66 datasets found
  1. U.S. leading social media platform users 2024, by political position

    • statista.com
    Updated Jun 25, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). U.S. leading social media platform users 2024, by political position [Dataset]. https://www.statista.com/statistics/1337623/us-distribution-leading-social-media-platforms-by-political-position/
    Explore at:
    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2024 - Dec 2024
    Area covered
    United States
    Description

    According to a 2024 survey, ** percent of social media users in the United States used Facebook, and ** percent of left-leaning users used the social network. Overall, ** percent of social media users who were politically left-leaning used Pinterest, compared to ** percent of right-leaning users.

  2. Political ideology of Spaniards 2023

    • statista.com
    Updated Jan 22, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Political ideology of Spaniards 2023 [Dataset]. https://www.statista.com/statistics/1059209/political-ideology-of-spaniards/
    Explore at:
    Dataset updated
    Jan 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Spain
    Description

    Around 46 percent of the Spanish population identified politically with the country’s left-wing, according to the latest studies conducted in 2023. In contrast, approximately 25 percent considered themselves to be right-wing supporters, with 17 percent of them identifying as right-wing voters. Around 17 percent of Spaniards, however, positioned their political orientation in the center. Spain: dissatisfied with its political leaders The political situation in Spain has been somewhat unstable in the past few years, with Spaniards last casting their ballots in July 2023. In that election, the Spanish socialist party (PSOE) required the support of the left-wing and the independent parties to form a coalition government. Given these circumstances, it comes as no surprise that the trust of Spaniards in the country’s politicians has been shaken, with the latest surveys ranking politicians as the least reliable profession in Spain. This lack of trust extends to the current Prime Minister, Pedro Sánchez, as the most recent study indicated that nearly 46 percent of the Spanish population had no confidence in the head of government. Spain’s mistrust in the political institutions In 2023, the Spaniards declared finding local and regional politicians as more trustworthy than the parliament and the national government. Political parties received even less trust by the citizens, scoring 4.1 points out of a possible ten. This lack of confidence by the countrymen in political institutions may be justified by the concern with political corruption. In a 2024 survey, almost 30 percent of the Spanish population declared that this form of corruption was one of the three most worrying topics that the Iberian country faces.

  3. d

    Replication Data for: Polarization, Demographic Change, and White Flight...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zingher, Joshua (2023). Replication Data for: Polarization, Demographic Change, and White Flight from the Democratic Party [Dataset]. http://doi.org/10.7910/DVN/WDRHTS
    Explore at:
    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Zingher, Joshua
    Description

    Whites have become decreasingly likely to support the Democratic Party. I show this shift is being driven by two mechanisms. The first mechanism is the process of ideological sorting. The Democratic Party has lost support among conservative whites because the relationships between partisanship, voting behavior, and policy orientations have strengthened. The second mechanism relates to demographic changes. The growth of liberal minority populations has shifted the median position on economic issues to the left and away from the median white citizen’s position. The parties have responded to these changes by shifting their positions and whites have become less likely to support the Democratic Party as a result. I test these explanations using 40 years of ANES and DW-NOMINATE data. I find that whites have become 7.7-points more likely vote for the Republican Party and mean white partisanship has shifted .25 points in favor of the Republicans as a combined result of both mechanisms.

  4. U.S. party identification 2023, by age

    • statista.com
    • ai-chatbox.pro
    Updated Aug 7, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). U.S. party identification 2023, by age [Dataset]. https://www.statista.com/statistics/319068/party-identification-in-the-united-states-by-generation/
    Explore at:
    Dataset updated
    Aug 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 7, 2023 - Aug 27, 2023
    Area covered
    United States
    Description

    According to a 2023 survey, Americans between 18 and 29 years of age were more likely to identify with the Democratic Party than any other surveyed age group. While 39 percent identified as Democrats, only 14 percent identified ad Republicans. However, those 50 and older identified more with the Republican Party.

  5. H

    Replication Data for: Does Diversity-Driven Hiring Decrease Ideological...

