Where we called:
Each point shows one of the 27871 calls we made.
Choice of vote: Dem. representative I do not know Did not respond
Explore the 2016 election in detail with this interactive map.
About the race
Gil Cisneros is a Navy veteran, lottery jackpot winner and philanthropist. 41% favorable rating; 36% unfavorable; 23% don’t know
Young Kim is a South Korean immigrant who has served as state representative and assistant to the current representative. 46% favorable rating; 35% unfavorable; 19% don’t know
The district, which chose Hillary Clinton in 2016, includes parts of Los Angeles, Orange, and San Bernardino counties, including towns like Yorba Linda, Diamond Bar, and Hacienda Heights.
With the retirement of the longtime Republican incumbent president, Democrats are targeting the district as one of the most competitive in Southern California.
Mr. Cisneros, a political newcomer, is a former Republican – he changed his party affiliation in 2008 because he felt the GOP was getting too ideological. After winning the California Mega Millions Lottery in 2010, he created and became involved in several philanthropic efforts in the arts, education and veterans. He raised nearly $ 10 million against Ms. Kim’s $ 2.2 million in the most recent reporting period, but $ 8 million is his own money that he loaned to his campaign.
Ms Kim, who was seconded by outgoing Ed Royce, emphasizes her connection to the district through her two-decade work in Mr Royce’s office. Ms Kim shared her own immigration story to highlight her take on immigration, saying she supports increased border security as well as compassion for children brought to the United States without legal papers.
California’s 39th has the largest Asian-American population of any battlefield districts, and Asian voters were a big part of the reason the district swung so heavily to Hillary Clinton in 2016. The Extra Appeal Ms. Kim’s for Asian Americans could be a big part of why Republicans stand a chance to hang out in such a diverse neighborhood.
Results of previous elections:
|President 2016||+9 Clinton|
|President 2012||+4 Romney|
|House 2016||+14 Rep.|
It’s usually best to look at a single poll in the context of other polls:
Our participation model
There is a big question in addition to the standard margin of error in a poll: who is going to vote? It’s a particularly difficult question this year, as the special election showed Democrats voting in large numbers.
To estimate the likely electorate, we combine what people say about their likelihood of voting with information about how often they have voted in the past. In previous races, this approach was more precise than just taking people at their word. But there are plenty of other ways to do it.
Assumptions about who will vote can be especially important in this race.
Our survey under different participation scenarios
|Who will vote?||Is. turn out||Our poll result|
|The types of people who voted in 2014||164,000||Kim +5|
|People whose voting history suggests they will vote no matter what they say||192 KB||Cisneros +1|
|Our estimate||193,000||Cisneros +1|
|People who say they will vote, adjusted for past levels of truthfulness||209,000||Cisneros +4|
|People who say they are almost certain to vote, and no one else||220,000||Cisneros +13|
|The types of people who voted in 2016||260,000||Cisneros +4|
|Each active registered voter||351,000||Cisneros +10|
In these scenarios, higher turnout tends to be better for Democrats.
The types of people we have reached
Even if the participation rate was exactly correct, the margin of error would not capture all the error in a survey. The simplest version assumes that we have a perfect random sample of the voting population. We dont do.
People who respond to polls are almost always too old, too white, too educated, and too politically engaged to accurately represent everyone.
How successful we were in reaching different types of voters
|18 to 29||3062||73||1 of 42||15%||13%|
|30 to 64||16473||274||1 in 60||55%||56%|
|65 and over||6542||148||1 of 44||30%||32%|
|Man||10529||270||1 of 39||54%||48%|
|Female||15558||226||1 of 69||46%||52%|
|White||11369||238||1 of 48||48%||49%|
|Not white||13082||220||1 in 59||44%||45%|
|Cell||19620||392||1 in 50||79%||–|
|Fixed line||6467||104||1 of 62||21%||–|
Pollsters compensate by giving more weight to respondents from under-represented groups.
Here, we weight by age, party registration, gender, probability of voting, race and region, primarily using data from voting log files compiled by L2, a non-partisan voter registration provider.
But weighting only works if you weight by the right categories and know what the make-up of the electorate will be. In 2016, many pollsters did not weight by education and overestimated Hillary Clinton’s position accordingly.
Even after weighting, our poll doesn’t have as many types of people as we would like.
Here are other common ways to weight a poll:
Our survey according to different weighting schemes
|Our poll result|
|Do not weight by party registration, like most public polls||Cisneros +2|
|Don’t weight by education, as in many polls in 2016||Cisneros +1|
|Our estimate||Cisneros +1|
|Weighting using census data instead of voting records, like most public polls||same|
About 7% of voters said they were undecided or refused to tell us who they would vote for.
Problems and other questions
Do you approve or disapprove of Donald Trump’s work as president?
|Approve||Disapp.||I do not know|
|The electors n = 496||45%||51%||4%|
Do you prefer Republicans to retain control of the House of Representatives or would you prefer Democrats to take control?
|Keep House representatives||Dems. take house||I do not know|
|The electors n = 496||47%||47%||6%|
What different types of voters said
Voters across the country are deeply divided along demographic lines. Our survey also suggests divisions. But don’t overinterpret these tables. Results among subgroups may not be representative or reliable. Be especially careful with groups of less than 100 respondents, shown here in bands.
|Female n = 226 / 52% of voters||50%||44%||6%|
|Man 270 / 48%||44%||48%||8%|
|18 to 29 n = 72 / 13% of voters||57%||32%||11%|
|30 to 44 95 / 16%||49%||36%||15%|
|45 to 64 181 / 40%||41%||54%||5%|
|65 and over 148 / 31%||50%||46%||4%|
|White n = 244 / 50% of voters||38%||57%||5%|
|Black 15 / 3%||83%||11%||7%|
|Hispanic 126 / 24%||58%||36%||6%|
|Asian 77 / 15%||50%||34%||16%|
|Other 23 / 5%||48%||47%||4%|
Race and education
|Not white n = 241 / 48% of voters||56%||35%||9%|
|White, college graduate 140 / 26%||42%||52%||6%|
|White, not a college graduate 104 / 24%||34%||62%||4%|
|HS Grad. or less n = 51 / 10% of voters||45%||44%||11%|
|Some College Educ. 150 / 33%||44%||50%||6%|
|4-year university graduate. 156 / 33%||51%||42%||7%|
|Post-grad. 134 / 22%||47%||47%||7%|
|Democrat n = 142 / 29% of voters||91%||6%||3%|
|Republican 187 / 39%||11%||86%||4%|
|Independent 135 / 26%||56%||36%||8%|
|Another party 19 / 4%||31%||32%||37%|
|Democratic n = 180 / 36% of voters||87%||9%||4%|
|Republican 194 / 40%||ten%||86%||4%|
|Other 122 / 25%||48%||35%||17%|
Intention to vote
|Already voted n = 83 / 18% of voters||46%||51%||3%|
|Almost certain 281 / 57%||49%||45%||6%|
|Very probable 94 / 20%||43%||49%||8%|
|Rather likely 14 / 2%||45%||26%||29%|
|Probably not 11 / 1%||37%||33%||30%|
|Not at all likely ten / 1%||26%||37%||37%|