"Between October 2011 and November 2012, Pew Research Center, with generous funding from The Pew Charitable Trusts and the John Templeton Foundation, conducted a public opinion survey involving more than 30,000 face-to-face interviews in 26 countries in Africa, Asia, the Middle East and Europe. The survey asked people to describe their religious beliefs and practices, and sought to gauge respondents; knowledge of and attitudes toward other faiths. It aimed to assess levels of political and economic satisfaction, concerns about crime, corruption and extremism, positions on issues such as abortion and polygamy, and views of democracy, religious law and the place of women in society.
"Although the surveys were nationally representative in most countries, the primary goal of the survey was to gauge and compare beliefs and attitudes of Muslims. The findings for Muslim respondents are summarized in the Religion & Public Life Project's reports The World's Muslims: Unity and Diversity and The World's Muslims: Religion, Politics and Society, which are available at www.pewresearch.org. [...] This dataset only contains data for Muslim respondents in the countries surveyed. Please note that this codebook is meant as a guide to the dataset, and is not the survey questionnaire." (2012 Pew Religion Worlds Muslims Codebook)
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Associated with manuscript titled: Fifty Muslim-majority countries have fewer COVID-19 cases and deaths than the 50 richest non-Muslim countriesThe objective of this research was to determine the difference in the total number of COVID-19 cases and deaths between Muslim-majority and non-Muslim countries, and investigate reasons for the disparities. Methods: The 50 Muslim-majority countries had more than 50.0% Muslims with an average of 87.5%. The non-Muslim country sample consisted of 50 countries with the highest GDP while omitting any Muslim-majority countries listed. The non-Muslim countries’ average percentage of Muslims was 4.7%. Data pulled on September 18, 2020 included the percentage of Muslim population per country by World Population Review15 and GDP per country, population count, and total number of COVID-19 cases and deaths by Worldometers.16 The data set was transferred via an Excel spreadsheet on September 23, 2020 and analyzed. To measure COVID-19’s incidence in the countries, three different Average Treatment Methods (ATE) were used to validate the results. Results published as a preprint at https://doi.org/10.31235/osf.io/84zq5(15) Muslim Majority Countries 2020 [Internet]. Walnut (CA): World Population Review. 2020- [Cited 2020 Sept 28]. Available from: http://worldpopulationreview.com/country-rankings/muslim-majority-countries (16) Worldometers.info. Worldometer. Dover (DE): Worldometer; 2020 [cited 2020 Sept 28]. Available from: http://worldometers.info
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Hadith (an Arabic word) refers to the words and actions of Prophet Mohammed. Those collections of Hadiths have been transmitted through generations of Muslim scholars until they have been collected and written in big collections. The chain of narrators is a main area of study in Islamic scholarship because a single hadith may have multiple chains of narrators (that may or may not overlap). However, it has mainly remained a qualitative field where scholars of Hadith try to determine the authenticity of Hadiths by investigating and validating the chains of narrators who transmitted a given hadith.
This unprecedented dataset contains over 24,000 scholars and narrators along with their teachers/students (and other metadata as well) which will provide a macroscopic overview of how and where hadith have been preserved in the early days of Islam. The dataset can also answer many other questions about whether certain schools of scholarships are more prolific in preserving hadiths than others.
This dataset wouldn't have been possible without the great people who have already transcribed this dataset from primary sources and bibliographies to muslimscholars.info database. I only scraped this database with a Python script plus very minimal cleanup.
The idea of collecting the dataset was inspired by this project.
I plan to extend this project by extracting the chain of every hadith and combining it with this dataset.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Hadith (an Arabic word) refers to the words and actions of Prophet Mohammed. Those collections of Hadiths have been transmitted through generations of Muslim scholars until they have been collected and written in big collections. The chain of narrators is a main area of study in Islamic scholarship because a single hadith may have multiple chains of narrators (that may or may not overlap). However, it has mainly remained a qualitative field where scholars of Hadith try to determine the authenticity of Hadiths by investigating and validating the chains of narrators who transmitted a given hadith. Further, the raw texts of Hadiths have not yet been used in qualitative approaches in data analysis. I hope this dataset makes it easier to further progress in this direction.