    • dataverse.harvard.edu
    Updated Dec 9, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Christopher C. Hull (2020). Replication Data for: Does Diversity-Driven Hiring Decrease Ideological Diversity? [Dataset]. http://doi.org/10.7910/DVN/U1Z981
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 9, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Christopher C. Hull
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    1950 - 2020
    Description

    Abstract This study presents a meta-analysis of research into academics’ ideological self-identification from 1955-2018, focusing on political scientists, social scientists, historians, and social/political psychologists. It suggests that from 1955 to about 1989, fewer than 50% of these academics self-identified as liberal, Left, or Democratic, but thereafter that percentage increased rapidly to as high as 89.3%. The study further explores whether diversity-driven hiring helps explain this decrease in ideological diversity. First, it examines whether more political scientists from demographics that lean left may in part account for the change. Second, it presents evidence the political science profession may signal a preferred ideology by explicitly favoring candidates who embrace racial, ethnic and sex diversity in particular, rather than e.g. ideological, partisan, methodological, socio-economic, class, religious, age, or geographic diversity. Third, the paper asks whether those hiring political scientists on average set diversity above other values, presenting new data drawn from the American Political Science Association (APSA) eJobs database. These data suggest hiring of political science educators now focuses more on a particular conception of diversity and the ideology underlying it than on liberal values or institutional expertise. Specifically, as of February 2019, an APSA job listing was about 100 times as likely to mention Race or Gender than Speech or the Judiciary, and about 200 times as likely to mention Diversity as Liberty. Together these results suggest that the political predilections of those emphasizing one conception of diversity over others may be driving political science education left, thereby decreasing ideological diversity. Dataset Contents Appendix A: Fig. 1. % of All Faculty (A), Social Scientists (S), Political Scientists (P), Psychologists and Social Psychologists (Y), or Historians (H) self-identifying as liberal, left (including far left), or Democratic, 1955-2018 Appendix B: Fig. 2. % of APSA eJobs listings with term, February 16, 2019

  6. z

    Data from: Right-wing Authoritarianism, Left-wing Authoritarianism, and...

    • zenodo.org
    • datadryad.org
    csv
    Updated Jun 3, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Joseph H. Manson; Joseph H. Manson (2022). Right-wing Authoritarianism, Left-wing Authoritarianism, and pandemic-mitigation authoritarianism [Dataset]. http://doi.org/10.5068/d1rh4k
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 3, 2022
    Dataset provided by
    Zenodo
    Authors
    Joseph H. Manson; Joseph H. Manson
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    On April 22, 2020, 549 U.S. resident users of Prolific.co completed (1) the Authoritarianism-Conservatism-Traditionalism Scales (Duckitt, Bizumic, Kruauss, and Heled, 2010), (2) the 22-item short form of the Left-Wing Authoritarianism Index (Costello and Lilienfeld, 2019), (3) their level of endorsement of 19 policies that could possibly mitigate the impact of the COVID-19 pandemic, and (4) a set of demographic questions (age, gender, ethnicity, pre-pandemic household income, and highest educational attainment). They were also asked to provide their current ZIP code, because county-level COVID-19 prevalence was a control variable in the analyses. To protect participants' confidentiality, neither ZIP code nor county name is included in this data set. Instead, the data set includes the relevant control variable (COVID-19 cases per 100,000 county residents on Apr. 22, 2020). Also provided are the STATA commands used in the analyses.

  7. Left-Right Survey, 1967-1968

    • icpsr.umich.edu
    ascii
    Updated Feb 16, 1992
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Laponce, Jean A. (1992). Left-Right Survey, 1967-1968 [Dataset]. http://doi.org/10.3886/ICPSR07094.v1
    Explore at:
    asciiAvailable download formats
    Dataset updated
    Feb 16, 1992
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Laponce, Jean A.
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/7094/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/7094/terms

    Time period covered
    1967 - 1968
    Area covered
    France, Global, United States, Canada
    Description

    For this study, conducted in 1967-1968, university students in French- and English-speaking areas of Canada, in the United States, and in France were surveyed. Data were obtained from 235 respondents in English-speaking Canada (interviewed at the University of British Columbia), 199 French Canadians (interviewed at the University of Montreal and Laval University), 166 Americans (interviewed at the University of Washington in Seattle), and 166 French students from universities in Paris, Strasbourg, and Lyon. Students were asked to evaluate a variety of terms using a revised form of Osgood's semantic differential. The respondents were thus requested to locate themselves, as well as names of politicians, states, and selected political concepts, in a left-to-right space presented visually as extending from the left side to the right side of the questionnaire page. Also included in the survey instrument were questions on party preference and on specific political, social, economic, and religious problems. Demographic variables cover sex, age, religion, and father's occupation.

