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Comparative politics · democracy and measurement

THE DEMOCRACY ALARM.

Two democracy reports sound different alarms.
Define the warning you can defend.

Bellara's election dashboard and democracy report tell different stories. As an independent analyst, audit the fictional documents before deciding what the public should hear. Read a real scholarly dispute about democratic backsliding, then trace authority, decisions and access through dated records. Build a transparent measurement charter with three indicators and two different rules for combining them. Compare country and population weighting, choose a verification project under a staff-hour limit, and test your rule in an unfamiliar municipal dossier. The challenge is to defend a specific warning with evidence, keep unknowns visible and explain which observation could make you revise it.

Start here. No advance reading required. Learn from the simplified explanations, examples and research-word help inside the activity. The journal articles are optional follow-up.

Created by Yoav Duman
Self-contained inquiry for introductory students · No advance reading required · Work in class or across sessions; student completion time has not yet been measured.

Original investigative political poster collage with print fragments, a microphone, public assembly silhouettes and civic documents; no case verdict or numerical data. Includes the Frontiers Simulations logo and creator credit.
Frontiers Simulations · Created by Yoav Duman

For class. For fun.

Choose the visible switch inside the app. For class: complete the source work, evidence activities, graph and table checks, written reasoning, transfer case and self-review, then save and submit as your instructor directs. For fun: browse every chapter, skip the forms, and print optional notes whenever you like. Switching modes preserves your work.

Audit the claim

Trace a dated institution, action and opportunity. Separate observed conditions from predicted electoral consequences.

Publish your rule

Define three operational indicators, apply two aggregation rules and make thresholds, weights and unknown policies explicit.

Challenge it elsewhere

Carry your rule into a new municipal inquiry, generate a rival and revise using evidence and a feasible next test.

A claim worth testing

Bellara / document inquiry

What process produced the disagreement, and which observation would distinguish your account from a credible rival?

Reconstruct the contributions of both articles, state a provisional claim and predict evidence that would distinguish it from a credible rival. Work with fictional records, numerical displays and institutional constraints before opening later evidence. Keep, narrow, change, or suspend the claim with reasons; preserve your initial account and explain your revision.

Go further · Why does resistance stop one attack but not another?

The core distinguishes an attempted loss from an implemented one. The new question asks which conditions make resistance effective.

Propose a comparison and competing predictions. This optional level explores a research question beyond the studies’ demonstrated findings; no invented result is presented as research evidence.

Research for everyone

Read the research. Follow the evidence.

No advance reading is required. These explanations introduce the research in everyday language for first-year students. Read them here or inside the simulation while working; the original articles and further reading are optional follow-up.

How the papers meet

This is a genuine empirical and conceptual dispute. Little and Meng argue that major increases in successful entrenchment should ordinarily register in electoral performance; they regard changing expert judgment as a likely contributor to the discrepancy, while acknowledging omitted dimensions and without directly measuring the bias contribution. Knutsen and colleagues question whether those indicators cover meaningful competition and test specific implications of a shared pessimism account. Their tests find little supporting evidence. A sentence saying “both measure different things” preserves a useful distinction but leaves the inferential disagreement unresolved. Bellara cannot settle a worldwide trend.

Article A / 2024

Measuring Democratic Backsliding

Andrew T. Little and Anne Meng
PS: Political Science & Politics
57(2): 149–161 · DOI 10.1017/S104909652300063X

The study records mostly stable aggregate electoral outcomes and argues that substantial successful entrenchment should ordinarily appear there. It favors a changing-judgment account for part of the discrepancy, without directly estimating that contribution. Coverage, performance, timing and the country-score restriction matter.

Explanation, evidence, and limits

In everyday terms: Little and Meng ask whether recent worldwide declines in democracy also appear in relatively easy-to-check election outcomes. Entrenchment means leaders making it harder to remove them from office. Keep their worldwide question separate from judging one country.

Democratic backsliding means weakening institutions or protections associated with democracy. It need not mean an immediate switch to dictatorship. Little and Meng ask whether the world as a whole experienced the large recent decline often described in public discussion. Their question concerns a cross-country trend, rather than whether a particular country has a serious problem.

Measuring a broad idea requires indicators: recorded signs of the thing we want to understand. An indicator such as whether the governing party lost an election is relatively easy to verify. Judging whether an entire election was free and fair requires weighing campaign access, intimidation, counting, and other conditions. The authors call the first kind more objective and the second more subjective; they argue that expert judgment offers wider coverage but can introduce bias.