Hadith dataset contains the set of all Hadiths from the six primary hadith collections. The data is scraped from http://qaalarasulallah.com/. Note that the chain_indx column refers to scholar_indx column in Hadith Narrators Dataset.
Notably, this is a very draft version of the dataset as it is not validated. For example, the number of Hadiths in this dataset is much higher than the real number of Hadiths contained in those sources. This may be due to a bug in my script. Further actions will be taken to further clean up this dataset. However, as it is right now, it can be used to prototype certain analyses in those areas.
Disclaimer: I scraped the data and I hold no responsibility for its accuracy or validation. Use at your own risk!
This dataset wouldn't have been possible without the great people who have already transcribed this dataset from primary sources and bibliographies to muslimscholars.info & qaalarasulallah.com database. I only scraped this database with a Python script plus very minimal cleanup.
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The religious dataset consisting of Hindu and Muslim hate comments from Bangladesh and India in the Bangla language is a collection of online comments that contain religious hate speech targeting either the Hindu or Muslim communities. These comments were gathered from various sources such as newspapers, social media platforms, and online forums. The purpose of collecting this data is to analyze the prevalence of religious intolerance, identify patterns in hate speech, and contribute to the development of tools for automatically detecting and mitigating such content.
Key Features of the Dataset: Source and Collection:
Comments were sourced from both Bangladesh and India, reflecting religious sentiments in these neighboring countries where tensions between religious groups have often been a social issue. Sources include Bangla-language social media, news articles, opinion pieces, and comments sections on websites.
Content: The dataset contains a mix of both Hindu-targeted hate speech and Muslim-targeted hate speech, with derogatory, offensive, and inflammatory remarks based on religion. Hate comments include stereotypical statements, incitement to violence, communal hatred, and discriminatory language directed at members of the opposing community.
Purpose and Use Cases: Hate Speech Detection: This dataset is useful for developing machine learning models that can automatically identify and flag harmful content on social media platforms. Social Science Research: Researchers can study the psychological and sociopolitical factors that drive such hate speech. Policy and Moderation Tools: Governments, social media platforms, and civil society organizations can use insights from this dataset to design anti-hate speech policies and create moderation systems that reduce online hate.
Challenges: Contextual Nuances: Understanding the cultural and religious context of Bangla comments is crucial for accurately identifying hate speech. A comment that might seem neutral in one context could be deeply offensive in another. Code-Switching: Some comments might mix Bangla with English or regional languages, complicating the classification and sentiment analysis process. Bias in Data: The dataset might reflect a certain level of social bias depending on the region from which it was collected, which needs to be addressed when training AI models.
Conclusion: This dataset offers valuable insights into the dynamics of religious hate speech in Bangladesh and India, two countries with diverse religious populations and a history of interfaith tension. It can help in the development of tools for mitigating online hate speech, while also fostering better understanding and tolerance across religious communities.
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### Institute for the Study of Contemporary Antisemitism (ISCA) at Indiana University Dataset on bias against Asians, Blacks, Jews, Latines, and Muslims
The ISCA project compiled this dataset using an annotation portal, which was used to label tweets as either biased or non-biased, among other labels. Note that the annotation was done on live data, including images and context, such as threads. The original data comes from annotationportal.com. They include representative samples of live tweets from the years 2020 and 2021 with the keywords "Asians, Blacks, Jews, Latinos, and Muslims".
