This Religion and State-Minorities (RASM) dataset is supplemental to the Religion and State Round 2 (RAS2) dataset. It codes the RAS religious discrimination variable using the minority as the unit of analysis (RAS2 uses a country as the unit of analysis and, is a general measure of all discrimination in the country). RASM codes religious discrimination by governments against all 566 minorities in 175 countries which make a minimum population cut off. Any religious minority which is at least 0.25 percent of the population or has a population of at least 500,000 (in countries with populations of 200 million or more) are included. The dataset also includes all Christian minorities in Muslim countries and all Muslim minorities in Christian countries for a total of 597 minorities. The data cover 1990 to 2008 with yearly codings.
These religious discrimination variables are designed to examine restrictions the government places on the practice of religion by minority religious groups. It is important to clarify two points. First, these variables focus on restrictions on minority religions. Restrictions that apply to all religions are not coded in this set of variables. This is because the act of restricting or regulating the religious practices of minorities is qualitatively different from restricting or regulating all religions. Second, this set of variables focuses only on restrictions of the practice of religion itself or on religious institutions and does not include other types of restrictions on religious minorities. The reasoning behind this is that there is much more likely to be a religious motivation for restrictions on the practice of religion than there is for political, economic, or cultural restrictions on a religious minority. These secular types of restrictions, while potentially motivated by religion, also can be due to other reasons. That political, economic, and cultural restrictions are often placed on ethnic minorities who share the same religion and the majority group in their state is proof of this.
This set of variables is essentially a list of specific types of religious restrictions which a government may place on some or all minority religions. These variables are identical to those included in the RAS2 dataset, save that one is not included because it focuses on foreign missionaries and this set of variables focuses on minorities living in the country. Each of the items in this category is coded on the following scale:
0. The activity is not restricted or the government does not engage in this practice.
1. The activity is restricted slightly or sporadically or the government engages in a mild form of this practice or a severe form sporadically.
2. The activity is significantly restricted or the government engages in this activity often and on a large scale.
A composite version combining the variables to create a measure of religious discrimination against minority religions which ranges from 0 to 48 also is included.
ARDA Note: This file was revised on October 6, 2017. At the PIs request, we removed the variable reporting on the minority's percentage of a country's population after finding inconsistencies with the reported values. For detailed data on religious demographics, see the "/data-archive?fid=RCSREG2" Target="_blank">Religious Characteristics of States Dataset Project.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Pass Christian by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Pass Christian. The dataset can be utilized to understand the population distribution of Pass Christian by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Pass Christian. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Pass Christian.
Key observations
Largest age group (population): Male # 5-9 years (316) | Female # 10-14 years (317). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Pass Christian Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Pass Christian population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Pass Christian. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 3,110 (52.34% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Pass Christian Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Pass Christian by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Pass Christian. The dataset can be utilized to understand the population distribution of Pass Christian by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Pass Christian. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Pass Christian.
Key observations
Largest age group (population): Male # 5-9 years (326) | Female # 10-14 years (349). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Pass Christian Population by Gender. You can refer the same here
Between Oct. 14, 2014, and May 21, 2015, Pew Research Center, with generous funding from The Pew Charitable Trusts and the Neubauer Family Foundation, completed 5,601 face-to-face interviews with non-institutionalized adults ages 18 and older living in Israel.
The survey sampling plan was based on six districts defined in the 2008 Israeli census. In addition, Jewish residents of West Bank (Judea and Samaria) were included.
The sample includes interviews with 3,789 respondents defined as Jews, 871 Muslims, 468 Christians and 439 Druze. An additional 34 respondents belong to other religions or are religiously unaffiliated. Five groups were oversampled as part of the survey design: Jews living in the West Bank, Haredim, Christian Arabs, Arabs living in East Jerusalem and Druze.
