Skills

Electoral and Voting Systems Analysis

8 weeks · 0 milestones

Conduct a real electoral data analysis using publicly available official election data from a named electoral authority. Analyse a specific named election or electoral system and draw a concrete, evidence-based conclusion about voting behaviour or system effects. Document your methodology and data sources. Proof is the analysis plus a Q&A with a political scientist or quantitative analyst who challenges your interpretation — specifically, what alternative explanations exist for the patterns you found. Your written response is a required part of the proof.

Part of: Social Sciences, Law & Humanities · Proves for: UG

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

Powstik Guide

A 500-word description of a real electoral dataset.

Steps

Name the source and access method.
Define each key variable.
Report coverage and missing data.
Describe the voting system behind it.

Template

Dataset:        Access:
| Variable | Definition |
|----------|------------|
Coverage and gaps:
Electoral system:

What gets sent back

Under 500 words.
Sources uncited.
Hypothetical instead of real.

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

You'll sign in first, then come straight back here.

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

Powstik Guide

A tested explanation for one electoral pattern.

Steps

Pick one question your dataset can answer.
Name the theory you'll test against it.
Run one clear method: comparison, correlation or regression.
Check whether the result fits the theory's prediction.
Give one other explanation for the same pattern.

Template

Question:
Theory and its prediction:
Method:
Result (with numbers):
Consistent with the theory? Why:
Alternative explanation:

What gets sent back

A pattern described but not explained.
A theory never tested against the data.
No alternative explanation.

Resources

Foundationstart here

Depthgo deeper

Masteryfor the dedicated

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

You'll sign in first, then come straight back here.

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

Powstik Guide

Your electoral analysis, challenged by an elections researcher.

Steps

State how far your finding generalises, and where it stops.
Check you haven't made individual claims from area data.
Book a political scientist or elections researcher.
Ask for three challenges to your interpretation.

Template

Challenge session log
Date:            Duration:
Reviewer name:
Reviewer role and credentials:

Challenge 1 (interpretation or generalisability):
  What they asked:
  My answer:
  Did it hold?
Challenge 2:
  What they asked:
  My answer:
  Did it hold?
Challenge 3:
  What they asked:
  My answer:
  Did it hold?

Update I am committing to:

What gets sent back

A reviewer outside electoral studies.
No limits on generalisation stated.
No update after the session.

Resources

Foundationstart here

Depthgo deeper

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

You'll sign in first, then come straight back here.

Part of

Political Science & Public Policy →

Related outcomes

Milestone map

3 milestones

Collect and describe a real electoral or voting systems dataset

4 weeks

Proof required

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

Powstik Guide

A 500-word description of a real electoral dataset.

Steps

Name the source and access method.
Define each key variable.
Report coverage and missing data.
Describe the voting system behind it.

Template

Dataset:        Access:
| Variable | Definition |
|----------|------------|
Coverage and gaps:
Electoral system:

What gets sent back

Under 500 words.
Sources uncited.
Hypothetical instead of real.

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

You'll sign in first, then come straight back here.

Analyse electoral patterns and develop an evidence-based interpretation

4 weeks

Proof required

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

Powstik Guide

A tested explanation for one electoral pattern.

Steps

Pick one question your dataset can answer.
Name the theory you'll test against it.
Run one clear method: comparison, correlation or regression.
Check whether the result fits the theory's prediction.
Give one other explanation for the same pattern.

Template

Question:
Theory and its prediction:
Method:
Result (with numbers):
Consistent with the theory? Why:
Alternative explanation:

What gets sent back

A pattern described but not explained.
A theory never tested against the data.
No alternative explanation.

Resources

Foundationstart here

Depthgo deeper

Masteryfor the dedicated

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

You'll sign in first, then come straight back here.

Defend electoral analysis under political scientist challenge

1 week

Proof required

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

Powstik Guide

Your electoral analysis, challenged by an elections researcher.

Steps

State how far your finding generalises, and where it stops.
Check you haven't made individual claims from area data.
Book a political scientist or elections researcher.
Ask for three challenges to your interpretation.

Template

Challenge session log
Date:            Duration:
Reviewer name:
Reviewer role and credentials:

Challenge 1 (interpretation or generalisability):
  What they asked:
  My answer:
  Did it hold?
Challenge 2:
  What they asked:
  My answer:
  Did it hold?
Challenge 3:
  What they asked:
  My answer:
  Did it hold?

Update I am committing to:

What gets sent back

A reviewer outside electoral studies.
No limits on generalisation stated.
No update after the session.

Resources

Foundationstart here

Depthgo deeper

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

You'll sign in first, then come straight back here.