A random sample of 600 tweets per year was drawn for each of the keywords. This includes retweets. Due to a sampling error, the sample for the year 2021 for the keyword "Jews" has only 453 tweets from 2021 and 147 from the first eight months of 2022 and it includes some tweets from the query with the keyword "Israel." The tweets were divided into six samples of 100 tweets, which were then annotated by three to seven students in the class "Researching White Supremacism and Antisemitism on Social Media" taught by Gunther Jikeli, Elisha S. Breton, and Seth Moller at Indiana University in the fall of 2022, see this report. Annotators used a scale from 1 to 5 (confident not biased, probably not biased, don't know, probably biased, confident biased). The definitions of bias against each minority group used for annotation are also included in the report.
If a tweet called out or denounced bias against the minority in question, it was labeled as "calling out bias."
The labels of whether a tweet is biased or calls out bias are based on a 75% majority vote. We considered "probably biased" and "confident biased" as biased and "confident not biased," "probably not biased," and "don't know" as not biased.
The types of stereotypes vary widely across the different categories of prejudice. While about a third of all biased tweets were classified as "hate" against the minority, the stereotypes in the tweets often matched common stereotypes about the minority. Asians were blamed for the Covid pandemic. Blacks were seen as inferior and associated with crime. Jews were seen as powerful and held collectively responsible for the actions of the State of Israel. Some tweets denied the Holocaust. Hispanics/Latines were portrayed as being in the country illegally and as "invaders," in addition to stereotypical accusations of being lazy, stupid, or having too many children. Muslims, on the other hand, were often collectively blamed for terrorism and violence, though often in conversations about Muslims in India.
# Content:
This dataset contains 5880 tweets that cover a wide range of topics common in conversations about Asians, Blacks, Jews, Latines, and Muslims. 357 tweets (6.1 %) are labeled as biased and 5523 (93.9 %) are labeled as not biased. 1365 tweets (23.2 %) are labeled as calling out or denouncing bias.
1180 out of 5880 tweets (20.1 %) contain the keyword "Asians," 590 were posted in 2020 and 590 in 2021. 39 tweets (3.3 %) are biased against Asian people. 370 tweets (31,4 %) call out bias against Asians.
1160 out of 5880 tweets (19.7%) contain the keyword "Blacks," 578 were posted in 2020 and 582 in 2021. 101 tweets (8.7 %) are biased against Black people. 334 tweets (28.8 %) call out bias against Blacks.
1189 out of 5880 tweets (20.2 %) contain the keyword "Jews," 592 were posted in 2020, 451 in 2021, and ––as mentioned above––146 tweets from 2022. 83 tweets (7 %) are biased against Jewish people. 220 tweets (18.5 %) call out bias against Jews.
1169 out of 5880 tweets (19.9 %) contain the keyword "Latinos," 584 were posted in 2020 and 585 in 2021. 29 tweets (2.5 %) are biased against Latines. 181 tweets (15.5 %) call out bias against Latines.
1182 out of 5880 tweets (20.1 %) contain the keyword "Muslims," 593 were posted in 2020 and 589 in 2021. 105 tweets (8.9 %) are biased against Muslims. 260 tweets (22 %) call out bias against Muslims.
# File Description:
The dataset is provided in a csv file format, with each row representing a single message, including replies, quotes, and retweets. The file contains the following columns:
'TweetID': Represents the tweet ID.
'Username': Represents the username who published the tweet (if it is a retweet, it will be the user who retweetet the original tweet.
'Text': Represents the full text of the tweet (not pre-processed).
'CreateDate': Represents the date the tweet was created.
'Biased': Represents the labeled by our annotators if the tweet is biased (1) or not (0).
'Calling_Out': Represents the label by our annotators if the tweet is calling out bias against minority groups (1) or not (0).
'Keyword': Represents the keyword that was used in the query. The keyword can be in the text, including mentioned names, or the username.