  8. Unemployed population who have previously worked and left last job more than...

    • datos.gob.es
    Updated Mar 27, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Instituto Nacional de Estadística (2025). Unemployed population who have previously worked and left last job more than 1 year ago by economic sector of last job, sex and age group. Percentages with regards the total in each economic sector. EPA (API identifier: 65858) [Dataset]. https://datos.gob.es/en/catalogo/ea0010587-parados-que-han-trabajado-anteriormente-y-han-dejado-su-ultimo-empleo-hace-mas-de-1-ano-por-sector-economico-sexo-y-grupo-de-edad-porcentajes-respecto-del-total-de-cada-sector-economico-epa-identificador-api-65858
    Explore at:
    Dataset updated
    Mar 27, 2025
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Description

    Table of INEBase Unemployed population who have previously worked and left last job more than 1 year ago by economic sector of last job, sex and age group. Percentages with regards the total in each economic sector. Annual. National. Economically Active Population Survey

  9. f

    Left Preference for Sport Tasks Does Not Necessarily Indicate...

    • plos.figshare.com
    pdf
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Florian Loffing; Florian Sölter; Norbert Hagemann (2023). Left Preference for Sport Tasks Does Not Necessarily Indicate Left-Handedness: Sport-Specific Lateral Preferences, Relationship with Handedness and Implications for Laterality Research in Behavioural Sciences [Dataset]. http://doi.org/10.1371/journal.pone.0105800
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Florian Loffing; Florian Sölter; Norbert Hagemann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In the elite domain of interactive sports, athletes who demonstrate a left preference (e.g., holding a weapon with the left hand in fencing or boxing in a ‘southpaw’ stance) seem overrepresented. Such excess indicates a performance advantage and was also interpreted as evidence in favour of frequency-dependent selection mechanisms to explain the maintenance of left-handedness in humans. To test for an overrepresentation, the incidence of athletes' lateral preferences is typically compared with an expected ratio of left- to right-handedness in the normal population. However, the normal population reference values did not always relate to the sport-specific tasks of interest, which may limit the validity of reports of an excess of ‘left-oriented’ athletes. Here we sought to determine lateral preferences for various sport-specific tasks (e.g., baseball batting, boxing) in the normal population and to examine the relationship between these preferences and handedness. To this end, we asked 903 participants to indicate their lateral preferences for sport-specific and common tasks using a paper-based questionnaire. Lateral preferences varied considerably across the different sport tasks and we found high variation in the relationship between those preferences and handedness. In contrast to unimanual tasks (e.g., fencing or throwing), for bimanually controlled actions such as baseball batting, shooting in ice hockey or boxing the incidence of left preferences was considerably higher than expected from the proportion of left-handedness in the normal population and the relationship with handedness was relatively low. We conclude that (i) task-specific reference values are mandatory for reliably testing for an excess of athletes with a left preference, (ii) the term ‘handedness’ should be more cautiously used within the context of sport-related laterality research and (iii) observation of lateral preferences in sports may be of limited suitability for the verification of evolutionary theories of handedness.

  10. g

    Einstellung zur Volkszählung (Panelstudie)

    • search.gesis.org
    • da-ra.de
    Updated Apr 13, 2010
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Gräf, Lorenz; Kühnel, Steffen M.; Scheuch, Erwin K. (2010). Einstellung zur Volkszählung (Panelstudie) [Dataset]. http://doi.org/10.4232/1.1592
    Explore at:
    application/x-stata-dta(1911986), application/x-spss-por(3636208), application/x-spss-sav(1966972)Available download formats
    Dataset updated
    Apr 13, 2010
    Dataset provided by
    GESIS Data Archive
    GESIS search
    Authors
    Gräf, Lorenz; Kühnel, Steffen M.; Scheuch, Erwin K.
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    Variables measured
    IDNR -, LFDNR -, P1001 -, P1002 -, P1003 -, P1004 -, P1005 -, P1006 -, P1007 -, P1008 -, and 647 more
    Description

    Attitude of the Federal German population and census critics to the census on 31. May 1987.

    Summary of three data sets archived and described under ZA Study Nos. 1588 to 1590.

