{"status":"OK","data":{"id":410565,"identifier":"9EPVXF","persistentUrl":"https://doi.org/10.34894/9EPVXF","protocol":"doi","authority":"10.34894","separator":"/","publisher":"DataverseNL","publicationDate":"2024-03-08","storageIdentifier":"surf://10.34894/9EPVXF","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9999,"datasetType":"dataset","locks":[],"latestVersion":{"id":26105,"datasetId":410565,"datasetPersistentId":"doi:10.34894/9EPVXF","datasetType":"dataset","storageIdentifier":"surf://10.34894/9EPVXF","versionNumber":1,"internalVersionNumber":8,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"DRAFT","deaccessionLink":"","distributionDate":"2024-03-08","productionDate":"2020-05-01","lastUpdateTime":"2024-03-08T15:16:17Z","releaseTime":"2024-03-08T15:16:17Z","createTime":"2024-03-08T15:14:51Z","publicationDate":"2024-03-08","citationDate":"2024-03-08","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9999,"license":{"name":"CC0-1.0","uri":"http://creativecommons.org/publicdomain/zero/1.0","iconUri":"https://licensebuttons.net/p/zero/1.0/88x31.png","rightsIdentifier":"CC0-1.0","rightsIdentifierScheme":"SPDX","schemeUri":"https://spdx.org/licenses/","languageCode":"en"},"fileAccessRequest":true,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"Becoming a Minority Project International Survey"},{"typeName":"subtitle","multiple":false,"typeClass":"primitive","value":"BaM Survey"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Keskiner, Elif"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"vu.nl"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0002-3278-9830"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"Keskiner, Elif"},"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"vu.nl"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"The BaM Project initiates an international survey among people living in neighborhoods where everybody is a numerical minority. In the BaM survey we would like to find out how people engage with each other in these neighborhoods. Where do they send their children to school? Do they experience conflicts and if so, what are they about? What do people appreciate about the neighborhoods? With whom do they interact in the street, in the playground and who do they talk to when having a coffee in the local bars?\n\nFor the BaM survey we approached people without a migration background in the age between 25 and 45. Our respondents are selected because they are born in one of the five countries and both their parents are also born in that country. The BaM survey can be accessed with a personal code administered to the selected respondents, who will be asked to fill in a survey of about 20 minutes, on-line on a laptop or tablet. The questions address different aspects of living in a diverse neighborhood. The survey is anonymous; hence the names and the identities of the respondents will not be shared, and we will be respecting people’s privacy and personal opinions."},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2024-03-08"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Social Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Mixed neighbourhoods"}}]},{"typeName":"topicClassification","multiple":true,"typeClass":"compound","value":[{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Inter-ethnic relations"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Lazëri, Marina. \"Understanding minority feeling among people without a migration background: evidence from five majority-minority European cities.\" Journal of Ethnic and Migration Studies 49.8 (2023): 1977-1995."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182550"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182550"}},{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Lazëri, M., & Coenders, M. (2023). Dutch national identity in a majority-minority context: when the dominant group becomes a local minority. Journal of Ethnic and Migration Studies, 49(9), 2129-2153."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2022.2104698"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2022.2104698"}},{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Crul, M., Lelie, F., & Song, M. (2023). The bi-directional impact of a mixed union. People without a migration background in a union with a partner with a migration background. Journal of Ethnic and Migration Studies, 49(8), 1996-2013."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182551"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182551"}},{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Crul, M., & Lelie, F. (2021). Measuring the impact of diversity attitudes and practices of people without migration background on inclusion and exclusion in ethnically diverse contexts. Introducing the diversity attitudes and practices impact scales. Ethnic and Racial Studies, 44(13), 2350-2379."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182551"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182551"}},{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Knipprath, K. (2023). From culturalisation to individuation: the role of urban spaces in shaping intergroup contacts and symbolic boundary perceptions. Journal of Ethnic and Migration Studies, 49(8), 2014-2033."