Data documentation

Field definitions and methodology for State Navigate data downloads. Questions? Contact mary@statenavigate.org.

• districtDistrict number
• TotalTotal district population*
• HouseholdsNumber of households in the district*
• NH_WhiteNumber of nonhispanic white residents*
• NH_BlackNumber of nonhispanic black residents*
• NH_AIANNumber of nonhispanic American Indian or Alaska native residents*
• NH_AsianNumber of nonhispanic Asian residents*
• NH_NHPINumber of nonhispanic Pacific Islander residents*
• NH_OthNumber of nonhispanic residents that identify as members of a single race other than white, black, American Indian, Alaska native, Asian, or Pacific Islander*
• NH_MultiNumber of nonhispanic residents that identify as members of multiple races*
• HispanicNumber of Hispanic residents*
• PCT_NH_WhitePercent of district residents that identify as nonhispanic white*
• PCT_NH_BlackPercent of district residents that identify as nonhispanic black*
• PCT_NH_AIANPercent of district residents that identify as nonhispanic American Indian or Alaska native*
• PCT_NH_AsianPercent of district residents that identify as nonhispanic Asian*
• PCT_NH_NHPIPercent of district residents that identify as nonhispanic Pacific Islander*
• PCT_NH_OthPercent of district residents that are nonhispanic and identify as members of a single race other than white, black, American Indian, Alaska native, Asian, or Pacific Islander*
• PCT_NH_MultiPercent of district residents that are nonhispanic and identify as members of multiple races*
• pres_2024Margin of victory in the 2024 presidential race within the district boundaries. Positive numbers indicate that Donald Trump won the district; negative numbers indicate that Kamala Harris won the district.
• no_hs_degreePercent of district residents who do not have a high school degree
• hs_degreePercent of district residents whose highest educational attainment is a high school degree
• college_bachelorPercent of district residents whose highest educational attainment is a bachelor’s degree
• college_graduate_plusPercent of district residents whose highest educational attainment is beyond a bachelor’s degree
• white_no_collegePercent of white district residents who do not have a bachelor’s degree
• white_collegePercent of white district residents who have a bachelor’s degree
• median_incomeEstimate of the individual median earnings for residents aged 25+ in the district, calculated as a weighted average of the median earnings of each census tract that intersects with the district, weighted based upon the population of the tract included in the districtborn_in_state: Percent of district residents born in the state
• natural_born_outside_statePercent of district residents that are natural born American citizens and were born in a different state
• naturalized_citizenPercent of district residents that are naturalized American citizens
• non_us_citizenPercent of district residents that are not American citizens
• PCT Under 18Percent of district residents under the age of 18*
• PCT 18 to 24Percent of district residents between the ages of 18 and 24*
• PCT 25 to 34Percent of district residents between the ages of 25 and 34*
• PCT 35 to 44Percent of district residents between the ages of 35 and 44*
• PCT 45 to 54Percent of district residents between the ages of 45 and 54*
• PCT 55 to 64Percent of district residents between the ages of 55 and 64*
• PCT 65 and OverPercent of district residents over the age of 64*

• candidateFull name of candidate in this election.
• election_fullIdentifier for the election. Note that elections with “state_leg” as part of their identification refer to the chamber for which the data files belong; for example, in the files referring to the State Senate, these indicate State Senate results.
• partyParty of candidate in this election.
• incumbentThis column is currently not in use.
• election_idShortened identifier for the election.
• districtDistrict identifier, where relevant.
• votesTotal votes earned by the candidate in the corresponding geography.
• vote_pctPercent of votes earned by the candidate in the corresponding geography.

The County Data files carry election results by county for each state. Note that for legislative elections, the results indicated are the results for whatever portion of the relevant district lies within the relevant county boundaries. In the case that multiple districts intersect the same county, the total voteshare is aggregated by party, and the candidate will appear as “DEM candidate” to indicate that multiple candidates are included. This file carries the following additional columns:

• countyName of the county for which the results are calculated.

The District Data files carry election results within the relevant district boundaries.

The Topline Data files carry the overall election results for each of the relevant races.

• idInternal StateNavigate identifier for the campaign being run. Note that multiple rows may carry the same id, if they represent the same candidate appearing on multiple ballots seeking the same seat.
• candidate_idInternal StateNavigate identifier for the candidate running for office. Note that this value remains constant across election cycles if the same candidate runs for office more than once.
• partyFull name of the candidate’s party
• party_codeStandard abbreviation for the candidate’s party
• incumbentBoolean for whether the candidate is an incumbent. Blanks indicate that data has not yet been collected.
• candidate_nameFull name of the candidate
• candidate_last_nameLast name of the candidate
• finance_report_startStart date of the campaign finance filing report that includes the date of the relevant election. If such a report is not available, the most recent report prior to the date of the election will be substituted here.
• finance_report_endEnd date of the campaign finance filing report that includes the date of the relevant election. If such a report is not available, the most recent report prior to the date of the election will be substituted here.
• cf_raisedTotal raised over the entirety of the campaign, as of the relevant filing report.
• cf_spentTotal spent over the entirety of the campaign, as of the relevant filing report.
• cf_cash_on_handTotal cash on hand, as of the relevant filing report.
• cf_loansOutstanding loans, as of the relevant filing report.
• cycleCampaign cycle of the candidate’s election.
• specialBoolean indicating whether the election is a special election. Blanks should be interpreted as FALSE.
• stageStage of the election for this row.
• election_dateDate of the election for this row.
• chamberName of the chamber for the seat. In the case of statewide elections, this column holds the name of the office being sought (e.g., “Governor” or “Attorney General”).
• chamber_typeType of the chamber for the seat (upper, lower, or statewide)
• districtDistrict number (or other identifier) for the seat. In the case of statewide elections, this column will be blank.
• stateName of the state in which the seat is located.