    Topics: 1. From the first wave of 1987: political interest; satisfaction with democracy in the Federal Republic; feeling of political effectiveness and degree of representation by politicians and parties; orientation of government policies on special interests or public welfare; attitude to the census; intent of members of household and respondent to participate; willingness to participate after notice of threat of fine; filling out the survey form oneself or by another person in household; conversations about the census in social surroundings and time of last conversation; attitude to the census in circle of friends and acquaintances as well as their willingness to participate; importance of political attitudes in social surroundings and visibility of one´s own views; knowledge about contents of the census survey (scale); assumed difficulty in filling out survey form; preference for filling out the form in the presence of the canvasser or alone; misgivings about canvasser in residence; difficulties in carrying out official matters; frequency of contact and ability to establish contacts; trust in institutions and organizations; self-assessment on a left-right continuum; assumed position of the majority of the population on a left-right continuum; postmaterialism; sympathy scale for political parties; frequency of use of television news broadcasts as well as the local part and political part of a daily newspaper; time of last noticed media reports about the census and content tendency of these programs; assumed attitude of the population to the census; living together with a partner and his attitude to the census; assumed participation of partner in the census; response or boycott conduct in the census survey; attitude to government statistics; attitude to punishment of census boycotters and preferred governmental behavior regarding refusal; personal fears regarding misuse of personal census data; trust in observance of data protection; sympathies regarding social movements as well as personal membership; party preference; perceived fears and their causes; attitude to technology; attitude to computers and scientific innovations; attitude to government dealing with data; assessment of census refusers as system opponents; attitude to storage of personal data; importance of data protection and trust in observance of the data protection regulation; judgement on quality of data protection; earlier participation in a survey and type of survey; attitude to selected infringements and crimes as well as other illegal actions (scale); religiousness; union membership; self-assessment of social class; possession of a telephone; willingness to participate in a re-interview.

    The following additional questions were posed to persons with strong or very strong political interest: demographic information on circle of close friends (ego-centered network); agreement with respondent regarding party preference and attitude to the census; willingness of friends to participate in the census; familiarity of friends among each other; personal willingness to participate in selected political forms of protest (scale); personal fears regarding misuse of personal data by selected institutions and public offices.

    Demography: month of birth; year of birth; sex; marital status; number of children; ages of children (classified); frequency of church attendance; school education; vocational training; occupation; occupational position; employment; monthly net income of respondent and household altogether; number of persons contributing to household income; size of household; position of respondent in household; characteristics of head of household; number of persons eligible to vote in household; persons in household who do not have German citizenship; self-assessment of social class; union membership of respondent and other members of household; possession of a telephone.

    Interviewer rating: presence of third persons during interview and person desiring this presence; intervention of others in interview and person introducing the intervention; attitude to the census of persons additionally present during interview; presence of further persons in other rooms; willingness to cooperate and reliability of respondent.

    Also encoded was: length of interview; date of interview; ident...

  11. g

    Auswirkungen des demographischen Wandels auf politische Einstellungen und...

    • search.gesis.org
    • pollux-fid.de
    • +1more
    Updated Jul 31, 2015
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Rattinger, Hans; Konzelmann, Laura (2015). Auswirkungen des demographischen Wandels auf politische Einstellungen und politisches Verhalten in Deutschland [Dataset]. http://doi.org/10.4232/1.12311
    Explore at:
    application/x-spss-sav(1091549), application/x-stata-dta(1001855), application/x-spss-por(1745206)Available download formats
    Dataset updated
    Jul 31, 2015
    Dataset provided by
    GESIS Data Archive
    GESIS search
    Authors
    Rattinger, Hans; Konzelmann, Laura
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    Time period covered
    Jan 19, 2011 - Sep 22, 2011
    Area covered
    Germany
    Description

    Political attitudes and behaviors with regard to demographic change.

