This statistic shows the result of a survey conducted in 2017 on the level of knowledge about religion in Sweden. That year, the largest religious knowledge of Swedish population (a share of 86 percent of respondents) had great or some knowledge about Christianity, whereas 14 percent had not much or no knowledge about Christianity. In contrast, only 40 percent of individuals said that they have a great or some knowledge about Judaism.

This statistic shows the result of a survey on religious identification in Sweden in 2017, by type. That year, the largest group of Swedish population (a share of 43 percent) participating in this survey identified themselves as non-practicing Christians. Only nine percent of respondents was practicing Christian, defined by the source as someone who goes to church at least monthly.

This dataset shows the Worker Population Ratio (WPR), in percentage terms, for major religions, based on usual status (ps+ss). For years before 2017-18, the data was obtained in different quinquennial rounds of NSSO conducted from 2004-05 (NSS 61st) to 2011-12 (NSS 68th round). From 2017-18 the data is sourced from the annual report of the Periodic Labour Force Survey (PLFS) conducted by the Ministry of Statistics and Programme Implementation. The data highlights the proportion of the working population within major religious communities.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: A dwelling is a building or independent building unit, constructed, adapted or converted to be inhabited by one or more people on a permanent or temporary basis. It must have a direct and independent access from the street or through common circulation spaces such as corridors, patios or stairways. - Households: It is the person or group of people, whether related or not, who occupy in their entirety or in part a home. They share at least the main meals and/or take care of other needs in common basic, charged to a common budget (they eat from the "same pot"). - Group quarters: It is one intended to be inhabited by people usually without ties family members, subject to administrative regulations and who live together for study reasons, health, religion, work, and tourism, among others. Among the collective housing we have: institutional and non-institutional.

Universe

All households present in the country on the day of the census.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics and Computing

SAMPLE SIZE (person records): 2936271.

SAMPLE DESIGN: Systematic sample of every 10th household, drawn by the National Institute of Statistics and Informatics

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form with five sections for the location, dwelling, household, and individuals

The statistic shows the religious affiliation of the population in the United States in 2017, by age. In 2017, about 38 percent of respondents aged 18 to 29 years old were unaffiliated with any religious belief.

One belt, one road, in 2017, the proportion of religious population in 64 countries is the total population. Data source: organized by the author. Data quality is good. The data can have one broad prospect in one belt, one road, and the other is comprehensive research on economy, society, population and governance structure. "One belt, one road" covers Asia Pacific, Eurasia, Middle East, Africa, etc., including 65 countries, with a total population of over 4 billion 400 million, accounting for 63% of the world's population. One belt, one road, one belt, one road, one belt, one road, one area, and the other two. The first one is to make contributions to the systematic research and comprehensive application of the whole area.

Pakistan Religion Distribution Dataset (1901 to 2023)

Dataset Description

This dataset contains religious distribution data for Pakistan from 1901 to 2023, sourced from various census data and official reports. The dataset provides a comprehensive overview of the population breakdown by religious groups across different decades. It includes historical data on major religions such as Islam, Hinduism, Sikhism, Christianity, and others, along with population percentages for each group at different points in time.

The dataset spans over a century and serves as a valuable resource for understanding the demographic and religious shifts in Pakistan's population. This data can be useful for researchers, policymakers, and educators interested in the sociological and historical trends of religious communities in Pakistan.

File Information

• File Name: Pakistan_Religion_Distribution_1901_to_2023.csv
• File Format: CSV
• Columns: The file contains data for each religious group across the years 1901, 1911, 1921, 1931, 1941, 1951, 1961, 1972, 1981, 1998, 2017, and 2023.

Column Descriptors

Data Provenance

• Source: Census data from Pakistan's historical records, including census reports from 1901, 1911, 1921, 1931, 1941, 1951, 1961, 1972, 1981, 1998, 2017, and 2023.
• Collection Method: Data was compiled from official records, government publications, and historical census reports. The figures represent the religious distribution of the population across various administrative divisions, including Punjab, Sindh, Khyber Pakhtunkhwa, Balochistan, Azad Jammu and Kashmir, and Gilgit–Baltistan.
• Note: The 1901, 1911, 1931, and 1941 data include information for all administrative divisions that composed the region of contemporary Pakistan, while 1951 and 1961 data represent the total population of the former administrative division of West Pakistan.