Their main reasoning starts with electoral competition. Leaders weakening democracy often want to stay in office. If such efforts have become substantially more successful worldwide, we should expect governments to lose less often or winners to dominate more strongly. The authors therefore adopt a relatively narrow starting point centered on meaningful elections and acceptance of defeat. They also recognize that democracy requires rights, media freedom, and checks on executive power.

Study details · four evidence anchors

The study in four receipts

What should appear if entrenchment grows?
The proposed reasoning predicts less frequent electoral defeat or stronger incumbent dominance. Stable turnover is relevant evidence against that particular global pattern, even when it cannot capture every democratic protection.
What was actually observed?
Most electoral indicators do not show a clear recent global decline. The press indicators point in different directions. This is a collection of findings, rather than evidence that all institutions everywhere remained unchanged.
Was coder bias proven?
No direct estimate proves how much of the discrepancy is caused by changing expert judgment. The paper models and discusses that possibility alongside subtler undemocratic strategies.
Can the summary index diagnose one country?
No. The authors say their simple combined index is for summarizing aggregate trends, not an appropriate substitute for country-year democracy indices.

Sources include National Elections Across Democracy and Autocracy (NELDA), the Database of Political Institutions, expanded constitutional-constraint data, Versteeg and colleagues’ term-limit data, and the Committee to Protect Journalists. Coverage varies by measure; do not claim a single balanced sample size for every graph.

The 12-component summary index normalizes available indicators to 0–1 and averages them. Journalist killings and imprisonments are excluded from that index because coverage is shorter and most country-years have zero counts. Its numeric level has no substantive country-democracy interpretation.

The term-limit source identifies 234 end-of-term instances in 2000–2018; 60 serious evasion attempts and 34 successes. These are eligible-leader opportunities, not 234 countries or elections. The study finds no clear trend in evasion rates.

Population-weighted trends are more pessimistic and sensitive to the largest countries. Formal models explore a common change in coder information or standards and a leader’s choice between subtle and blatant violations. Models establish possible mechanisms, not the measured prevalence of those mechanisms.

How the researchers studied it

The study examines records from several sources: election outcomes and competition, constitutional constraints on leaders, attempts to evade term limits, and journalists jailed or killed. The unit is often a country-year: one country observed in one year. To avoid comparing only whichever countries held an election that year, some graphs carry forward a country’s most recent election if it occurred within six years.

Most main comparisons give each country equal weight. This answers a question about the average country, not the conditions experienced by the average person. The authors also examine population weighting, separate regime groups, and changes over longer periods. These are descriptive comparisons; countries and leaders were not randomly assigned to different democratic conditions.

What they found

Rates of ruling-party and leader turnover are broadly stable after the late 1990s. Winners’ vote or seat shares do not generally rise, and basic multiparty competition does not show the expected global decline. Constitutional constraints are largely stable or increasing. The press evidence is mixed: journalists jailed increase while murders decrease.

The authors regard time-varying expert judgment as a likely explanation for at least part of the discrepancy with more pessimistic indices. They model changing information or standards and discuss a shift toward subtle attacks. The descriptive comparisons do not directly estimate how much of the discrepancy is bias. Their official reply restates that restriction while insisting that the stable electoral patterns still require explanation.

Where the claim stops

Stable electoral indicators support a claim with clear limits about those indicators. They do not establish that every democratic protection stayed intact or that each country is safe. The authors explicitly accept backsliding in some countries. Election performance also reflects popularity and governing performance, so turnover is not a direct measure of every democratic condition.

Their simple combined index summarizes aggregate trends; they explicitly warn against using it as a country-year democracy score. Do not convert its numeric level into a valid diagnosis of one country. A local audit can expose an indicator’s limit without establishing the direction or size of a global trend.

Read What We Do; The Search for More Objective Measures; Taking Stock; Making Sense of the Data; and Conclusion.

Read first: Start with the explanation on this screen. Then check what was compared, what was found, and what remains uncertain. The journal article link is optional.

Open-access complete publisher text · CC BY.

Article B / 2024

Conceptual and Measurement Issues in Assessing Democratic Backsliding

Carl Henrik Knutsen, Kyle L. Marquardt, Brigitte Seim, Michael Coppedge, Amanda B. Edgell, Juraj Medzihorsky, Daniel Pemstein, Jan Teorell, John Gerring, and Staffan I. Lindberg
PS: Political Science & Politics
57(2): 162–177 · DOI 10.1017/S104909652300077X

The response argues that meaningful contestation requires supporting freedoms which low-threshold indicators can miss. It tests several implications of shared expert pessimism and finds little support for them. This is substantive evidence against specified bias accounts, without validating every rating or excluding every bias.

