NOTES:*Antarctica is included under the jurisdiction of the Christchurch, NZ diocese and therefore the Christchurch boundary and statistics are included in information about Antarctica.Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.World Regional BoundariesCredits: Esri; Global Mapping International, Missions Database: Global Mapping International; United States Central Intelligence AgencyThis layer represents the boundaries for the regions of the world. There are 25 commonly recognized world regions. The layer provides a base map of the regions for the world, providing a straightforward method of selecting a small multi-country area for display or study. The layer is suitable for display to a largest scale of 1:15,000,000.To download the data for this layer as a layer package for use in ArcGIS desktop applications, please refer to World Regions.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/

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

aCatholic populations by country from http://www.catholic-hierarchy.org/country/sc1.html[4].bOnly the top 31 Catholic countries with more than 5 million Catholics and countries in which at least 50% of the population is Catholic are included (as well as Canada and Uganda, each with more than 40% Catholic population), which excludes India, Indonesia, Kenya, Nigeria, and Vietnam.cFrom [6], [7].dFrom [8], [9].eFrom [10], [11].fChagas disease is found in every South American and Central American country listed [5].gFrom [31].

This dataset is extracted from https://en.wikipedia.org/wiki/Catholic_Church_by_country. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

PerCapita_CO2_Footprint_InDioceses_FULLBurhans, Molly A., Cheney, David M., Gerlt, R.. . “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.MethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

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.

Between 1991 and 2001, the number of Roman Catholics in Canada increased slightly, while the number adhering to Protestant denominations continued a long-term decline. The census enumerated just under 12.8 million Roman Catholics, up 4.8%, while the number of Protestants fell 8.2% to about 8.7 million. The largest gains in religious affiliations occurred among faiths consistent with changing immigration patterns toward more immigrants from regions outside of Europe, in particular Asia and the Middle East.

Using data for a representative sample of the Dutch population with information about participants’ religious background, we study the association between religion and moral behavior and attitudes. We find that religious people are less accepting of unethical economic behavior (e.g., tax evasion, bribery) and report more volunteering. They are equally likely as non-religious people to betray trust in an experimental game, where social behavior is unobservable and not directed to a self-selected group of recipients. Religious people also report lower preference for redistribution. Considering differences between denominations, Catholics betray less than non-religious people, while Protestants betray more than Catholics and are indistinguishable from the non-religious. We also explore the intergenerational transmission and the potential causality of these associations.

Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/

PerCapita_CO2_Footprint_InDioceses_FULLBurhans, Molly A., Cheney, David M., Gerlt, R.. . “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.MethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

A growing literature posits that colonial Christian missions brought schooling to the colonies, improving human capital in ways that persist to this day. But in some places they did much more. This paper argues that colonial Catholic missions in the Philippines functioned as state-builders, establishing law and order and building fiscal and infrastructural capacities in territories they controlled. The mission-as-state was the result of a bargain between the Catholic missions and the Spanish colonial government: missionaries converted the population and engaged in state-building, whereas the colonial government reaped the benefits of state expansion while staying in the capital. Exposure to these Catholic missions-as-state then led to long-run improvements in state capacity and development. I find that municipalities that had a Catholic mission have higher levels of state capacity and development today. A variety of mechanisms---religious competition, education, urbanization, and structural transformation---explain these results. (2021-11-08)

Program Version: State/SE 17.0 Data File: replication_data_church.dta Do-File: replication_dofile_church

Pope Francis will arrive in Canada today on a visit expressly meant to engage Indigenous peoples across the country, address the Catholic Church’s role in the residential school system, and to take steps toward reconciliation.

He is scheduled to arrive in Edmonton at 11:20 local time (1:20 p.m. EST) after a ten hour flight from Rome. At the airport he is expected to be greeted by a large group of Canadian leaders, including Prime Minister Justin Trudeau and Chief RoseAnne Archibald of the Assembly of First Nations.

Francis is not expected to speak publicly on the day of his arrival—or perform Mass, despite arriving on a Sunday—as spokespeople say his first words spoken in Canada will be at his visit to a former residential school in Maskwacis, just south of Edmonton.

The 85-year-old pope is flying aboard a plane supplied by the Italian national airline and will be accompanied by media as well as members of his staff and “seguito,” or inner circle.

He has struggled in recent months with mobility challenges, and cancelled another planned trip to Africa last month. As a result, a special lift will be used at the airport to assist him of the plane. As well, he is expected to use a wheelchair for much of the trip, and limit public appearances to no more than 60 to 90 minutes.

From the 17th century to the 1990s, about 150,000 children are known to have been put through the residential school system, which ripped Indigenous children from their families and placed them in institutions meant to destroy their culture and traditions. Many suffered emotional, physical and sexual abuse.