Use Cases

This dataset is ideal for: - Studying demographic and religious trends in Pakistan - Researching the impact of religious distribution on social policies - Understanding historical changes in religious communities

This statistic shows the result of a survey on religious identification in Denmark in 2017, by type. The majority of the population, with a share of ** percent, was non-practicing Christians. The share with the lowest religious identification in Denmark had other religion than Christianity, reaching **** percent.

About this dataset

Context

The dataset tabulates the Faith population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Faith. The dataset can be utilized to understand the population distribution of Faith by age. For example, using this dataset, we can identify the largest age group in Faith.

Key observations

The largest age group in Faith, SD was for the group of age 50-54 years with a population of 40 (14.18%), according to the 2021 American Community Survey. At the same time, the smallest age group in Faith, SD was the 20-24 years with a population of 0 (0.00%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Faith is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Faith total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Faith Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Christian County population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Christian County. The dataset can be utilized to understand the population distribution of Christian County by age. For example, using this dataset, we can identify the largest age group in Christian County.

Key observations

The largest age group in Christian County, IL was for the group of age 55-59 years with a population of 2,767 (8.13%), according to the 2021 American Community Survey. At the same time, the smallest age group in Christian County, IL was the 85+ years with a population of 818 (2.40%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Christian County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Christian County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Christian County Population by Age. You can refer the same here

This statistic displays the religiously unaffiliated population in Belgium in 2017, by upbringing. 38 percent of the respondents participating in this survey said to consider themselves as religiously unaffiliated. Of these people, 25 percent was also raised unaffiliated. On the other hand, nearly 90 percent of the unaffiliated said they were baptized.

About this dataset

Context

The dataset tabulates the Pass Christian population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Pass Christian. The dataset can be utilized to understand the population distribution of Pass Christian by age. For example, using this dataset, we can identify the largest age group in Pass Christian.

Key observations

The largest age group in Pass Christian, MS was for the group of age 5-9 years with a population of 496 (8.77%), according to the 2021 American Community Survey. At the same time, the smallest age group in Pass Christian, MS was the 85+ years with a population of 67 (1.18%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Pass Christian is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Pass Christian total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Pass Christian Population by Age. You can refer the same here

This statistic shows the result of a survey conducted in 2017 on people agreeing that Islam is fundamentally incompatible with Denmark's culture and values. That year, the largest agreement of the Danish population was church-attending Christians, with a share of 55 percent of respondents. Compared with the religiously unaffiliated reaching 30 percent of individuals it was 25 percentage points higher.

About this dataset

Context

The dataset tabulates the Faith 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 Faith. 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 - 64 years with a poulation of 137 (48.58% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Faith population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Faith is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Faith is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Faith Population by Age. You can refer the same here

This statistic displays the religiously unaffiliated population share in Belgium in 2017, by conviction. Roughly ** percent of the Belgian respondents participating in this survey said to be religiously unaffiliated. Of this ** percent, nearly ** percent of the participants described themselves as atheist. Five percent said to be agnostic.

Abstract

In 1985 the population and health observatory was established at Mlomp, in the region of Ziguinchor, in southern Senegal (see map). The objective was to complement the two rural population observatories then existing in the country, Bandafassi, in the south-east, and Niakhar, in the centre-west, with a third observatory in a region - the south-west of the country (Casamance) - whose history, ethnic composition and economic situation were quite different from those of the regions where the first two observatories were located. It was expected that measuring the demographic levels and trends on those three sites would provide better coverage of the demographic and epidemiological diversity of the country.

Following a population census in 1984-1985, demographic events and causes of death have been monitored yearly. During the initial census, all women were interviewed concerning the birth and survival of their children. Since 1985, yearly censuses, usually conducted in January-February, have been recording demographic data, including all births, deaths, and migrations. The completeness and accuracy of dates of birth and death are cross-checked against those of registers of the local maternity ward (_95% of all births) and dispensary (all deaths are recorded, including those occurring outside the area), respectively. The study area comprises 11 villages with approximately 8000 inhabitants, mostly Diola. Mlomp is located in the Department of Oussouye, Region of Ziguinchor (Casamance), 500 km south of Dakar.