    Topics: Assessment of the national economic situation (retrospective, current, prospective); concern regarding demographic change; anticipated problems caused by an aging society; perceived age limit of older and younger people; knowledge test: Proportion of the country´s population over 65; perception of commonalities in own age group; perceived frequency of media reports on generational conflicts; political interest; assessment of one´s own economic situation (retrospective, current, prospective); voter turnout (Sunday question); party preference (voters and non-voters); perceptions of social conflicts between selected social groups (people with and without children, politically left and right, young and old, poor and rich, employed and retired, Germans and foreigners, East Germans and West Germans); most important political goals (post-materialism, Inglehart indicators); opinion on selected statements about old and young (frequent abuse of social benefits in Germany, assessment of representation of younger people´s interests in politics, assessment of representation of older people in political positions, older people should organize their own party, older people should support younger people and younger people should support older people); perceived strength of general intergenerational support; financial support of a family member of another generation resp. frequency of self-received financial support (intergenerational transfers); frequency of support from a person in everyday life who belongs to another generation or frequency of self-received support; satisfaction with democracy; political trust (Bundestag, politicians, Federal Constitutional Court, federal government, media); opinion on selected statements about young and old (importance of contact with significantly younger persons, evaluation of the representation of the interests of older persons in politics, older persons live at the expense of the following generations, older persons have built up what the younger persons live on today, importance of contact with significantly older persons, evaluation of the representation of younger persons in political positions; political efficacy; electoral norm (voter turnout as a civic duty); sympathy scalometer of political parties (CDU/CSU, SPD, FDP, Greens, Die Linke); satisfaction with selected policy areas (reduction of unemployment, health, education, financial security for the elderly, family, care in old age); preferred level of government spending in the aforementioned areas; preferred government responsibility in the aforementioned areas; most competent party to solve the problems in the aforementioned areas (problem-solving competence); salience of the aforementioned policy areas; self-ranking on a left-right continuum; assessment of the representation of older people´s interests by political parties (CDU/CSU, SPD, FDP, Greens, Die Linke); assessment of the representation of younger people´s interests by political parties (CDU/CSU, SPD, FDP, Greens, Die Linke); recall Bundestag elections 2013 (voter turnout, voting decision); expected occurrence of various future scenarios (conflicts between older and younger people, refusal of younger people to pay for the pensions of older people, older people more likely to assert their political interests than younger people, increasing old-age poverty, refusal of younger people to pay for the medical care of older people, Germany will no longer be able to afford current pension levels, Elderly will no longer receive all available medical benefits); reliance most likely on state, family or self for own retirement; knowledge test: Year of phased introduction of retirement at 67; civic engagement; hours per week of volunteering; perception of social justice; general life satisfaction; party affiliation and strength of party identification; concerns regarding own retirement security (financial/medical) or feared unemployment; religious affiliation; religiosity; salience of selected life domains (family and friends, health, leisure, politics, income, education, work, and occupation); self-assessment of class affiliation; residence description.

    Demography: age (grouped) and year of birth; sex; household size; number of persons under 18 in household; household composition (one, two, or three generations); number of children and grandchildren; regrets about own childlessness; partnership; living with...

  12. S

    Demographics by Census Block

    • data.sanjoseca.gov
    • gisdata-csj.opendata.arcgis.com
    Updated Apr 28, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Enterprise GIS (2025). Demographics by Census Block [Dataset]. https://data.sanjoseca.gov/dataset/demographics-by-census-block
    Explore at:
    arcgis geoservices rest api, zip, geojson, html, csv, kmlAvailable download formats
    Dataset updated
    Apr 28, 2025
    Dataset provided by
    City of San José
    Authors
    Enterprise GIS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This demographics data package is part of a 3 layer set for Tracts, Block Groups, and Blocks across all of Santa Clara County. A field is present in each to allow filtering for the geometries that are only in The City of San Jose. Each of the data layers contains the most commonly requested demographic fields from the U.S. Census/American Community Survey. Please note these fields are not exactly the same as found in the census tables, the goal was to standardize the field names so that they will always remain the same regardless of if the census changes the field names or range values. San Jose GIS Enterprise staff will update these fields once a year. Please check the field that states the last time it was updated and from what source. Please also note that Tracts has the most data fields, Block Groups slightly less, and Blocks has very few. The finer scaled geometries have less data available from the U.S. Census, so those fields were dropped.

    Source: Census 2020

    Data is updated every ten years from decennial census.

  13. w

    Ages

    • whitecity.ca
    • rmofwestinterlake.com
    • +68more
    Updated May 2, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Ages [Dataset]. https://whitecity.ca/p/statistics-community-profile
    Explore at:
    Dataset updated
    May 2, 2025
    Description

    Ages chart illustrates the age and gender trends across all age and gender groupings. A chart where the the covered area is primarily on the right describes a very young population while a chart where the the covered area is primarily on the left illustrates an aging population.

