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State-Level Audience Size and Demographic Composition Estimates
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Release Notes
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This report and the data are published using the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) license. Anyone is free to share this report so long as you give appropriate credit (“Attribution”), do not use it for commercial purposes (“Non-Commercial”), and do not remix or transform the materials (“No Derivatives”). All third party and underlying copyrights contained in this report are reserved. The views and opinions expressed in this report are those of the authors and do not necessarily reflect the positions of Story at Scale’s funders or partners.
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Detailed Story at Scale Audience Distribution Estimates
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These release notes describe state-level Story at Scale audience estimates. You can find the cross-tabulations here. The document below describes how the estimates were constructed and how to interpret the values.
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Story at Scale
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Story at Scale is a year-long collaboration of researchers, data scientists, artists, advocates, and organizers to develop and test a new cultural strategy to advance gender justice. Using big data and a collaborative, creative process, Story at Scale delivers audience research and a narrative foundation to guide artists and campaigners in telling stories that reflect the world we seek: a joy-filled life in a gender-just future. Story at Scale’s tools are designed for practical use by those working on issues ranging from reproductive justice to sex- and gender-based violence to LGBTQ+ rights and more.
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The Story at Scale Audiences
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To ensure that our stories reach our audiences, we need to know not just what we want to say but what our audiences will hear. The Story at Scale audience profiles are not about political issues or even gender justice; they are about how gender works in our audiences’ lives today. Our research, based on an original survey of more than 6,000 respondents, revealed six audiences with different (and distinct) lived gender stories.
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You can find detailed descriptions of the audiences on the Story at Scale website. For more on the specific methods we used to create the audiences, please see the Audience Research report.
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Creating National Models
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We created national models to help us understand where the audiences are, how old they are, and what their other important identities might be. To generate the state-level audience distribution estimates, we:
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1. Matched the survey responses to the Catalist voter file
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2. Created statistical models predicting segment membership from features on the voter file including vote history, age, and gender
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3. Scored those models on all registered (active and inactive) voters in the United States
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4. Used those national scores to create estimates of audience membership by state, age, race, and gender
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How to Use the Estimates
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These estimates are just that--estimates--highly educated, machine learning-informed guesses. They are not precise counts of people or voters, but they do suggest patterns. They are best used for planning your story strategy rather than for micro-targeting. You can use them to think about:
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*The coalition of likely voters where you are. Can you achieve a win on your gender justice issue with the base (Force for Good and Justice Rising) alone, or do you need to reach another audience such as Kids First?
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*The audiences with the greatest need to hear from you where you are. Are you in a state with many No Special Treatment members? They might be targeted by conservative messaging. For the Win? They tend not to engage politically and could suffer by their absence from the 2020 election. Justice Rising? They have so much potential to fight for gender justice, but they need to hear about our vision about a safe, abundant future.
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*The demographic profiles of the audiences that interest you. In Georgia, Kids First is 71% African American. In Michigan, that audience is 62% white. How could those intersectional identities affect the stories you tell in this audience about abundance or curiosity and the future?
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The Tables and Measures
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This section describes what is in each table. For some details on the limitations of these data, scroll down to the next section.
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All Registered Voters by State
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This table shows how all registered voters are distributed across audiences.
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ColumnDefinition
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StateTwo letter state abbreviation
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Registered Voters (Approx.)An approximate count of the total registered voters in the state
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Justice RisingThe percent of all registered voters who are Justice Rising
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Force for GoodThe percent of all registered voters who are Force for Good
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Kids FirstThe percent of all registered voters who are Kids First
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For the WinThe percent of all registered voters who are For the Win
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No Special TreatmentThe percent of all registered voters who are No Special Treatment
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Religious TraditionalistsThe percent of all registered voters who are Religious Traditionalists
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2020 Expected Voters by State
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This table shows how voters in the 2020 general are distributed across audiences.
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ColumnDefinition
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StateTwo letter state abbreviation
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Registered Voters (Approx.)An approximate count of the total registered voters in the state
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Estimated 2020 Voters (Approx.)An approximate count of the voters expected to turn out in the 2020 general election in the state
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Justice RisingThe percent of all expected 2020 voters who are Justice Rising
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Force for GoodThe percent of all expected 2020 voters who are Force for Good
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Kids FirstThe percent of all expected 2020 voters who are Kids First
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For the WinThe percent of all expected 2020 voters who are For the Win
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No Special TreatmentThe percent of all expected 2020 voters who are No Special Treatment
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Religious TraditionalistsThe percent of all expected 2020 voters who are Religious Traditionalists
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Detailed State Profiles
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This table describes each audience in each state in terms of demographic and lifestyle characteristics
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ColumnDefinition
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StateTwo letter state abbreviation
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DemographicThe demographic category (e.g., "Gender")
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College DegreeBased on the Catalist education model, the estimated proportion of the audience that has a college degree
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Kids at HomeBased on the Catalist model, the estimated proportion of the audience that has kids living at home
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Economic SensitivityBased on the Catalist model of responses to questions about late payments on debt and ability to weather a personal financial crisis, this is a propensity rather than a percent. Values 0.7 + are considered very Sensitive
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GenderGender as recorded on the voter file. Note that other genders and identities are not included because those data are not available from states.
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RaceRace as recorded on the voter file in some states and as predicted by the Catalist race model where not reported by states
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GroupThe group or measure within the demographic category (e.g., "Women")
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Justice RisingThe percent (or propensity) for the measure within the group. (e.g., 32% of Justice Rising in Alaska has a college degree)
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Force for GoodThe percent (or propensity) for the measure within the group.
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Kids FirstThe percent (or propensity) for the measure within the group.
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For the WinThe percent (or propensity) for the measure within the group.
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No Special TreatmentThe percent (or propensity) for the measure within the group.
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Religious TraditionalistsThe percent (or propensity) for the measure within the group.
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2020 Expected Voters by Metropolitan Area
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This table shows how voters in the 2020 general are distributed across audiences.
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ColumnDefinition
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StateTwo letter state abbreviation
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Metropolitan AreaCensus Metropolitan Area (CBSA)
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Registered Voters (Approx.)An approximate count of the total registered voters in the state
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Estimated 2020 Voters (Approx.)An approximate count of the voters expected to turn out in the 2020 general election in the state
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Justice RisingThe percent of all expected 2020 voters who are Justice Rising
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Force for GoodThe percent of all expected 2020 voters who are Force for Good
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Kids FirstThe percent of all expected 2020 voters who are Kids First
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For the WinThe percent of all expected 2020 voters who are For the Win
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No Special TreatmentThe percent of all expected 2020 voters who are No Special Treatment
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Religious TraditionalistsThe percent of all expected 2020 voters who are Religious Traditionalists
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2020 GOTV Opportunity by State and Race
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This table shows how voters in the 2020 general election are distributed across audiences.
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Net impact of GOTV: Get Out the Vote program within a segment can turn out both conservative and progressive votes. Segments with Large Net Progressive GOTV have (1) a relatively large number of non-voters who can be turned out and (2) a relatively large number of progressive non-voters who can be turned out. Segments with Large Net Conservative GOTV are likely to yield many more conservatives than progressives. All these estimates are the impacts of statewide GOTV campaigns
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