# Licences
Data is published under the terms of the "Creative Commons Attribution 4.0 International" licence (https://creativecommons.org/licenses/by/4.0)
# Acknowledgements
We are grateful for the technical collaboration with Indiana University's Observatory on Social Media (OSoMe). We thank all class participants for the annotations and contributions, including Kate Baba, Eleni Ballis, Garrett Banuelos, Savannah Benjamin, Luke Bianco, Zoe Bogan, Elisha S. Breton, Aidan Calderaro, Anaye Caldron, Olivia Cozzi, Daj Crisler, Jenna Eidson, Ella Fanning, Victoria Ford, Jess Gruettner, Ronan Hancock, Isabel Hawes, Brennan Hensler, Kyra Horton, Maxwell Idczak, Sanjana Iyer, Jacob Joffe, Katie Johnson, Allison Jones, Kassidy Keltner, Sophia Knoll, Jillian Kolesky, Emily Lowrey, Rachael Morara, Benjamin Nadolne, Rachel Neglia, Seungmin Oh, Kirsten Pecsenye, Sophia Perkovich, Joey Philpott, Katelin Ray, Kaleb Samuels, Chloe Sherman, Rachel Weber, Molly Winkeljohn, Ally Wolfgang, Rowan Wolke, Michael Wong, Jane Woods, Kaleb Woodworth, and Aurora Young.
This work used Jetstream2 at Indiana University through allocation HUM200003 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.
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The present data from 194 customers of small and medium enterprises (SMEs) tell us about their acceptance of Islamic microfinance in Kano State, Nigeria. The dataset includes variables such as gender, age, marital status, duration as customer, account operate, annual income, type of business, service quality, perceived value, corporate image and religiosity of customers in Kano State. We fielded a survey from March to June 2019, self-administered questionnaires were used for data collection. This data may help scholars to understand how people of Kano State accept Islamic microfinance interacted with service quality, customer perceived value, corporate image and religiosity.
https://doi.org/10.17026/fp39-0x58https://doi.org/10.17026/fp39-0x58
This dataset contains the Arab-West Report special reports that were published in 2004.This dataset mainly contains the writings of Cornelis Hulsman ,Drs., among other authors on topics related to Muslim- Christian relations and interfaith dialogue between the West and Islamic world. Additionally this dataset contains reports pertaining to certain Muslim –Christian incidents and reports about allegations of forced conversions of Coptic girls. Some of the articles addressed the issue of missionaries.Further reports address monastic life and recommendations of Arab-West Report's work by other social figures.Furthermore, the dataset included commentary on published material from other sources (reviews/critique of articles from other media).Some of the themes that characterized this dataset:-A description of the history of the conflicts around the development of the convent of Patmos on the Cairo-Suez road.-An overview of a book titled “Christians versus Muslims in Modern Egypt: The Century-Long Struggle for Coptic Equality” by S. S. Hasan.- Rumors of forced conversions Of Coptic girls: A report by Hulsman stated that the US Copts Association published a press release on March 25, 2004 with the title “Coptic Pope Denounces Forced Conversion of Coptic Girls.” He criticized that the US Copts Association for not making much of an effort, if any, to check the veracity of the rumors.- A Glimpse into Monastic Life in Egypt: A Visit to St. Maqarius Monastery:- Another report covered the incident in which a priest and two members of the church board of Taha al-ʿAmeda died after an accident with a speeding car driven by a police officer.- A critique of Al-Usbuʿa newspapers: the author accused the newspaper of cherry-picking statements by Coptic extremists, who are much disliked in the US Coptic community and who have no following. He considered that quoting statements from such isolated radicals gives readers the impression that they represent much more than a few individuals. It has all appearance that al-Usbuʿa has highlighted these radicals to create fear and harm the reputation of US Copts in Egypt.- A number of reports highlighted a visit and the speech delivered by the Archbishop of Canterbury, Dr George Carey (Lord Carey) at the Azhar entitled “Muslims/Christian Relationships: A New Age Of Hope?”- A report covered the first visit made by Archbishop Rowan Williams to the Diocese of Egypt since he became the Archbishop of Canterbury. The archbishop met with President Mubarak, Dr. Muhammad Sayyed Tantawi, the Grand Imam of the Azhar, Pope Shenouda and also laid the foundation stone of Harpur Community Health Centre in Sadat City.- Updates on the developments of AWR’s work to create an electronic archive of information pertaining to relations between Muslims and Christians in the Arab-World in general and Egypt in particular.Additionally, this dataset also provides updates of the then-under construction - Center for Arab-West Understanding (CAWU) web-based Electronic Documentation Center (EDC) for contemporary information covering Arab-West and Muslim-Christian relations.