On 1 January 2000 the Mlomp area included a population of 7,591 residents living in 11 villages. The population density was 108 people per square kilometre. The population belongs to the Diola ethnic group, and the religion is predominantly animist, with a large minority of Christians and a few Muslims. Though low, the educational level - in 2000, 55% of women aged 15-49 had been to school (for at least one year) - is definitely higher than at Bandafassi. The population also benefits from much better health infrastructure and programmes. Since 1961, the area under study has been equipped with a private health centre run by French Catholic nurses and, since 1968, a village maternity centre where most women give birth. The vast majority of the children are totally immunized and involved in a growth-monitoring programme (Pison et al.,1993; Pison et al., 2001).

Geographic coverage

The Mlomp DSS site, about 500 km from the capital, Dakar, in Senegal, lies between latitudes 12°36' and 12°32'N and longitudes 16°33' and 16°37'E, at an altitude ranging from 0 to 20 m above sea level. It is in the region of Ziguinchor, Département of Oussouye (Casamance), in southwest Senegal. It is locates 50 km west of the city of Ziguinchor and 25 kms north of the border with Guinea Bissau. It covers about half the Arrondissement of Loudia-Ouolof. The Mlomp DSS site is about 11 km × 7 km and has an area of 70 km2. Villages are households grouped in a circle with a 3-km diameter and surrounded by lands that are flooded during the rainy season and cultivated for rice. There is still no electricity.

Analysis unit

Individual

Universe

At the census, a person was considered a member of the compound if the head of the compound declared it to be so. This definition was broad and resulted in a de jure population under study. Thereafter, a criterion was used to decide whether and when a person was to be excluded or included in the population.

A person was considered to exit from the study population through either death or emigration. Part of the population of Mlomp engages in seasonal migration, with seasonal migrants sometimes remaining 1 or 2 years outside the area before returning. A person who is absent for two successive yearly rounds, without returning in between, is regarded as having emigrated and no longer resident in the study population at the date of the second round. This definition results in the inclusion of some vital events that occur outside the study area. Some births, for example, occur to women classified in the study population but physically absent at the time of delivery, and these births are registered and included in the calculation of rates, although information on them is less accurate. Special exit criteria apply to babies born outside the study area: they are considered emigrants on the same date as their mother.

A new person enters the study population either through birth to a woman of the study population or through immigration. Information on immigrants is collected when the list of compounds of a village is checked ("Are there new compounds or new families who settled since the last visit?") or when the list of members of a compound is checked ("Are there new persons in the compound since the last visit?"). Some immigrants are villagers who left the area several years before and were excluded from the study population. Information is collected to determine in which compound they were previously registered, to match the new and old information.

Information is routinely collected on movements from one compound to another within the study area. Some categories of the population, such as older widows or orphans, frequently move for short periods of time and live in between several compounds, and they may be considered members of these compounds or of none. As a consequence, their movements are not always declared.

Kind of data

Event history data

Frequency of data collection

One round of data collection took place annually, except in 1987 and 2008.

Sampling procedure

No samplaing is done

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

List of questionnaires: - Household book (used to register informations needed to define outmigrations) - Delivery questionnaire (used to register information of dispensaire ol mlomp) - New household questionnaire - New member questionnaire - Marriage and divorce questionnaire - Birth and marital histories questionnaire (for a new member) - Death questionnaire (used to register the date of death)

Cleaning operations

On data entry data consistency and plausibility were checked by 455 data validation rules at database level. If data validaton failure was due to a data collection error, the questionnaire was referred back to the field for revisit and correction. If the error was due to data inconsistencies that could not be directly traced to a data collection error, the record was referred to the data quality team under the supervision of the senior database scientist. This could request further field level investigation by a team of trackers or could correct the inconsistency directly at database level.

No imputations were done on the resulting micro data set, except for:

a. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is greater than 180 days, the ENT event was changed to an in-migration event (IMG). b. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is less than 180 days, the OMG event was changed to an homestead exit event (EXT) and the ENT event date changed to the day following the original OMG event. c. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is greater than 180 days, the EXT event was changed to an out-migration event (OMG). d. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is less than 180 days, the IMG event was changed to an homestead entry event (ENT) with a date equal to the day following the EXT event. e. If the last recorded event for an individual is homestead exit (EXT) and this event is more than 180 days prior to the end of the surveillance period, then the EXT event is changed to an out-migration event (OMG)

In the case of the village that was added (enumerated) in 2006, some individuals may have outmigrated from the original surveillance area and setlled in the the new village prior to the first enumeration. Where the records of such individuals have been linked, and indivdiual can legitmately have and outmigration event (OMG) forllowed by and enumeration event (ENU). In a few cases a homestead exit event (EXT) was followed by an enumeration event in these cases. In these instances the EXT events were changed to an out-migration event (OMG).