Interviews were conducted under the direction of Public Opinion and Marketing Research of Israel (PORI). Surveys were administered through face-to-face, paper and pencil interviews conducted at the respondent's place of residence. Sampling was conducted through a multi-stage stratified area probability sampling design based on national population data available through the Israel's Central Bureau of Statistics' 2008 census.
The questionnaire was designed by Pew Research Center staff in consultation with subject matter experts and advisers to the project. The questionnaire was translated into Hebrew, Russian and Arabic, independently verified by professional linguists conversant in regional dialects and pretested prior to fieldwork.
The questionnaire was divided into four sections. All respondents who took the survey in Russian or Hebrew were branched into the Jewish questionnaire (Questionnaire A). Arabic-speaking respondents were branched into the Muslim (Questionnaire B), Christian (Questionnaire C) or Druze questionnaire (D) based on their response to the religious identification question. For the full question wording and exact order of questions, please see the questionnaire.
Note that not all respondents who took the questionnaire in Hebrew or Russian are classified as Jews in this study. For further details on how respondents were classified as Jews, Muslims, Christians and Druze in the study, please see sidebar in the report titled "http://www.pewforum.org/2016/03/08/israels-religiously-divided-society/" Target="_blank">"How Religious are Defined".
Following fieldwork, survey performance was assessed by comparing the results for key demographic variables with population statistics available through the census. Data were weighted to account for different probabilities of selection among respondents. Where appropriate, data also were weighted through an iterative procedure to more closely align the samples with official population figures for gender, age and education. The reported margins of sampling error and the statistical tests of significance used in the analysis take into account the design effects due to weighting and sample design.
In addition to sampling error and other practical difficulties, one should bear in mind that question wording also can have an impact on the findings of opinion polls.
This study, designed and carried out by the "http://www.asarb.org/" Target="_blank">Association of Statisticians of American Religious Bodies (ASARB), compiled data on 372 religious bodies by county in the United States. Of these, the ASARB was able to gather data on congregations and adherents for 217 religious bodies and on congregations only for 155. Participating bodies included 354 Christian denominations, associations, or communions (including Latter-day Saints, Messianic Jews, and Unitarian/Universalist groups); counts of Jain, Shinto, Sikh, Tao, Zoroastrian, American Ethical Union, and National Spiritualist Association congregations, and counts of congregations and adherents from Baha'i, three Buddhist groupings, two Hindu groupings, four Jewish groupings, and Muslims. The 372 groups reported a total of 356,642 congregations with 161,224,088 adherents, comprising 48.6 percent of the total U.S. population of 331,449,281. Membership totals were estimated for some religious groups.
In January 2024, the ARDA added 21 religious tradition (RELTRAD) variables to this dataset. These variables start at variable #12 (TOTCNG_2020). Categories were assigned based on pages 88-94 in the original "https://www.usreligioncensus.org/index.php/node/1638" Target="_blank">2020 U.S. Religion Census Report.
Visit the "https://www.thearda.com/us-religion/sources-for-religious-congregations-membership-data" Target="_blank">frequently asked questions page for more information about the ARDA's religious congregation and membership data sources.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This data powers a dashboard presenting insights into the religious affiliations and Assisted Dying voting patterns of UK Members of Parliament (MPs). It can be found here:
👉 https://davidjeffery.shinyapps.io/mp-religion/.
Please cite all uses of the data.
This dashboard presents insights into the religious affiliations and Assisted Dying voting patterns of UK Members of Parliament. It combines publicly available data to support transparency and understanding of Parliament’s composition.
The data is compiled from publicly available parliamentary records and voting data. You can download it directly from the link in the header or view it in the Raw Data tab of the dashboard.
There are three steps to determining religion. An MP is classified as having a religion based on the following criteria:
If the MP is a member of a religiously based group, they are classified as a member of that religion.
If a member has publicly spoken about their religion, they are classified as a member of that religion.
Finally, the text an MP swore in on is used to help infer their religion.