- A report discussed the misconceptions of Christians in Islam.- An editorial commenting on the assassination of Theo van Gogh resulted in a debate in Dutch media about the limits of the freedom of expression.- An article calling on the western readers to be careful with Christian persecution stories from Egypt, they may be true but also may be rumours.-The Muslim World And The West; What Can Be Done To Reduce Tensions?-Text of a lecture for students and professors of different faculties at the University of Copenhagen, , about plans to establish the Center for Arab-West Understanding in Cairo, Egypt.- Escalations following the alleged conversion of A priest’s wife to IslamThe list of authors’ featurd in this dataset goes as follows:Cornelis Hulsman, Drs. , Wolfram Reiss, Rev. Dr. , John H. Watson, Kim Kwang-Chan, Dr. , Kamal Abu al-Majd, Fiona McCallum, Mary Picard , Jeff Adams, Dr., Rev., Jennie Marshall , Marcos Emil Mikhael, Usamah W. al-Ahwani, Sawsan Jabrah and Nirmin Fawzi, Hānī Labīb, George Carey (Lord), Rowan Williams, Lambeth Palace Press Office, H.G. Bishop Munir Hanna Anis Armanius, Eildert Mulder, Rīhām Saʿīd, Tharwat al-Kharabāwī, Geir Valle, Janique Blattman, Iqbal Barakah , Munā ʿUmar, Dieter Tewes, ʿAmr Asʿad Khalīl, Dr., Janique Blattmann, Vera Milackova, Tamir Shukri, and Christiane Paulus All reports are written in English, though some reports feature Arabic text or cite Arabic sources.
The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.
The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.
The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.
National coverage
Individual
Observation data/ratings [obs]
In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.
In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.
In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.
The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).
For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.
Sample size for Iran, Islamic Rep. is 1005.
Landline and mobile telephone
Questionnaires are available on the website.
Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.
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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.
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Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
The supply of labor available in an economy includes people who are employed, those who are unemployed but seeking work, and first-time job-seekers. Not everyone who works is included: unpaid workers, family workers, and students are often omitted, while some countries do not count members of the armed forces. Data on labor and employment are compiled by the International Labour Organization (ILO) from labor force surveys, censuses, establishment censuses and surveys, and administrative records such as employment exchange registers and unemployment insurance schemes.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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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%).
This dataset contains the Arab-West Report special reports that were published in 2007. This dataset mainly contains the writings of Cornelis Hulsman, Drs., among other authors on topics related to Muslim- Christian relations and interfaith dialogue. Additionally, this dataset features certain reports related to the Christian faith in Egypt, Monastic life and Coptic traditions.
Some of the articles address the media coverage of Muslim-Christian incidents and sectarian tensions, and how biased media reporting can often exacerbate existing tensions between groups. These articles feature a number of interviews conducted by Arab West Report with prominent social figures and scholars.
Additionally, reports from this dataset discuss conversion cases and interfaith meetings that were held at the time. This dataset also contains media critique from Arab West Report Editor-in-Chief Cornelis Hulsman, Drs.
Some of the themes that characterize this dataset include:
- Authors report on their trip to see the celebration of the Holy Family crossing the Nile River in a village in Upper Egypt. They reflect on their experiences and the need to improve dialogue between Muslims and Christians in Egypt.
- An overview of a forum organized by the Center for Civilizational Studies and Dialogue between Cultures at Cairo University to introduce a book written by Father Christian van Nispen, sj, entitled, ‘Christians and Muslims: Brothers before God.’ van Nispen’s principle argument is that both Muslims and Christians worship one and the same God, but according to different understandings.