Response rate

On an average the response rate is about 99% over the years for each round.

Sampling error estimates

Not applicable

Data appraisal

CenterId Metric Table QMetric Illegal Legal Total Metric Rundate
SN012 MicroDataCleaned Starts 18756 2017-05-19 00:00
SN012 MicroDataCleaned Transitions 0 45136 45136 0 2017-05-19 00:00
SN012 MicroDataCleaned Ends 18756 2017-05-19 00:00
SN012 MicroDataCleaned SexValues 38 45098 45136 0 2017-05-19 00:00
SN012 MicroDataCleaned DoBValues 204 44932 45136 0 2017-05-19 00:00

The research considered the ways that faith is experienced and negotiated by seafarers on board cargo ships as well as the provisions for faith/welfare made by charitable organisations based in ports ashore.

In order to understand these areas, we used a combination of qualitative research methods, specifically, observation and interviews. Fifty-five shipboard semi-structured interviews with seafarers were carried out (representing all of those seafarers who were present while the researcher was on board). Interviews were conducted with reference to a flexible interview guide and they were digitally recorded and transcribed. Transcripts were analysed and thematically coded using Nvivo 12. Shipboard research was complemented by research in two seafarers’ centres ashore. These UK-based centres have been assigned the pseudonyms Riverside and Porton. Both centres supplied services to more than one port within their locality and were run by different faith-based charities. They were chosen with reference to the size and cargoes of the ports concerned and the organisations running them. An interview guide provided the framework for semi-structured interviews with chaplains and volunteers in these two ports. Five formal interviews were carried out with paid staff, and ten formal interviews were carried out with volunteers, at the two centres. We supplemented our research in the two ports with nine interviews with representatives from the main charitable bodies connected to seafarers’ welfare (3 in the UK and 6 based outside the UK) and with seven additional chaplains/volunteers providing welfare services for seafarers in both UK (1) and non-UK (6) ports. Chaplains were selected with reference to gender and nationality to ensure an appropriate mix.

Interviews with non-Filipino seafarers and port-based centre staff and volunteers were undertaken in English. Interviews with Filipino participants were undertaken in Tagalog and were subsequently translated by the fieldworker. All seafarers on board the two ships where observational work was conducted were included in the research resulting in a full representation of all ranks on board. All seafarers on board were male which is common in the cargo shipping sector where less than 1% of the workforce is estimated to be female. Interviews were of between one and two hours duration.

In increasingly secular societies the significance of religion could be regarded as waning. However, with increased population mobility and the tendency for some conflict to be cast around religious difference it is critical that the social sciences return to religion as a centrally important tenet. This project considers religious difference alongside spiritual need in relation to the case of global seafaring. The research will make an important contribution to our understanding of how multi-faith groups peacefully co-exist and what factors may disrupt/threaten social harmony in religiously diverse populations. The project will focus upon seafarers from different countries and of multiple faiths living and working together on ships and in ports. In the context of the challenging social circumstances where they live and work (confined in relatively small spaces on board working cargo ships and largely isolated from wider society) it will explore how they understand their own spirituality and that of colleagues and how they manage/experience religious needs/expression. Traditionally ports in the UK and US have provided chaplaincy/welfare services to international seafarers of multiple faiths in an effort to meet a variety of spiritual/social needs. These past and present services will also be a focus for the research. Archive data will be collected charting the historical development of chaplaincy in ports in the UK/US. In addition, contemporary chaplains will be included as participants in order to understand how they shape and practice their respective religious beliefs, alongside their vocation for ministry, and how their organisations have changed over time in relation to their objectives and practices in funding such ministry. This combination of research concerns will provide the opportunity for us to analyse seafarers' own religious perspectives and attitudes towards other faiths; seafarers' spiritual needs; available support for seafarers' spiritual needs within the confines of ports; access and experiences of such port-based welfare/religious services (from the point of view of seafarers) the objectives of organisations providing chaplaincy in ports and their associated plans for the future. Three aims guide the project 1) We aim to inform better welfare/spiritual provision by organisations working in ports to seafarers calling at them 2) We aim to gain a better understanding of how traditional/non-traditional religions/spirituality are expressed, experienced, and negotiated in ports and in multinational residential workplaces (i.e. ships). 3) We will explore the evolution of religion in limited but important situations outside congregations and formally designated religious sites. In this we aim to add to academic understandings of contemporary 'religion' and its diversity and to study religion/spirituality beyond expected locations (e.g. churches/religious communities). The study has 4 main components. 1) Historical examination of archive material relating to the development of welfare and religious services in US/UK ports 2) A series of semi-structured interviews with key stakeholder organisations, which fund/manage current port-based ministry and welfare 3) Port-based ethnography focussing on observation of chaplaincy 'in action' and interviews with key participants/providers 4) Shipboard ethnography focussing on seafarers and their spiritual/religious practices/needs/expression. This bi-national case study will be conducted by a multi-disciplinary team of sociologists and theologians. It will assess continuities/discontinuities between ports in terms of provision and the diverse ways religion is present on cargo ships. This will be of practical value to seafarers and those attempting to meet their spiritual/religious needs, of academic value to scholars of religion and the workplace, and of general value in raising awareness of a vital but neglected area of modern economic life.

