Milestone map
Milestone map
3 milestones
Collect and describe a real electoral or voting systems dataset
4 weeks
Obtain a real electoral dataset from a public elections commission, an academic data repository (Harvard Dataverse, ICPSR), or a government open-data portal. Describe the dataset: what elections are covered, what the key variables are, what the unit of analysis is (constituency, party, candidate, election), data quality issues (missing values, rounding), and what research questions can be addressed with it. Produce descriptive statistics: vote shares by party across time or geography, turnout patterns, and at least one geographic or temporal comparison.
Proof required
Data description document (500+ words) with the dataset source and access method, key variables with definitions, data quality notes, descriptive statistics covering vote shares and turnout, and at least one comparison across time or geography supported by tables or charts.
What gets checked
- Dataset is from a real public source with an accessible link or repository citation
- Data quality issues are documented — missing data, definitional changes across time, or rounding are addressed
- At least one geographic or temporal comparison is supported by specific numbers, not just described
Common mistakes
- Treating the dataset as clean without investigating data quality — real electoral datasets have well-documented irregularities that affect analysis
- Describing vote shares without temporal or geographic comparison — the pattern only becomes meaningful relative to other elections or constituencies
- Not documenting the data access method — another researcher must be able to replicate the dataset acquisition
Resources
Foundationstart here
Depthgo deeper
What a verifier looks for
- Confirm the dataset is from a real public source — access the cited link
- Review the data quality section — confirm it addresses specific known issues in the dataset
- Check the comparison — confirm it is supported by specific numbers in tables or charts
Analyse electoral patterns and develop an evidence-based interpretation
4 weeks
Using the dataset from M1, analyse a specific electoral pattern or research question: voting system effects on party fragmentation, the relationship between turnout and margin of victory, geographic polarisation over time, or demographic predictors of party support. Apply an appropriate quantitative method (regression, correlation, chi-square, or time-series comparison) and produce an interpretation that connects the data pattern to a theoretical explanation from electoral studies or political science.
Proof required
Electoral analysis document (500+ words) applying a quantitative method to the M1 dataset, interpreting the results in relation to a named theoretical explanation, and noting at least one alternative interpretation of the same data pattern.
What gets checked
- Quantitative method is described and applied correctly — results are reproducible from the described steps
- Interpretation connects data to a named theoretical explanation from electoral studies — not just a data description
- At least one alternative interpretation is documented and explained
Common mistakes
- Describing the pattern without explaining it — an analysis that says 'turnout declined over time' without a theoretical account of why is data journalism, not analysis
- Choosing a theoretical explanation without addressing whether the data is consistent with it — the analysis must test whether the data fits the theory
- Not documenting alternative interpretations — real electoral data can often support multiple theoretical accounts
Resources
What a verifier looks for
- Review the quantitative method application — confirm results are reproducible from the described steps
- Check the theoretical interpretation — confirm a named theory from electoral studies is applied, not a general claim
- Verify at least one alternative interpretation is documented
Defend electoral analysis under political scientist challenge
1 week
Present the electoral data analysis to a political scientist or elections researcher for a Q&A challenge. The reviewer must probe the interpretation — 'your analysis shows X but an alternative explanation is Y — how do you rule Y out?', 'this pattern holds in period A but reverses in period B — why?', 'your dataset covers only one country — how generalizable is your interpretation?'. Document the challenges and your responses. This Q&A satisfies the ADVERSARIAL VERIFICATION RULE.
Proof required
Q&A notes (250+ words) documenting the reviewer's credentials (political scientist or elections researcher), at least three specific challenges to the interpretation, your responses, and any analysis updates committed to.
What gets checked
- Reviewer is a political scientist or elections researcher with relevant expertise
- At least three specific interpretation challenges are documented
- At least one analysis update is documented based on the session
Common mistakes
- Choosing a reviewer unfamiliar with electoral studies — the challenge must be domain-specific to electoral data interpretation
- Not being able to discuss generalizability under challenge — single-country or single-election analyses always have generalizability constraints that must be acknowledged
- Not updating the analysis based on a legitimate alternative interpretation challenge
Resources
What a verifier looks for
- Confirm the reviewer is a political scientist or elections researcher
- Review Q&A notes — confirm at least three specific interpretation challenges are documented
- Check that at least one analysis update is documented