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182552"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1080/1369183X.2023.2182552"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"Appendices\n\n1. Details sampling BaM survey: neighborhood selection and sampling\n\n1.1. Amsterdam\n\nThe city of Amsterdam is divided up into 7 city districts, 22 city areas, 99 neighbourhoods and 481 smaller units. The neighbourhood level (which the municipality calls ‘wijken’) was used in the sampling process. Out of the 99 neighbourhoods, 12 have less than 2.000 inhabitants and were therefore excluded from the sampling. Out of the remaining 87 neighbourhoods, 42 are majority minority neighbourhoods (MMN), which were all included in the sampling.\n\nThe municipal register (Basisregistratie Personen, BRP) was used to conduct the sampling. This was done by the research department of Amsterdam (OIS) on the basis of the composition of the population as of March/ April 2019. In total a sample of 2.000 inhabitants was selected with an equal number of persons per majority minority neighbourhood. It is important to note that only one person per independent domicile could be selected.\n\nTo ensure that only individuals, who fit the BaM project definition of ‘no migration background’ participate in the study, at the beginning of the survey in all cities all respondents were screened by asking about their birthplace and the birthplace of their parents. Those who did not fit the study’s target group were excluded from the remainder of the questionnaire.\n\n1.2. Rotterdam\n\nRotterdam, the other Dutch city in the BaM survey, is divided into 15 areas and 86 neighbourhoods. Here too the neighbourhood level was used in the sampling process. Out of the 86 neighbourhoods, 23 have less than 2.000 inhabitants and were therefore excluded from the sampling. Out of the remaining 63 neighbourhoods, 35 are sampled in the BAM survey as MMN.\n\nThe municipal register (Basisregistratie Personen, BRP) was used to conduct the sampling. This was done by the research department of Rotterdam (OBI) on the basis of the composition of the population as of March/ April 2019. In total a sample of 2.000 inhabitants was selected with an equal number of persons per neighbourhood. Again, one person per independent domicile could be selected.\n\n1.3. Antwerp\n\nAntwerp is divided into 9 districts, 70 neighbourhoods and 298 smaller units. The neighbourhood level was used in the sampling process. Out of the 70 neighbourhoods, 14 have less than 2.000 inhabitants and were therefore excluded from the sampling. Out of the remaining 56 neighbourhoods, 27 are sampled as MMN.\n\nThe city of Antwerp does not provide data on the country of birth. The city however does provide figures on the nationality of the person, or on their first nationality and the nationality or the parents. This is done as in the following order: 1. First nationality of the father; 2. First nationality of the mother; 3. First nationality of the person; 4. Current nationality of the person. If all four nationalities are Belgian, the person is labelled as having no migration background (in Flemish ‘autochtoon’). As this definition might lead to an underestimation of the population with migration background3, we considered neighbourhoods where more than 45% (rather than 50%) of the population is defined as ‘allochtoon’ as MMN in Antwerp and also included them in the sampling.\n\nData from the Belgian postal company Bpost was used to conduct the sampling. This was done by the fieldwork bureau DESAN. In total a sample of 3.000 inhabitants was selected. DESAN acquired lists of names, addresses and age of people living in the selected neighbourhoods from the Belgian postal company Bpost. It then applied onomastic sampling (i.e. they selected Belgian sounding names) to the file obtained to isolate persons without migration background. DESAN has extensive experience with this and estimates that onomastic method applied is valid for 90% of the records. The selected respondents were first screened if they belonged to our target group.\n\n1.4. Malmö\n\nMalmö is divided into 5 city areas, 10 city parts, and 135 subareas (neighbourhoods). The subarea (neighbourhood) level was used in the sampling process since it was more comparable to the area levels in the other cities. Out of the 135 neighbourhoods, 73 had less than 2000 inhabitants and were therefore excluded from the sampling. Out of the remaining 62 neighbourhoods, 33 are MMN and are sampled.