These sources are used in order of priority. For example, Tim Farron is a member of Christians in Parliament and has spoken about his religious views. However, he did not take the oath on the Bible, but made a solemn affirmation on no text. Regardless, he is still classed as Christian.
What do those variable names mean?
Member ID – member_id – A unique numeric identifier for each MP provided by Parliament.
Name – display_as – The full display name of the MP.
Gender – gender – The MP’s gender.
Party – party – The full political party name.
Party (Simplified) – party_simple – A shortened or cleaned version of the party name.
Religion – mp_final_relig – The MP’s classified religion based on multiple criteria outlined above.
AD: 2nd Reading Vote – ass_suicide_2nd – The MP’s vote (Yes, No, Abstain) on the Assisted Dying Bill 2nd Reading.
AD: 3rd Reading Vote – ass_suicide_3rd – The MP’s vote (Yes, No, Abstain) on the Assisted Dying Bill 3rd Reading.
LGBT Status – lgbt – Whether the MP is publicly identified as LGBT (LGBT.MP).
Ethnic Minority – ethnic_mp – Whether the MP identifies as an ethnic minority.
Religious Group: Christian – relig_christian – MP belongs to a Christian group (1 = Yes).
Religious Group: Muslim – relig_muslim – MP belongs to a Muslim group (1 = Yes).
Religious Group: Jewish – relig_jewish – MP belongs to a Jewish group (1 = Yes).
Religious Group: Sikh – relig_sikh – MP belongs to a Sikh group (1 = Yes).
Oath Taken – mp_swear – Whether the MP took the Oath or made an Affirmation.
Oath Book – mp_swear_book – The specific religious text (e.g., Bible, Quran) used when swearing in.
Inferred Religion – mp_inferred_relig – The religion inferred from the swearing-in text.
Election Outcome – elected – Whether the MP was re-elected in the most recent election.
Majority – majority – The MP’s vote share margin.
Constituency Type – constituency_type – Type: Borough or County.
Claimant Rate – cen_claimant – % of constituents claiming unemployment benefits.
% White (Census) – cen_eth_white – Proportion of white ethnicity in the constituency.
% Christian – cen_rel_christian – Constituency Christian population from the Census.
% Buddhist – cen_rel_buddhist – Constituency Buddhist population.
% Hindu – cen_rel_hindu – Constituency Hindu population.
% Jewish – cen_rel_jewish – Constituency Jewish population.
% Muslim – cen_rel_muslim – Constituency Muslim population.
% Sikh – cen_rel_sikh – Constituency Sikh population.
% No Religion – cen_rel_no religion – Constituents identifying as non-religious.
% No Qualifications – cen_qual_none – Constituents with no formal qualifications.
% Graduates – cen_qual_grad – Constituents with degree-level education.
% Some Disability – cen_disab_some – Constituents reporting a form of disability.
Don’t worry, I’m not suggesting we bring back the Test Acts. The logic here is that more granular data is better.
When swearing in, there are versions of the Bible specific to Catholics — typically the New Jerusalem Bible or the Douay–Rheims Bible — whereas if someone just asks for “the Bible”, they are given the King James Version and could be from any Christian denomination.
It would be a shame to lose that detail, so I provide the option to break out Catholic MPs separately.
The Parliament website has a great guide:
👉 https://www.parliament.uk/about/how/elections-and-voting/swearingin/
This dashboard was created by Dr David Jeffery, University of Liverpool.
Follow me on Twitter/X or Bluesky.
I needed to know MPs’ religion, and the text MPs used to swear in seemed like a valid proxy. This information was held by Humanists UK and when I asked for it, they said no.
So I did what any time-starved academic would do: I collected the data myself, by hand, and decided to make it public.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Pass Christian Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Pass Christian, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Pass Christian.