Presents demographic statistics related to the female population in Alberta, including: age structure, regional differences, culture and religion,

“Interreligious Conflicts in Indonesia 2017” provides documentation of a cross-religious dataset among the general population in six potential conflict regions in Indonesia. The Dans Data Guide 15 (meta-data) contains the research topic, theoretical framework, relevant concepts and measurements, the purposive sampling of locations, data collection procedures, the random selection of respondents and the response rates. The data were collected to investigate the relationship of ethno-religious identification with support for interreligious violence among the general population in carefully selected areas of latent and manifest conflict in Indonesia: Bekasi, South Lampung, Singkil-Aceh, Poso, Kupang, and Sampang-Madura. This research applies and further develops an integrated theory of intergroup conflict, in formulating and empirically testing hypotheses on cross-cultural and inter-individual differences of latent conflict, more specifically inter-group contact avoidance and support of interreligious protests and interreligious violence. The research is funded by the Indonesia Endowment Fund for Education (LPDP). Valid: 2017-11-10

The latest population figures produced by the Office for National Statistics (ONS) on 28 June 2018 show that an estimated 534,800 people live in Bradford District – an increase of 2,300 people (0.4%) since the previous year.

Bradford District is the fifth largest metropolitan district (in terms of population) in England, after Birmingham, Leeds, Sheffield and Manchester although the District’s population growth is lower than other major cities.

The increase in the District’s population is largely due to “natural change”- there have been around 3,300 more births than deaths, although this has been balanced by a larger number of people leaving Bradford to live in other parts of the UK than coming to live here and a lower number of international migrants. In 2016/17 the net internal migration was -2,700 and the net international migration was 1,700.

A large proportion of Bradford’s population is dominated by the younger age groups. More than one-quarter (29%) of the District’s population is aged less than 20 and nearly seven in ten people are aged less than 50. Bradford has the highest percentage of the under 16 population in England after the London Borough of Barking and Dagenham, Slough Borough Council and Luton Borough Council.

The population of Bradford is ethnically diverse. The largest proportion of the district’s population (63.9%) identifies themselves as White British. The district has the largest proportion of people of Pakistani ethnic origin (20.3%) in England.

The largest religious group in Bradford is Christian (45.9% of the population). Nearly one quarter of the population (24.7%) are Muslim. Just over one fifth of the district’s population (20.7%) stated that they had no religion.

There are 216,813 households in the Bradford district. Most households own their own home (29.3% outright and 35.7% with a mortgage). The percentage of privately rented households is 18.1%. 29.6% of households were single person households.

Information from the Annual Population Survey in December 2017 found that Bradford has 228,100 people aged 16-64 in employment. At 68% this is significantly lower than the national rate (74.9%). 91,100 (around 1 in 3 people) aged 16-64, are not in work. The claimant count rate is 2.9% which is higher than the regional and national averages.

Skill levels are improving with 26.5% of 16 to 74 year olds educated to degree level. 18% of the district’s employed residents work in retail/wholesale. The percentage of people working in manufacturing has continued to decrease from 13.4% in 2009 to 11.9% in 2016. This is still higher than the average for Great Britain (8.1%).