- Another report highlighted the second conference on bias, entitled: ‘The International Conference for Dialogue between Civilizations and the Different Tracks of Knowledge.’ The 4-day conference, was sponsored by the Program for Civilizational Studies and Dialogue between Cultures at Cairo University, and the International Institute of Islamic Thought.
- The Arab West Report annual report: The Center for Arab-West Understanding presents its annual report for 2006.
Media critique:
- “Minister Of Awqaf Dr. Hamdi Zakzouk Falsely Accused Of Calling For The Death Penalty For Apostates From Islam”: Arab-West Report responds to media claims that Dr. Hamdi Zakzouk called for the death penalty for apostates from Islam.
-In another report, the authors stress that misguided media reporting often only serves to further tensions, particularly in cases of sectarian strife. Another article presents the transcript of a lecture for the Arab Thought Forum. It considers media distortions and mis-representation in the media that only serve to further antagonize Muslim-Christian relations and the perception of Islam / the Arab world in the West. Cornelis Hulsman, Drs., explains the role of the Center for Arab West Understanding, and the importance of constructive, unbiased, and fully researched journalism.
-Hulsman stressed in one of his articles that media frequently manipulate headlines in an effort to present stories in the context they desire. Headlines are also frequently sensationalized in an effort to attract a larger number of readers, but if this also distorts a story this should be questioned. Cornelis Hulsman, Drs., stresses the danger of ignorant media reporting, and the damage that inaccurate fact-checking can cause. He provides a number of examples from various intellectuals, commenting on stories that have been sensationalized in the media, and the negative effects this reporting had on Arab-West relations and on furthering dialogue between the Islamic and Arab world and the West.
Interviews:
-“An interview With Father Basilius About Father Matta Al-Maskin”: Father Basilius discusses the history and theological philosophies of Father Mattá al-Maskīn. The interview is mainly focused on theology and the practices of clergymen.
- An interview with Tarek Heggy at CIDT where Drs. Cornelis Hulsman and staff members discuss sensitive issues throughout the Arab world.
- An interview by AWR/ CIDT interns with Dr. Hala Mustafa, where she comments on her role in the National Democratic Party’s Policies Committee, her opinions on reform in Egypt, critiques the role of Egyptian security, and outlines the necessary steps needed for reform to take effect.
- “Saad Eddin Ibrahim Meets With CIDT Interns To Discuss How Islamists Have Changed”: Saad Eddin Ibrahim, is one of the most outspoken critics of the Egyptian government, who was imprisoned from 2000-2003 for his critique. Saad Eddin Ibrahim is a liberal secularist, but as a result of his strong democratic stance, he defends the rights of all groups in society, including Islamists, to participate in the politics of the country. CIDT-interns met with him for a talk about his life and his views.
-A review of the Annual Anglican-Al Azhar Interfaith Meeting Dialogue held in All-Saints Cathedral which implicitly...
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Recent issues on politics have been dominant in Indonesia that people are divided and become more intolerant of each other. Indonesia has the biggest Muslim population in the world and the role of Islam in Indonesian politics is significant. The current Indonesian government claim that moderate Muslims are loyal to the present political system while the opposing rivals who are often labelled’intolerant and radical Muslims’ by Indonesian mass media often disagree with the central interpretation of democracy in Indonesia. Studies on contributing factors and discourse strategies used in news and articles in secular and Islamic mass media which play a vital role in the construction of Muslim and Islamic identities in Indonesia are, therefore, recommended.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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Census 2021 data on religion by highest qualification level, by sex, by age, England and Wales combined. This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.
The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question.
Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.
This dataset shows population counts for usual residents aged 16 years and over. Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.
These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.
Quality notes can be found here
Quality information about Education can be found here
Religion
The 8 ‘tickbox’ religious groups are as follows:
No qualifications
No qualifications
Level 1
Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills
Level 2
5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma
Apprenticeship
Apprenticeship
Level 3
2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma
Level 4 +
Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)
Other
Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems. By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.