Key observations
Among the Hispanic population in Pass Christian, regardless of the race, the largest group is of Other Hispanic or Latino origin, with a population of 223 (75.08% of the total Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Origin for Hispanic or Latino population include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Pass Christian Population by Race & Ethnicity. You can refer the same here
description: Roman Catholic Churches In Large Cities in Arkansas This dataset includes buildings where Roman Catholics gather for organized worship in cities with a population of 50,000 people or more. Roman Catholic Churches are Christian Churches that are subject to the papal authority in Rome. In addition to what are commonly thought of as Roman Catholic Churches, this data set also includes Newman (or Neumann) Centers and Chaldean Churches. Newman Centers are Roman Catholic Churches setup specifically to serve college or university populations. The Chaldean Church (also known as the Chaldean Church of Babylon) reunited with the Catholic Church in the 15th century. It originated in the Middle East. If a group of Roman Catholics gather for organized worship at a location that also serves another function, such as a school, these locations are included in this dataset if they otherwise meet the criteria for inclusion. Roman Catholic Shrines are included if they hold regularly scheduled mass. If a congregation celebrates mass at multiple locations, we have tried to include all such locations. This dataset excludes churches that are not subject to papal authority in Rome. Some churches may refer to themselves as "Catholic", and yet not be part of the "Roman" Catholic Church and these Churches are excluded from this dataset. Specifically Protestant Churches and their descendants which separated from the Roman Catholic Church beginning in 1517, Eastern Orthodox Churches (e.g. Russian, Greek) which separated from the Roman Catholic Church in 1054, and Episcopalian (Church of England in America) which separated from the Roman Catholic Church in 1534 are excluded. The 22 "Eastern Catholic autonomous particular churches", with the exception of the Chaldean Church, are also excluded. These are Churches which are in full communion with the Pope in Rome, but which practice their own rites which are different from the Western or Latin Roman Catholic Church. This dataset excludes rectories. Private homes, even if they are used for formal worship, are excluded from this dataset. Locations that are only used for administrative purposes are also excluded. This dataset also includes original TGS research. All data is non license restricted data. TGS has ceased making phone calls to verify information about religious locations. Therefore all entities in this dataset were €œverified€ using alternative reference sources, such as topo maps, parcel maps, various sources of imagery, and internet research. The CONTHOW attribute for these entities has been set to €œALT REF€ . Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g. the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2007/09/05 and the newest record dates from 2007/09/05; abstract: Roman Catholic Churches In Large Cities in Arkansas This dataset includes buildings where Roman Catholics gather for organized worship in cities with a population of 50,000 people or more. Roman Catholic Churches are Christian Churches that are subject to the papal authority in Rome. In addition to what are commonly thought of as Roman Catholic Churches, this data set also includes Newman (or Neumann) Centers and Chaldean Churches. Newman Centers are Roman Catholic Churches setup specifically to serve college or university populations. The Chaldean Church (also known as the Chaldean Church of Babylon) reunited with the Catholic Church in the 15th century. It originated in the Middle East. If a group of Roman Catholics gather for organized worship at a location that also serves another function, such as a school, these locations are included in this dataset if they otherwise meet the criteria for inclusion. Roman Catholic Shrines are included if they hold regularly scheduled mass. If a congregation celebrates mass at multiple locations, we have tried to include all such locations. This dataset excludes churches that are not subject to papal authority in Rome. Some churches may refer to themselves as "Catholic", and yet not be part of the "Roman" Catholic Church and these Churches are excluded from this dataset. Specifically Protestant Churches and their descendants which separated from the Roman Catholic Church beginning in 1517, Eastern Orthodox Churches (e.g. Russian, Greek) which separated from the Roman Catholic Church in 1054, and Episcopalian (Church of England in America) which separated from the Roman Catholic Church in 1534 are excluded. The 22 "Eastern Catholic autonomous particular churches", with the exception of the Chaldean Church, are also excluded. These are Churches which are in full communion with the Pope in Rome, but which practice their own rites which are different from the Western or Latin Roman Catholic Church. This dataset excludes rectories. Private homes, even if they are used for formal worship, are excluded from this dataset. Locations that are only used for administrative purposes are also excluded. This dataset also includes original TGS research. All data is non license restricted data. TGS has ceased making phone calls to verify information about religious locations. Therefore all entities in this dataset were €œverified€ using alternative reference sources, such as topo maps, parcel maps, various sources of imagery, and internet research. The CONTHOW attribute for these entities has been set to €œALT REF€ . Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g. the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2007/09/05 and the newest record dates from 2007/09/05
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Pass Christian, Mississippi by age, education, race, gender, work experience and more.