  14. S

    Demographics by Census Block Group

    • data.sanjoseca.gov
    • gisdata-csj.opendata.arcgis.com
    Updated Apr 28, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Enterprise GIS (2025). Demographics by Census Block Group [Dataset]. https://data.sanjoseca.gov/dataset/demographics-by-census-block-group
    Explore at:
    kml, arcgis geoservices rest api, html, zip, geojson, csvAvailable download formats
    Dataset updated
    Apr 28, 2025
    Dataset provided by
    City of San José
    Authors
    Enterprise GIS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This demographics data package is part of a 3 layer set for Tracts, Block Groups, and Blocks across all of Santa Clara County. A field is present in each to allow filtering for the geometries that are only in The City of San Jose. Each of the data layers contains the most commonly requested demographic fields from the U.S. Census/American Community Survey. Please note these fields are not exactly the same as found in the census tables, the goal was to standardize the field names so that they will always remain the same regardless of if the census changes the field names or range values. San Jose GIS Enterprise staff will update these fields once a year. Please check the field that states the last time it was updated and from what source. Please also note that Tracts has the most data fields, Block Groups slightly less, and Blocks has very few. The finer scaled geometries have less data available from the U.S. Census, so those fields were dropped.

    Source: American Community Survey (ACS) 2021 5-year estimates

    Data is updated annually.

  15. H

    Replication Data for: The Political Geography of the Gender Gap

    • dataverse.harvard.edu
    Updated Feb 16, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dawn Teele (2023). Replication Data for: The Political Geography of the Gender Gap [Dataset]. http://doi.org/10.7910/DVN/VZURJ6
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 16, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Dawn Teele
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This paper leverages fine grained municipal level data from Sweden, including turnout figures separated by sex, to examine the political geography of the gender gap. Prominent arguments about the ``traditional'' gender gap claim that early on, women turned out at low rates and voted for conservative parties. Instead, I argue that when parties have clear geographic strongholds, gender gaps depend on population demographics and the mobilization of men and women in a given election. Using the computational method of bounds to estimate women's vote choice, I find that women in cities and large municipalities were much more supportive of the left than women in the countryside after suffrage. At the national level, high turnout among women in more populous municipalities drove the majority of women to support the left. These findings demonstrate that the partisan gender gap is not only a feature of gender, but also produced by electoral geography.

  16. d

    Data from: The niche through time: Considering phenology and demographic...

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated Jun 20, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Damaris Zurell; Niklaus Zimmermann; Philipp Brun (2024). The niche through time: Considering phenology and demographic stages in plant distribution models [Dataset]. http://doi.org/10.5061/dryad.sn02v6xct
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Dryad Digital Repository
    Authors
    Damaris Zurell; Niklaus Zimmermann; Philipp Brun
    Description

    Species distribution models (SDMs) are widely used to infer species-environment relationships, predict spatial distributions, and characterise species’ environmental niches. While the importance of space and spatial scales is widely acknowledged in SDM applications, temporal components of the niche are rarely addressed. We discuss how phenology and demographic stages affect model inference in plant SDMs. Ignoring conspicuousness and timing of phenological stages may bias niche estimates through increased observer bias, while ignoring stand age may bias niche estimates through temporal mismatches with environmental variables, especially during times of rapid global warming. We present different methods to consider phenology and demographic stages in plant SDMs, including the selection of causal, spatiotemporally explicit predictors, and the calibration of stage-specific SDMs. Based on a case study with citizen science data, we illustrate how spatiotemporal SDMs provide deeper insights on..., We conducted a keyword-based search in the Web of Science to quantify how often temporal components related to phenology and demographic stages are explicitly considered in plant SDMs. A full list of keywords is provided in the Supporting Information Table S1. We used a nested set of keywords to identify all studies that mentioned SDMs (or common synonyms), were focused on plants, and were listing relevant keywords related to phenology or to demographic stages, respectively. The search was carried out on 5-Oct-2023 and was restricted to English-language journal articles in the period 1945-2022 (no studies using SDMs were published before that start year). Overall, we found more than 40,000 articles mentioning SDM and over 10,000 articles in our refined search for plant SDMs, with a strong increase in the number of articles over time. Among these, phenology (or related search terms) was mentioned in 970 articles and demographic stages (or related terms) in 1188 articles, each averaging c..., , # The niche through time: considering phenology and demographic stages in plant distribution models

    https://doi.org/10.5061/dryad.sn02v6xct

    Description of the data and file structure

    Columns from WoS (Web of Science) search – these are identical in both excel sheets

    These columns are the standard columns provided as WoS search output. If the entries contain "n/a", then no information was provided by WoS because those items are not applicable. For example, a journal article does not have any entries for book authors.

