Progressive policies are popular in Ohio. According to a Data for Progress poll of likely Ohio voters:

• 71% support having the wealthiest do their part by paying closer to what they actually owe in taxes.
• 60%of likely Ohio voters said they want Ohioans to be paid more fairly for the work they do by setting the minimum wage at $15 an hour.
• 77% want to make sure families can make ends meet and set up their children for success by creating a state child tax credit.
• 66% said mental health and behavioral health issues should be addressed by health care providers and expressed support for a “health-first response.”
• 70% said they wanted to have more of a say in how government works though participatory budgeting.

Poll results are available at House- and Senate-district level, so advocates can use these data to speak knowledgeably to their representatives.

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Data for Progress estimates opinion for a set of policy proposals at the district level using a machine learning model. The model is trained on state representative survey responses linked to a commercial voter file, and accounts for over 400 variables, including individual demographic characteristics, vote history, and primary participation as well as the political and demographic characteristics of the respondents’ census tract.

Once trained on the survey data, the model is used to score individual voters on their probability of support for a set of policies and aggregate those support scores by different geographies across a variety of political environments. The process used is known as MRP (or Multilevel regression with poststratification). Support is displayed by modeling two-way support for an issue at the voter level. Since this is an estimation technique, the measure of uncertainty is roughly double that of a traditional polling instrument. The model remains informative, especially when comparing values, but it is important to be aware of its additional uncertainty.

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