Party registration tells you how voters identify. Candidate election results tell you which party wins. But neither tells you what voters actually believe about policy.
A jurisdiction can be strongly Democratic in registration and candidate voting, yet conservative on criminal justice, moderate on taxes, and progressive on social issues. Ideology analysis reveals these cross-cutting patterns by examining how voters behave when party labels are removed—on ballot measures.
Why Ballot Measure Voting Matters
Ballot propositions are the cleanest test of policy preferences:
- No party labels appear on the ballot. Voters must decide based on the issue itself.
- Propositions span the full range of issues. Taxes, bonds, criminal justice, social policy, housing, labor, governance—the full ideological spectrum gets tested over time.
- Results are revealed preferences, not stated preferences. This is how voters actually behave, not how they say they would.
A D+25 district that votes against rent control and for tougher sentencing is telling you something important about its actual policy preferences—information that registration alone would never reveal.
Finding Ideology Analysis
On any jurisdiction page, click the Voters tab, then select Ideology Analysis from the submenu. You can also reach it from the Summary tab by clicking the link in the Ideology section.
The page shows an overall ideology classification at the top, followed by category-by-category breakdowns. Below that, you can browse individual proposition results by election year.
The Core Insight: Issue-Specific Ideology
The most common mistake is treating ideology as monolithic. It isn't.
The platform breaks ideology into five categories:
- Tax-Related Measures: New taxes, tax increases, tax repeals
- Bond Measures: State or local borrowing for infrastructure, schools, housing
- Social Issues: Civil rights, marijuana, bilingual education, affirmative action
- Criminal Justice: Sentencing, parole, police practices, incarceration
- Rent Control: Expanding or restricting local rent control authority
A jurisdiction can be:
- Progressive on social issues and bonds
- Moderate on taxes
- Conservative on criminal justice
This is common—and knowing the pattern is essential for messaging strategy, issue prioritization, and coalition building.
How the Ideology Scores Work
Ideology scores are percentile rankings, not vote percentages.
A score of 75 in "Tax-Related Measures" means this jurisdiction votes more progressively on tax propositions than 75% of similar jurisdictions. It does not mean 75% of voters are progressive.
Each proposition is classified based on the typical partisan divide:
- For propositions where "Yes" aligns with progressive positions, higher Yes percentages yield higher progressive scores
- For propositions where "Yes" aligns with conservative positions (like tougher sentencing), the scale is inverted
This ensures the spectrum is consistent: Progressive always means the same directional lean regardless of how the proposition was worded.
Interpreting Proposition Results
For any election year, you can see individual proposition results showing:
- This jurisdiction's Yes/No percentages
- Comparison to statewide results (was local support higher or lower than California overall?)
- Standing relative to similar jurisdictions (Very High, High, Average, Low, Very Low support)
A proposition might pass statewide but fail locally—or vice versa. The statewide outcome badge tells you what happened overall; the local percentage tells you how this specific area voted.
The "standing" comparison is often more revealing than the raw percentage. A 52% Yes vote might seem like weak support—until you see that similar jurisdictions averaged 65%, meaning this area was actually conservative on that issue relative to peers.
What This Analysis Is For
Validating or challenging assumptions. You assume a D+30 district is progressive. The ideology breakdown shows it's "Conservative" on criminal justice and "Moderate" on taxes. Your messaging strategy needs to account for this complexity.
Issue-specific viability assessment. Before running a local ballot measure, check how voters have historically responded to similar issues. If rent control has failed 60-40 in the last two cycles, you face headwinds regardless of party registration.
Messaging calibration. A Democratic candidate in a district that's progressive on social issues but moderate on taxes might emphasize social policy and downplay tax-increase proposals. A Republican in a district that's conservative on crime but progressive on bonds might lead with public safety while avoiding anti-infrastructure messaging.
Coalition analysis. Jurisdictions with unusual ideological profiles (progressive on some issues, conservative on others) often contain persuadable voters who don't fit neat partisan categories.
Important Caveats
Past voting is not prediction. Historical patterns are the best baseline, but novel propositions can break precedent. Unusual campaign spending, confusing ballot language, or unique coalitions can shift outcomes away from historical tendencies.
Proposition classification involves judgment. The "progressive" or "conservative" label on each proposition reflects typical partisan alignments, but some measures attract unusual coalitions that don't fit the standard mold.
Only statewide propositions are included. Local ballot measures are not part of the ideology calculation. A jurisdiction's stance on local issues may differ from its statewide voting patterns.
Campaign effects are not visible. Heavy spending or misleading advertising can swing results in ways that don't reflect underlying ideology. A narrow loss for a progressive measure after a $50 million opposition campaign tells a different story than the raw percentage suggests.
Common Mistakes
Assuming party registration equals issue positions. A D+25 district is not necessarily progressive on every issue. Many Democratic-registered voters diverge from party positions on criminal justice, taxes, or rent control.
Over-interpreting single propositions. One proposition result is not reliable. The category aggregates exist precisely because individual measures can be swayed by idiosyncratic factors.
Treating percentiles as percentages. An ideology percentile of 70 does not mean 70% of voters are progressive. It means this jurisdiction votes more progressively than 70% of similar jurisdictions.
Ideology analysis reveals the policy preferences that registration and candidate voting obscure. Use it to understand what voters actually believe—not just how they identify.