This dataset contains the Arab West Report special reports published in the year 2003. The majority of the material in this dataset focuses on in depth analysis of Muslim-Christian relations in Egypt, however, Judaism is also the subject of a great deal of analysis in these reports. A number of the reports address relations between religious minorities such as 'dhimmi' status, and the complex relationship between national identity and religious identity. A number of reports are also media critique, a staple of AWR’s work.
The AWR reports in this dataset also describe the early work of AWR, and introduce several of its early board members and affiliates. Authors include:
- Cornelis Hulsman, Drs.
- Sunni M. Khalid
- Jeff Adams (Dr. Rev.)
- Larry F. Levine (Dr.)
- Victor M. Ordonez
- Michael Reimer (Dr.)
- Wolfram Reiss, (Rev. Dr.)
- Johanna Pink (Dr.)
- Nirmīn Fawzī
- Hedda Klip
- Munīr Hannā Anīs Armanius (Bishop)
- Cassandra Chambliss
- Adam Hannestad
- David Weaver
- Konrad Knolle (Rev.)
- Usamah Wadi‘ al-Ahwani
- Marjam Van Oort
- Nawal al-Sa‘dawi
- M.E. van Gent
- Subhi ‘Uwaydah, (Rev. Dr.)
- Andreas Van Agt, (Dr.)
Institutional authors include AWR Editorial Board, AWR Board of Advisors, Center for the Study of Christianity in Islamic Lands (CSCIL), and EKD Presservice.
All reports are written in English, though some reports feature Arabic text or cite Arabic sources.
Team including job titles:
Sparks, MA M.R. (Center for Intercultural Dialogue and Translation (CIDT))
Adams, Rev.Dr. J. (Religious News Service from the Arab-World (RNSAW))
Levine, Dr. L.
Khalid, S.
Reimer, Dr. M. (American University in Cairo)
Ordonez, Dr. V.
Reiss, Rev. Dr. W.
Pink, Dr. J.
Fawzi, N. (Religious News Service from the Arab World (RNSAW))
Klip, Rev. H. (Swiss Reformed Church)
Hannā Anīs Armanius, Bishop M. (Episcopal Church)
Chambliss, C. (Intern-Center for Arab-West Understanding (CAWU))
Hannestad, A.
Weaver, D. (Church World Service, USA)
Knolle, Rev. K. (German Reformed Church in Cairo)
Al-Ahwani, U. (Religious News Service from the Arab-World (RNSAW))
Oort, M. Van (Roos Foundation)
Al-Sa'adawi, N.
Gent, M.E. Van
Uwaydah, Rev. Dr. S. (Coptic Evangelical Church Ismailia, Egypt)
van Agt, Dr. A.
EKD Press Service
Center for the Study of Christianity in Islamic Lands (CSCIL)
AWR Editorial Board
AWR Board of Advisors
Hulsman, Drs. C. Mr. (Center for Intercultural Dialogue and Translation
The Places of Worship dataset is composed of any type of building or portion of a building that is used, constructed, designed, or adapted to be used as a place for religious and spiritual activities. These facilities include, but are not limited to, the following types: chapels, churches, mosques, shrines, synagogues, and temples. The license free Large Protestant Churches, Mosques, Jewish Synagogues, and Roman Catholic Churches in Large Cities datasets were merged together to create the initial data for the Places of Worship dataset. Additional entities have been added from TGS research. This dataset contains Buddhist, Christian, Hindu, Islamic, Judaic, and Sikh places of worship. Unitarian places of worship have been included when a congregation from one of these religions meets at a church owned by a Unitarian congregation. Some Protestant denominations are not currently represented in this dataset. The Places of Worship dataset is not intended to include homes of religious leaders (unless they also serve as a place of organized worship), religious schools (unless they also serve as a place of organized worship for people other than those enrolled in the school), Jewish Mikvahs or Hillel facilities, and buildings that serve a purely administrative purpose. If a building's primary purpose is something other than worship (e.g., a community center, a public school), but a religious group uses the building for worship on a regular basis, it was included in this dataset if it otherwise met the criteria for inclusion. Convents and monasteries are included in this dataset, regardless of whether or not the facilities are open to the public, because religious services are regularly held at these locations. On 08/07/2007, TGS ceased making phone calls to verify information about religious locations. Therefore, most entities in this dataset were verified using alternative reference sources such as topographic maps, parcel maps, various sources of imagery, and internet research.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
We have built the Salat Postures Dataset from a set of images of students and laboratory members performing different Salat positions using mobile phones, from various view angles and with different brightness conditions, especially captured for the purpose, complemented with images (and video frames) of people in prayer collected from the Internet.
