policy is too."	The physical basics are a documented scientific finding; the POLICY response (which tool, how fast, who pays) is a separate, normative, genuinely contested question.
Cites "$2.15 a day" or "$1.90 a day" as the current global poverty line.	Those were the prior International Poverty Lines. The current one, since June 2025, is $3.00/day (2021 international-$) — always check the date on a poverty statistic.
Treats the falling poverty rate as proof that a specific policy (trade, aid, a particular ideology) caused it.	The chart shows a trend, not an experiment. Attributing the cause to any single factor is a further, contested claim the chart alone doesn't prove.
Expects the course to declare globalization simply "good" or "bad."	The course presents each side's strongest case — documented gains AND documented costs — and grades reasoning, never a verdict on the normative question.

Scope flag

This outline stays within Objective 8 (international relations and global political economy), building directly on Week 14's IR paradigms. It is not a full course in international economics — comparative advantage, trade policy, and the states-markets spectrum are introduced at the survey level a political-science student needs, not at the technical depth an economics major would receive. The climate section states the physical and scientific basics factually per the documented scientific-assessment record, without adjudicating policy choices, which are presented with proponents and critics. All named thinkers/frameworks (Ricardo's comparative advantage; Hall & Soskice's varieties-of-capitalism typology; the Moatsos 2021 and World Bank PIP poverty series) are real and cited factually. The instructor and institution remain fictional.

~ Prof. Halloran's edition · Fall 2026 · built with thecoursemaker.com