The schools were funded by the government and largely operated by religious churches, with about 60 per cent being run by the Catholic Church.

The Pope apologized for the church’s role in the schools in April from the Vatican, but an apology in Canada is seen as more meaningful and is expected to be made during the visit.

The Secretary of Social Development (SEDESOL) and the National Council to Prevent Discrimination developed the National Survey on Discrimination in Mexico to assess the amount of discrimination in the everyday lives of Mexican citizens. Specifically, SEDESOL wanted to analyze the problem from the perspectives of the general population and from specific vulnerable populations. For this reason, the survey developed seven different questionnaires: a general questionnaire for the general population and six separate questionnaires for targeted vulnerable populations. These targeted vulnerable populations included: a) population of elderly people, b) indigenous population, c) population with non-Catholic religious beliefs, d) female population, e) people with disabilities, and f) individuals with non-heterosexual preferences, which became a case study due to the difficulty covering that specific targeted population.

This dataset examines the responses of 789 individuals with non-Catholic religious beliefs in Mexico. These religious minorities were asked questions regarding the following: general views on discrimination; whether or not they have experienced discrimination based on their religious beliefs; whether or not Catholics have more privileges in society; what action should be taken to prevent religious discrimination; the role of government in preventing discrimination toward religious minorities; the life opportunities of religious minorities; their views on other vulnerable populations; and whether or not discrimination toward religious minorities has changed over the years. The methodology, questionnaire, and responses in the dataset were translated from Spanish into English.

Catholics to Population {title at top of page}Data Developers: Burhans, Molly A., Cheney, David M., Emege, Thomas, Gerlt, R.. . “Catholics to Population {title at top of page}”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Catholic Hierarchy, Environmental Systems Research Institute, Inc., 2019.Web map developer: Molly Burhans, October 2019Web app developer: Molly Burhans, October 2019GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/The Catholic Leadership global maps information is derived from the Annuario Pontificio, which is curated and published by the Vatican Statistics Office annually, and digitized by David Cheney at Catholic-Hierarchy.org -- updated are supplemented with diocesan and news announcements. GoodLands maps this into global ecclesiastical boundaries. Admin 3 Ecclesiastical Territories:Burhans, Molly A., Cheney, David M., Gerlt, R.. . “Admin 3 Ecclesiastical Territories For Web”. Scale not given. Version 1.2. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.Derived from:Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.

.CATHOLIC Whois Database, discover comprehensive ownership details, registration dates, and more for .CATHOLIC TLD with Whois Data Center.

Quelle: EVS (2016): European Values Study 2008: Integrated Dataset (EVS 2008). GESIS Data Archive, Cologne. ZA4800 Data file Version 3.0.0, doi:10.4232/1.11004

.CATHOLIC.EDU.AU Whois Database, discover comprehensive ownership details, registration dates, and more for .CATHOLIC.EDU.AU TLD with Whois Data Center.

Data on religion by gender and age for the population in private households in Canada, provinces and territories.

Full edition for scientific use. The long-term study ‘Religion in People's Lives’ has been conducted every ten years since 1970 and provides comprehensive data on the development of religion in Austria, Germany and Switzerland. The 2020 study will be accompanied by this online survey to gain additional insights. The Roman Catholic Church is undergoing an epochal change, as religion is now seen as an individual choice and no longer as a cultural destiny. In the future, there will be fewer Catholics but more committed Christians. This movement will be organised in a network structure, with communities (‘hostels’) that live the Gospel and are socially committed. This change will not be controlled by centralised institutions, but will develop from the grassroots, inspired by the Gospel and the Second Vatican Council. The reforms will emerge from the dynamics of local communities.

In November 2018 CyArk documented the Mexico City Metropolitan Cathedral in collaboration with the Directorate General of Sites and Monuments and the Secretaria de Cultura, Agenda Digital de Cultura. Citibanamex Compromiso Social supported the project. Subject to earthquake damage over the centuries of its existence, a 2017 earthquake caused further damage to the structure. Using laser scanning technology, photogrammetry, and drones, CyArk digitally capturing details of the structure today. This information will aid site managers in restoration work and preserving the cathedral, one of Mexico's most important religious and historic sites. Built on top of the capital of the Aztec empire, Tenochtitlan, Mexico City's Metropolitan Cathedral exemplifies the dynamic nature of a city and nation influenced by its indigenous and colonial histories. The Cathedral complex is the seat of the Roman Catholic Archdiocese of Mexico and composed of four buildings: the cathedral, the sagrario or sacristy, the Capilla de las Animas, and the Ex curia building. The expansively ornate cathedral draws visitors from around the world and remains an active religious center for Mexicans today. External Project Link: https://artsandculture.google.com/exhibit/yQIiSHwJIYFsKg Additional Info Link: https://cyark.org/projects/mexico-city-metropolitan-cathedral