The overall aim was to conduct a wide-ranging survey of Catholic adults living in Britain, which asked about many aspects of their lives, including their socio-demographic circumstances, the nature and extent of their religious engagement (belonging, behaviour and beliefs), their views of the Catholic Church’s leadership, institutions and teachings, and their social and political attitudes. The survey was conducted online by Savanta ComRes, in October-November 2019. This is a cross-sectional dataset, based on interviews with 1,823 self-identifying Catholics adults in Britain (aged 18 and over).
In recent decades, the religious profile of British society has changed significantly, with a marked increase in 'religious nones', declining proportions identifying as Anglican or with a particular Non-Conformist tradition, an increase in non-denominational Christians, and the spread of non-Christian faiths. Within this wider context, Roman Catholics have remained broadly stable as a proportion of the adult population and represent the second largest Christian denomination in Britain, after Anglicans. However, there have been significant internal and external developments which have affected the institutional church and wider Roman Catholic community in Britain, and which could have shaped how Catholics' think about and engage with their faith and how it impacts their daily lives. Recent years have seen demographic change through significant inflows of Catholic migrants coming from Eastern Europe, the papal visit of Pope Benedict XVI to Britain in autumn 2010 (the first since 1982), Pope Francis's pontificate from 2013 onwards, Catholic leaders' political interventions against 'aggressive secularism' and in other policy debates, and internal crises and debates impacting on the perceived authority of the Catholic Church. The last major academic investigation of the Catholic community (and only in England and Wales) was undertaken in the late 1970s (Hornsby-Smith and Lee 1979; Hornsby-Smith 1987, 1991). It found that the 'distinctive subculture' of the Catholic community in the post-war period was evolving and dissolving in complex ways due to processes of social change and developments within the wider faith, such as the Second Vatican Council (Hornsby-Smith 1987, 1991). It also demonstrated growing internal heterogeneity in Catholics' religious beliefs, practices and social attitudes (Hornsby-Smith 1987, 1991). However, while there has been some recent scholarship on particular topics relating to Catholics and Catholicism in Britain, using both general social surveys and limited one-off denomination-specific opinion polls (Clements 2014a, 2014b; 2016; Bullivant 2016a, 2016b), there has been no systematic academic inquiry into the Roman Catholic population in Britain. In comparison, an academic-led survey series has profiled the Catholic population in the United States on five occasions between 1987 and 2011, with other large-scale surveys carried out in recent years by organisations such as the Pew Research Center. Most existing research into the waning of religious belief, practice, and affiliation in Britain has focused either on the very large, macro level or on the very small, micro level. While both are important and necessary, largely missing has been sustained sociological attention on how secularising trends have affected - and are being mediated within - individual religious communities. This project would undertake such a task for Roman Catholics in Britain, by conducting a large-scale, thematically wide-ranging and nationally representative survey. It would provide a detailed study of personal faith, social attitudes and political engagement within a significant religious minority with distinctive historical roots and in which 'tribal' feelings of belonging have been strong. The core topics would consist of personal faith, religiosity and associational involvement in parish life; attitudes towards leadership and governance within the institutional church; attitudes on social and moral issues; and political attitudes and engagement. It would be thematically wide-ranging and analytically rich, providing a detailed portrait of contemporary social, religious and attitudinal heterogeneity amongst Catholics. By undertaking this large-scale and wide-ranging survey, an important and distinctive contribution would be made to the sociology of religion in Britain in general and to the study of its Catholic population in particular.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Historical Dataset of Christian Park School 82 is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1990-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1990-2023),Asian Student Percentage Comparison Over Years (1988-1990),Hispanic Student Percentage Comparison Over Years (1993-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (1991-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2001-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2011-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2011-2022)
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of Pass Christian by race. It includes the distribution of the Non-Hispanic population of Pass Christian across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Pass Christian across relevant racial categories.