    ColumnExplanation
    Publication TypeType of publication: J .. Journal article
    AuthorsAuthors
    Book AuthorsBook Authors
    Book EditorsBook Editors ...
  17. d

    Public Health Official Departures

    • data.world
    csv, zip
    Updated Jun 7, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    The Associated Press (2022). Public Health Official Departures [Dataset]. https://data.world/associatedpress/public-health-official-departures
    Explore at:
    csv, zipAvailable download formats
    Dataset updated
    Jun 7, 2022
    Authors
    The Associated Press
    Description

    Changelog:

    Update September 20, 2021: Data and overview updated to reflect data used in the September 15 story Over Half of States Have Rolled Back Public Health Powers in Pandemic. It includes 303 state or local public health leaders who resigned, retired or were fired between April 1, 2020 and Sept. 12, 2021. Previous versions of this dataset reflected data used in the Dec. 2020 and April 2021 stories.

    Overview

    Across the U.S., state and local public health officials have found themselves at the center of a political storm as they combat the worst pandemic in a century. Amid a fractured federal response, the usually invisible army of workers charged with preventing the spread of infectious disease has become a public punching bag.

    In the midst of the coronavirus pandemic, at least 303 state or local public health leaders in 41 states have resigned, retired or been fired since April 1, 2020, according to an ongoing investigation by The Associated Press and KHN.

    According to experts, that is the largest exodus of public health leaders in American history.

    Many left due to political blowback or pandemic pressure, as they became the target of groups that have coalesced around a common goal — fighting and even threatening officials over mask orders and well-established public health activities like quarantines and contact tracing. Some left to take higher profile positions, or due to health concerns. Others were fired for poor performance. Dozens retired. An untold number of lower level staffers have also left.

    The result is a further erosion of the nation’s already fragile public health infrastructure, which KHN and the AP documented beginning in 2020 in the Underfunded and Under Threat project.

    Findings

    The AP and KHN found that:

    • One in five Americans live in a community that has lost its local public health department leader during the pandemic
    • Top public health officials in 28 states have left state-level departments ## Using this data To filter for data specific to your state, use this query

    To get total numbers of exits by state, broken down by state and local departments, use this query

    Methodology

    KHN and AP counted how many state and local public health leaders have left their jobs between April 1, 2020 and Sept. 12, 2021.

    The government tasks public health workers with improving the health of the general population, through their work to encourage healthy living and prevent infectious disease. To that end, public health officials do everything from inspecting water and food safety to testing the nation’s babies for metabolic diseases and contact tracing cases of syphilis.

    Many parts of the country have a health officer and a health director/administrator by statute. The analysis counted both of those positions if they existed. For state-level departments, the count tracks people in the top and second-highest-ranking job.

    The analysis includes exits of top department officials regardless of reason, because no matter the reason, each left a vacancy at the top of a health agency during the pandemic. Reasons for departures include political pressure, health concerns and poor performance. Others left to take higher profile positions or to retire. Some departments had multiple top officials exit over the course of the pandemic; each is included in the analysis.

    Reporters compiled the exit list by reaching out to public health associations and experts in every state and interviewing hundreds of public health employees. They also received information from the National Association of City and County Health Officials, and combed news reports and records.

    Public health departments can be found at multiple levels of government. Each state has a department that handles these tasks, but most states also have local departments that either operate under local or state control. The population served by each local health department is calculated using the U.S. Census Bureau 2019 Population Estimates based on each department’s jurisdiction.

    KHN and the AP have worked since the spring on a series of stories documenting the funding, staffing and problems around public health. A previous data distribution detailed a decade's worth of cuts to state and local spending and staffing on public health. That data can be found here.

    Attribution

    Findings and the data should be cited as: "According to a KHN and Associated Press report."