Explanation, evidence, and limits

In everyday terms: the response asks whether election outcomes alone miss important losses of rights, media freedom and checks on leaders. The disagreement concerns both what democracy means and how to measure change.

Knutsen and colleagues respond directly to Little and Meng. Their starting question is: what do we mean by democracy before we measure its change? A definition centered on the existence of competing parties captures something important. But people also need room to organize, discuss politics, obtain independent information, and challenge abuses. Losing one of these conditions may count as democratic erosion while elections continue.

A measure can be easy to reproduce yet poor at representing its intended concept. Counting whether several parties exist sets a low threshold: parties may remain legal while their ability to campaign deteriorates. Agreement about the count does not fix this missing coverage. Conversely, expert assessment may capture harder-to-observe conditions but needs clear questions, evidence, and reported uncertainty.

The authors also ask how signs should be combined. If a necessary protection disappears, should strengths elsewhere cancel it out in an average? How long a period should count as change? Several small annual losses can become a substantial decline over ten years. Giving each country equal weight and giving more weight to populous countries also answer different questions; neither choice should be concealed inside a single headline.

Study details · four evidence anchors

The study in four receipts

What can a stable party count miss?
Several parties can remain legal while access to independent information or organizing weakens. A low-threshold indicator may stay at its top value while a broader democratic condition deteriorates.
What did the ten-year comparison show?
On V-Dem’s Electoral Democracy Index for 2012–2022, 32 countries show discernible negative change and 11 positive change. More than 100 show no discernible change. The finding depends on the specified measure, period, and uncertainty rule.
How was changing judgment investigated?
The researchers examined previous-score revisions, the similarity of changes across countries, and patterns of expert disagreement. The tested patterns did not support a broad shared-pessimism explanation.
Why inspect missing records?
If information is disproportionately missing from declining countries, an average calculated only from the available cases can look healthier than the full population. Missing is not the same as unchanged.

V-Dem version 13 underlies the response. The 2012–2022 comparison uses 95% credible intervals for estimated changes. A credible interval represents uncertainty within the statistical model; it is not a forecast of a country’s political future.

The Electoral Democracy Index averages an additive and a multiplicative combination of five components. Suffrage and elected officials are fact-based components; expression, association, and clean elections aggregate several expert-coded indicators. The model adjusts for reliability and differences in how experts use the rating scales.

The response reports 43% of country-years missing a quarter or more of Little and Meng’s 12 index indicators and 11% missing half or more. Their regressions show that missingness is associated with lower EDI and declining EDI, raising a selection concern rather than proving every missing value is bad.

The authors compare coder-level scores across V-Dem versions 9 (2019) and 13 (2023), plus other checks. These indirect tests address predicted patterns of bias and cannot rule out all possible common shifts. Several authors are involved in V-Dem; assess their evidence and tests rather than infer validity or invalidity from that involvement.

How the researchers studied it

They compare Little and Meng’s measures with V-Dem’s Electoral Democracy Index, which combines elected officials, voting rights, freedom of association, freedom of expression, and clean elections. V-Dem experts answer defined questions about specific conditions; they do not simply assign a general democracy mood score. A statistical measurement model combines their answers and represents uncertainty.

The authors test implications of the proposed changing-pessimism bias. They inspect whether declines are broadly synchronized, whether successive data releases revise earlier judgments downward, and whether expert disagreement follows systematic patterns. They also examine missing data, indicator thresholds, and how the combined index behaves in known historical cases.

What they found

Across 2012–2022, they identify 32 countries with clearly discernible negative changes and 11 with positive changes on the Electoral Democracy Index; more than 100 have no discernible change. “Discernible” means the estimated change’s 95% uncertainty interval excludes zero, which would mean no change. The interval describes imprecision in the estimate. These are not counts of every possible small decline or improvement.

Their tests find little to no evidence for the proposed shared pessimism pattern. Declines differ across countries and components: expression and civil society often deteriorate while electoral measures are less affected. They argue that limited coverage, low thresholds, and systematic missingness weaken Little and Meng’s measures as a benchmark for broader democracy.

Where the claim stops

The response supports the existence of recent backsliding on a broader, specified conception. It does not prove that every expert rating is accurate or rule out every conceivable changing bias. The authors acknowledge that their model cannot directly correct a synchronized shift in every expert’s standards.

An uncertainty interval concerns an estimate, not a guarantee that a government is safe when zero is included. Definitions, periods, missingness and weighting can produce different trends. A fictional local audit is not a new V-Dem observation or a test of the worldwide conclusion.

Read Conceptualizing Democracy; Conceptualizing Backsliding; Biases in V-Dem Measures?; Objective versus Subjective Measures; and Conclusion.