Key observations
Of the Non-Hispanic population in Pass Christian, the largest racial group is White alone with a population of 4,058 (71.89% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Pass Christian Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population 26 years and over Health Insurance Coverage Statistics for 2023. This is part of a larger dataset covering consumer health insurance coverage rates in Christian County, Missouri by age, education, race, gender, work experience and more.
https://lida.dataverse.lt/api/datasets/:persistentId/versions/1.2/customlicense?persistentId=hdl:21.12137/0VNUJEhttps://lida.dataverse.lt/api/datasets/:persistentId/versions/1.2/customlicense?persistentId=hdl:21.12137/0VNUJE
The purpose of the study: to explore the attitudes of Lithuanian population towards the development of European identity and citizenship in the context of EU change and enlargement. Major investigated questions: respondents were asked whether they support Lithuania's membership in the EU and how membership in this organisation brings benefits and disadvantages to Lithuania. They were asked whether they voted in the European Parliament elections and whether they often watch TV, listen to the radio or read daily newspapers to find out about political news. Next, they were asked to rate the influence of different people on important national issues (ordinary citizen; Member of the European Parliament - 11 choices in total). The survey went on to analyse whether it is more important to grow a competitive European economy within global markets or to ensure better social protection for all its citizens. They were asked to reveal the extent to which they associate themselves with their region, their country or Europe (EU). Given the block of questions, they were asked what it means to be Lithuanian (to be Christian; to follow Lithuanian cultural traditions - 8 choices in total). Given the list of threats, they were asked to rate the risk those threats pose to the EU (non-EU immigrants; EU expansion by including Turkey - 5 choices in total). Respondents had the opportunity to assess European unification and to indicate what it means to be European (being a Christian; following the European cultural traditions - 8 choices in total). Then, trust in the EU and in the ability of Lithuanian institutions to take the right decisions was assessed. The aim was to find out whether respondents felt that decision-makers at the EU level did not take Lithuania's interests into account sufficiently, and whether the interests of some EU Member States were given too much weight. The survey went on to analyse whether different policy areas should be dealt with at the national level or EU level (fight against unemployment; immigration policy [from non-EU countries] - 8 choices in total). Given the next set of questions, respondents were asked what the EU will look like in 10 years (unified EU tax system; mutual social security system - 4 choices in total). Next, they were asked how satisfied they are with the way democracy works in the EU and Lithuania. The survey went on to analyse whether the European Commission should be politically accountable to the European Parliament. Given another block of statements, respondents were asked whether or not different EU policies pose a risk to Lithuania (5 choices in total). Next, the survey went on to assess whether the redistribution of resources between EU Member States to protect the single currency is fair. Respondents were asked whether there should be a mutual EU army or whether each EU Member State should have its national army, and which institution is best suited to take care of Europe's security. Respondents were asked whether they were personally content with the introduction of the euro in Lithuania in 2015 and to describe their political views on a left-right scale. While having the future of the EU in mind, respondents were asked what the EU economy, the economic disparities between EU member states, the social disparities between EU citizens, the importance of the EU as a geopolitical power in the world and what the EU politically will be like in 10 years. The survey was concluded by asking whether or not Lithuania has benefited from EU membership. Socio-demographic characteristics: gender, age, nationality, education, marital status, occupation, income per household member per month, place of residence, lived, worked, studied abroad, religion, frequency of participation in religious services.