• idInternal StateNavigate identifier for the donation.
• campaign_idInternal StateNavigate identifier for the campaign receiving the donation. Note that this column can be crossreferenced with the column “id” in the candidate downloads.
• candidate_nameFull name of the candidate.
• cycleCycle in which the donation was received.
• nameName of the donor.
• amountAmount of the donation.
• dateDate of the donation.
• purposePurpose of the donation, if indicated on filing reports.

• idInternal StateNavigate identifier for the expenditure.
• campaign_idInternal StateNavigate identifier for the campaign spending the money. Note that this column can be crossreferenced with the column “id” in the candidate downloads.
• candidate_nameFull name of the candidate.
• cycleCycle in which the donation was received.
• nameName of the payee.
• amountAmount of the expense.
• dateDate of the expense.
• purposePurpose of the expense, if indicated on filing reports.

• vote_event_idIdentifier for the vote
• correctYeaNumber of yea votes correctly predicted by W-NOMINATE
• wrongYeaNumber of votes predicted to be yea by W-NOMINATE, but were actually nay
• wrongNayNumber of votes predicted to be nay by W-NOMINATE, but were actually yea
• correctNayNumber of nay votes correctly predicted by W-NOMINATE
• GMPGeometric Mean Probability (the geometric mean for the likelihood functions of the underlying optimizations); a measure of goodness of fit
• PREProportional Reduction in Error; another measure of goodness of fit
• spread1DSpread of the w-nominate scores in the first dimension (horizontal axis)
• spread2DSpread of the w-nominate scores in the second dimension (vertical axis)
• midpoint1DMidpoint of the w-nominate scores in the first dimension
• midpoint2DMidpoint of the w-nominate scores in the second dimension
• totalYeaTotal number of yea votes
• totalNayTotal number of nay votes
• cv1First parameter of the cutting line (the line that separates ‘yeas’ from ‘nays’)
• cv2Second parameter of the cutting line
• angle1Angle of the normal vector (atan(cv1, cv2)*180/pi)
• angle1adjAngle adjusted to be non-negative
• cv1adjcv1 adjusted to be non-negative
• cv2adjcv2 adjusted to be non-negative
• angle2Angle of the normal vector using adjusted CVs
• angle2adjAngle of the normal vector plus 90 degrees
• bill_idIdentifier for the bill
• start_dateDate on which the vote began
• motion_textText of the motion on which the vote is being held.
• resultResult of the vote.
• session_identifierIdentifier for the session in which the vote is held.
• titleTitle of the underlying bill.
• identifierIdentifier for the underlying bill.
• abstractAbstract for the underlying bill.
• urlLink to the bill on the relevant state agency’s website.
• yesTotal voting yes.
• noTotal voting no.
• not votingTotal not voting on the motion.
• abstainTotal abstaining from the vote on the motion.
• otherTotal legislators in the relevant body whose vote cannot be classified as yes, no, not voting, or abstention.
• total_votesTotal votes on the motion.
• roll_call_idShortened identifier for the voting event event.

• vote_event_idIdentifier for the vote event considered. Note that this can be cross-referenced with the vote_event_id column in the W-NOMINATE Vote Data files.
• voter_idIdentifier for the legislator voting.
• yea_probProbability of the legislator voting in favor of the motion, as calculated by W-NOMINATE.
• vote_descThe legislator’s actual vote on the legislation.
• people_idShortened identifier for the legislator voting.
• roll_call_idShortened identifier for the vote event considered.

• voter_idIdentifier for the legislator.
• nameName of the legislator.
• partyCurrent party affiliation of the legislator.
• districtDistrict name/number for the legislator.
• correctYeaNumber of yea votes cast by this legislator correctly predicted by W-NOMINATE.
• wrongYeaNumber of votes predicted to be yea by W-NOMINATE, but were actually cast as nay.
• wrongNayNumber of votes predicted to be nay by W-NOMINATE, but were actually cast as yea.
• correctNayNumber of nay votes cast by this legislator correctly predicted by W-NOMINATE.
• GMPGeometric Mean Probability (the geometric mean for the likelihood functions of the underlying optimizations); a measure of goodness of fit
• PREProportional Reduction in Error; another measure of goodness of fit
• coord1DFirst dimension W-NOMINATE score for the legislator.
• coord2DSecond dimension W-NOMINATE score for the legislator.
• se1Dstandard error of the first dimension scores
• se2Dstandard error of the second dimension scores
• Corr.1correlation between the first and second dimension scores
• people_idShortened identifier for the legislator voting.

[1] For documentation on GMP and other technical parameters, see Poole KT, Rosenthal H (1983). “A Spatial Model for Legislative Roll Call Analysis.” Carnegie Mellon Working Paper, and Poole, K., Lewis, J. B., Lo, J., & Carroll, R. (2011). “Scaling Roll Call Votes with wnominate in R”. Journal of Statistical Software, 42(14), 1–21.