Read first: Start with the explanation on this screen. Then check what was compared, what was found, and what remains uncertain. The journal article link is optional.

Open-access complete publisher text · CC BY.

Keep investigating.

Follow a question beyond the core pair, including a research synthesis from Annual Review of Political Science.

Further reading / 2024

What We Do and Do Not Know about Democratic Backsliding

Andrew T. Little and Anne Meng
PS: Political Science & Politics
57(2): 224–229 · DOI 10.1017/S1049096523001038

The authors’ official reply separates their observed electoral patterns from disputed explanations. It restates the country-score warning, acknowledges no direct test of coder bias in their original article, and asks for more evidence on rights, institutions, and resilience. It is part of the same controversy, not a correction notice.

Try this question: Which disagreement concerns the recorded pattern, and which concerns whether that pattern adequately represents democratic change?

Open-access complete publisher text · CC BY.

Further reading / 2024

An Events-Based Approach to Understanding Democratic Erosion

Hannah Baron, Robert A. Blair, Jessica Gottlieb, and Laura Paler
PS: Political Science & Politics
57(2): 208–215 · DOI 10.1017/S1049096523001026

The Democratic Erosion Event Dataset records political events and resistance alongside country scores. Turkey and Brazil illustrate how events can reveal erosion missed by narrow measures, or resistance obscured by an alarming summary. Event selection and classification still require judgment. Two case studies illuminate a process without settling the worldwide rate.

Try this question: How would you distinguish an attack, its implementation, and the resistance that prevents it from producing a lasting loss?

Open-access complete publisher text · CC BY.

Further reading / 2024

Measuring Backsliding with Observables: Observable-to-Subjective Score Mapping

Daniel Weitzel, John Gerring, Daniel Pemstein, and Svend-Erik Skaaning
PS: Political Science & Politics
57(2): 216–223 · DOI 10.1017/S1049096523001075

A model trained on earlier observable institutions predicts established democracy indices in later years. The analysis suggests some decline, with timing and size varying across indices. The authors stress that predictive consistency does not establish whether the measure captures the intended idea: a model can reproduce earlier judgments without knowing whether those judgments were right.

Try this question: If a model accurately reproduces past ratings, what must still be checked before calling it a valid democracy measure?

Open-access complete publisher text · CC BY.

These two 2024 articles belong to a published controversy in PS: Political Science & Politics. Little and Meng question strong claims of recent global decline using relatively observable indicators; Knutsen and colleagues respond directly by challenging measurement choices and testing proposed expert bias. Their disagreement offers a live problem about evidence, definitions, and the scope of a conclusion.

Open / print the complete reading guide ↗

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Everything you need.

Launch in your browser, download a self-contained copy, or take the whole resource pack. No account or API key is needed.

Optional online saving keeps private drafts recoverable with your recovery key. A class submission requires a class code and your explicit consent.

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Read / print the packet online ↗ · Student guide online ↗ · Instructor guide online ↗ · File and saving notes ↗

Review and revision records

The earlier faculty-role reports are AI assessments prepared before publication. They are included as an assessment archive, rather than evidence of trials with recruited faculty or students.

Full faculty-role assessments · PDF ↗ · Faculty-led revision record · PDF ↗

Each complete ZIP contains this simulation, the three PDF guides, editable Word worksheet, printable HTML guides, poster, original artwork, all logo variants, source/configuration files, a portable backend, and the review archive. Journal articles are linked; journal PDFs are not bundled.

In the classroom

Give the finding room to develop.

Use this module to teach concepts, indicators and the political consequences of measurement. No advance reading is required. Students use the explanations inside the activity. In class, students can compare the scholars' strongest arguments, commit a document-based explanation and challenge one another's proposed warning rules. The fictional dossiers support different bounded conclusions; students must show the evidence and assumptions behind their choice. A focused seminar begins the inquiry, while complete operational rules, calculations and independent transfer require further work. Human assessment uses six criteria. No personal political disclosure is needed: discussion can stay with the invented institutions and records.

Assess the connection from claim to predicted observation, the interpretation of a specific record, and the reason for retaining or revising after a challenge. Use a receipt from each article, a precise limitation, and a useful next test. The app offers feedback on fixed-choice questions; students’ written findings are drafts for review.

Progress saves on the current browser. Export a JSON progress file to restore your work later; download the text brief or print your record to save a PDF. Printing and downloading do not submit work to Canvas. Optional private online saving and consented class submission are available inside the app; follow your instructor’s directions for separate Canvas submission.

Open the instructor guide ↗