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License information was derived automatically
Context
The dataset tabulates the data for the Pass Christian, MS population pyramid, which represents the Pass Christian population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Pass Christian Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Historical Dataset of Valor Christian College is provided by CommunityCollegeReview and contain statistics on metrics:Total Faculty Trends Over Years (2019-2023),Total Enrollment Trends Over Years (2009-2023),Student-Staff Ratio Trends Over Years (2019-2023),Full-Time Students Enrollment Trends Over Years (2009-2023),Part-Time Students Enrollment Trends Over Years (2009-2023),Full-Time Undergraduate Students Enrollment Trends Over Years (2009-2023),Asian Student Percentage Comparison Over Years (2019-2023),Hispanic Student Percentage Comparison Over Years (2019-2021),Black Student Percentage Comparison Over Years (2019-2023),White Student Percentage Comparison Over Years (2019-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Non Resident Student Percentage Comparison Over Years (2019-2021),Diversity Score Comparison Over Years (2009-2023),Financial Aid Student Percentage Comparison Over the Years (2019-2023),Percentage Admitted Comparison Over the Years (2009-2010),Dormitory Capacity Trends Over Years (2019-2023)
Religion by Indigenous identity, age and gender for the population in private households.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual two or more races student percentage from 2014 to 2023 for Christian School vs. Alabama and Birmingham City School District
This Religion and State-Minorities (RASM) dataset is supplemental to the Religion and State Round 2 (RAS2) dataset. It codes the RAS religious discrimination variable using the minority as the unit of analysis (RAS2 uses a country as the unit of analysis and, is a general measure of all discrimination in the country). RASM codes religious discrimination by governments against all 566 minorities in 175 countries which make a minimum population cut off. Any religious minority which is at least 0.25 percent of the population or has a population of at least 500,000 (in countries with populations of 200 million or more) are included. The dataset also includes all Christian minorities in Muslim countries and all Muslim minorities in Christian countries for a total of 597 minorities. The data cover 1990 to 2008 with yearly codings.
These religious discrimination variables are designed to examine restrictions the government places on the practice of religion by minority religious groups. It is important to clarify two points. First, these variables focus on restrictions on minority religions. Restrictions that apply to all religions are not coded in this set of variables. This is because the act of restricting or regulating the religious practices of minorities is qualitatively different from restricting or regulating all religions. Second, this set of variables focuses only on restrictions of the practice of religion itself or on religious institutions and does not include other types of restrictions on religious minorities. The reasoning behind this is that there is much more likely to be a religious motivation for restrictions on the practice of religion than there is for political, economic, or cultural restrictions on a religious minority. These secular types of restrictions, while potentially motivated by religion, also can be due to other reasons. That political, economic, and cultural restrictions are often placed on ethnic minorities who share the same religion and the majority group in their state is proof of this.
This set of variables is essentially a list of specific types of religious restrictions which a government may place on some or all minority religions. These variables are identical to those included in the RAS2 dataset, save that one is not included because it focuses on foreign missionaries and this set of variables focuses on minorities living in the country. Each of the items in this category is coded on the following scale:
0. The activity is not restricted or the government does not engage in this practice.
1. The activity is restricted slightly or sporadically or the government engages in a mild form of this practice or a severe form sporadically.
2. The activity is significantly restricted or the government engages in this activity often and on a large scale.
A composite version combining the variables to create a measure of religious discrimination against minority religions which ranges from 0 to 48 also is included.
ARDA Note: This file was revised on October 6, 2017. At the PIs request, we removed the variable reporting on the minority's percentage of a country's population after finding inconsistencies with the reported values. For detailed data on religious demographics, see the "/data-archive?fid=RCSREG2" Target="_blank">Religious Characteristics of States Dataset Project.