The total number of collected images is 1904 (file extensions: jpeg, jpg, png, PNG, mpo), which we manually labeled into four classes using rectangular bounding boxes. Each image is associated with an XML file with the same name, containing the class annotations and bounding box coordinates, following the Pascal VOC format. The four classes correspond to the four main positions in Islamic prayer:
Total instances: 2156
You may need a preprocessing step to rename some class names, since classes 'sitting'/'julus', and 'sujud'/'Sujud' appear with two different names/spellings.
If you use this dataset in your research, please cite:
Koubâa, A., Ammar, A., Benjdira, B., Al-Hadid, A., Kawaf, B., Al-Yahri, S.A., Babiker, A., Assaf, K. and Ras, M.B., 2020, March. Activity Monitoring of Islamic Prayer (Salat) Postures using Deep Learning. In 2020 6th Conference on Data Science and Machine Learning Applications (CDMA) (pp. 106-111). IEEE.
Available on arxiv.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
During the present time, COVID-19 situation is the topmost priority in our life. We are introducing a new dataset named Covid Face-Mask Monitoring Dataset which is based on Bangladesh perspective. We have a main concern to detect people who are using masks or not in the street. Furthermore, few people are not wearing masks properly which is harmful for other people and we have the intention to detect them also. Our proposed dataset contains 6,550 images and those images collected from the walking street, bus stop, street tea stall, foot-over bridge and so on. Among the full dataset, we selected 5,750 images for training purposes and 800 images for validation purposes. Our selected dimension is 1080 × 720 pixels for entire dataset. The percentage of validation data from the full dataset is almost 12.20%. We used a personal cell phone camera, DSLR for collecting frames and adding them into our final dataset. We have also planned to collect images from the mentioned place using an action camera or CCTV surveillance camera. But, from Bangladesh perspective it is not easy to collect clear and relevant data for research. To extend, CCTV surveillance cameras are mostly used in the university, shopping complex, hospital, school, college where using a mask is mandatory. But our goal of research is different. In addition, we want to mention that in our proposed dataset there are three classes which are 1. Mask, 2. No_mask, 3. Mask_not_in_position.
"Between October 2011 and November 2012, Pew Research Center, with generous funding from The Pew Charitable Trusts and the John Templeton Foundation, conducted a public opinion survey involving more than 30,000 face-to-face interviews in 26 countries in Africa, Asia, the Middle East and Europe. The survey asked people to describe their religious beliefs and practices, and sought to gauge respondents; knowledge of and attitudes toward other faiths. It aimed to assess levels of political and economic satisfaction, concerns about crime, corruption and extremism, positions on issues such as abortion and polygamy, and views of democracy, religious law and the place of women in society.
"Although the surveys were nationally representative in most countries, the primary goal of the survey was to gauge and compare beliefs and attitudes of Muslims. The findings for Muslim respondents are summarized in the Religion & Public Life Project's reports The World's Muslims: Unity and Diversity and The World's Muslims: Religion, Politics and Society, which are available at www.pewresearch.org. [...] This dataset only contains data for Muslim respondents in the countries surveyed. Please note that this codebook is meant as a guide to the dataset, and is not the survey questionnaire." (2012 Pew Religion Worlds Muslims Codebook)