    Is Data Missing?

    If you know of a public health official in your state or area who has left that position between April 1, 2020 and Sept. 12, 2021 and isn't currently in our dataset, please contact authors Anna Maria Barry-Jester annab@kff.org, Hannah Recht hrecht@kff.org, Michelle Smith mrsmith@ap.org and Lauren Weber laurenw@kff.org.

  18. A

    ‘Inactive population who have worked previously and left their last job more...

    • analyst-2.ai
    Updated Jan 8, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Inactive population who have worked previously and left their last job more than 1 years ago by economic sector of last job, sex and age group. Percentages with regards the total in each age group. EPA (API identifier: 5293)’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-europa-eu-inactive-population-who-have-worked-previously-and-left-their-last-job-more-than-1-years-ago-by-economic-sector-of-last-job-sex-and-age-group-percentages-with-regards-the-total-in-each-age-group-epa-api-identifier-5293-67ab/latest
    Explore at:
    Dataset updated
    Jan 8, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Inactive population who have worked previously and left their last job more than 1 years ago by economic sector of last job, sex and age group. Percentages with regards the total in each age group. EPA (API identifier: 5293)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-347-5293 on 08 January 2022.

    --- Dataset description provided by original source is as follows ---

    Table of INEBase Inactive population who have worked previously and left their last job more than 1 years ago by economic sector of last job, sex and age group. Percentages with regards the total in each age group. Annual. National. Economically Active Population Survey

    --- Original source retains full ownership of the source dataset ---

  19. V

    ACS Demographics

    • data.virginia.gov
    • hub.arcgis.com
    Updated Nov 12, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Arlington GIS Portal (2024). ACS Demographics [Dataset]. https://data.virginia.gov/dataset/acs-demographics
    Explore at:
    arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Nov 12, 2024
    Dataset provided by
    Arlington County, VA - GIS Mapping Center
    Authors
    Arlington GIS Portal
    Description

    Public demographics data for Arlington County, VA using census tract geometry. Includes fields noting if the statistic is reliable. Data pulled from US Census Bureau, American Community Survey 5-Year Estimates. Table layer has no associated geometry and can be joined to the corresponding tract year.

  20. A

    Public School Characteristics - Current

    • data.amerigeoss.org
    Updated Jul 5, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    United States (2022). Public School Characteristics - Current [Dataset]. https://data.amerigeoss.org/dataset/public-school-characteristics-current
    Explore at:
    html, geojson, kml, zip, arcgis geoservices rest api, csvAvailable download formats
    Dataset updated
    Jul 5, 2022
    Dataset provided by
    United States
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    The National Center for Education Statistics' (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated point locations (latitude and longitude) for public elementary and secondary schools included in the NCES Common Core of Data (CCD). The NCES EDGE program collaborates with the U.S. Census Bureau's Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to develop point locations for schools reported in the annual CCD directory file. The CCD program annually collects administrative and fiscal data about all public schools, school districts, and state education agencies in the United States. The data are supplied by state education agency officials and include basic directory and contact information for schools and school districts, as well as characteristics about student demographics, number of teachers, school grade span, and various other administrative conditions. CCD school and agency point locations are derived from reported information about the physical location of schools and agency administrative offices. The point locations in this data layer represent the most current CCD collection available. Check the SURVYEAR attribute in the data table to determine file vintage. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations. For more information about these CCD attributes, as well as additional attributes not included, see: https://nces.ed.gov/ccd/files.asp.

    Notes:

    -1 or M

    Indicates that the data are missing.

    -2 or N

    Indicates that the data are not applicable.

    -9

    Indicates that the data do not meet NCES data quality standards.

    Previous collections are available for the following years:

    All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). U.S. leading social media platform users 2024, by political position [Dataset]. https://www.statista.com/statistics/1337623/us-distribution-leading-social-media-platforms-by-political-position/
Organization logo

U.S. leading social media platform users 2024, by political position

Explore at:
Dataset updated
Jun 25, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Jan 2024 - Dec 2024
Area covered
United States
Description

According to a 2024 survey, ** percent of social media users in the United States used Facebook, and ** percent of left-leaning users used the social network. Overall, ** percent of social media users who were politically left-leaning used Pinterest, compared to ** percent of right-leaning users.

Search
Clear search
Close search
Google apps
Main menu