\n\nIt is important to note that the Swedish definition of migration background deviates from the BaM one, i.e. in Sweden a person has a migration background if they were born abroad or had two parents that were born abroad (compared to the definition used in the BaM project, in which a person is considered to have a migration background if they were born abroad or at least one of their parents were born abroad). We based the neighbourhood selection on the Swedish definition, as that was the available data. As this definition might lead to an underestimation of the population with migration background, we also considered neighbourhoods where more than 40% (rather than 50%) of the population is defined as having a migration background as MMN in Malmö. Data collection provider Norstat used data provided by Itesco to conduct the sampling. In total a sample of 8500 inhabitants was selected in two sampling rounds. The sample file contained the following information: name, address, age and neighbourhood. Initially Norstat purchased a sample from a database provided by Itesco that covers addresses and phone numbers of about 80% of the Swedish population. Using this database, Norstat first conducted onomastic sampling (i.e. they selected Swedish sounding names) and then selected individuals between 25 and 45 years of age. The first sampling round only considered individuals living in neighbourhoods that in 2017 (i) had more than 2000 inhabitants, and (ii) had more than 50% of inhabitants with a migration background (according to the official Swedish definition). This step resulted in the selection of 5000 names in 24 neighbourhoods. Given that Sweden uses a less strict definition of migration background than we do in the BaM project (see neighborhood selection) which might result in an underestimation of the population with a migration background, we also initiated a second sampling round in September 2019. We did this in neighborhoods in which 40-49% of the inhabitants had a migration background according to the official Swedish definition (an additional 9 neighborhoods). The same sampling procedure as during the first round was used, and approximately 3500 people were selected. To ensure that only individuals, who fit the BaM project definition of ‘no migration background’ participate in the study, Norstat screened the respondents at the beginning of the survey by asking about their birthplace and the birthplace of their parents. Those who did not fit the study’s target group were excluded from the remainder of the questionnaire. This strategy is in fact applied to all the fieldworks we have conducted in other cities.\n\n1.5. Vienna\n\nVienna is divided into 23 districts (‘Bezirke’), 250 Zählbezirke, and 1364 smaller units, called the Zählsprengel. The Zählbezirke level (which is comparable to the neighbourhood level) was used in the sampling process. It is important to note, that on the Zählbezirk-level, the city of Vienna provides information about the migration background of the inhabitants (‘ausländische Herkunft’) based on nationality or country of birth. According to this definition, Zählbezirke in Vienna that have 50% or more people with a migration background fall into the sample population of the BaM survey. Out of the 250 Zählbezirke, 32 are MMN and they were all used for sampling.\n\nData was collected by the fieldwork bureau IFES through random walks (285 responses, CAPI, 71%) and online interviews (115 responses, CAWI, 29%) in majority minority neighborhoods. Within a larger Zählbezirk only majority-minority sub-levels of Zählbezirke, so-called Zählsprengel, were considered for the random walks. The selected respondents out of the random walks were screened if they belonged to our target group.\n\n1.6. Hamburg\n\nHamburg is divided into seven city areas (Bezirke), 104 city parts (Stadtteile) and 943 statistical areas. For the project, only people without a migration background were to be interviewed in neighborhoods in which a high proportion of the population has a migration background. 15 city districts were selected for this purpose.\n\nData was collected by the fieldwork bureau Infas. Infas was given 9944 address entries from the statistical office in Hamburg. In the study, only people without migration background were included. The address entries provided to Infas were subjected to a classification procedure to determine whether the person in question had a migration background. For this purpose, the proven onomastic procedure was used. For each combination of name and first name, linguistic and static procedures are used to determine whether a migration background can be assumed or not. As a result of this procedure a migration background could be assumed for 21.2 percent of the gross sample. These cases were removed from the sample. Thus, 7839 cases were available for the field operation. A sample of 5183 cases was randomly drawn from these 7839 cases. The selected respondents were first screened if they belonged to our target group.\n\n2. Fieldwork\n\n2.1. Amsterdam\n\nThe fieldwork was conducted by OIS, the department for research, information and statistics of the municipality of Amsterdam. In total 422 responses were collected.\n\nIn the first step, the persons in the selected sample received an invitation letter to participate in the survey with a link to the online questionnaire and a personal password. Then, two weeks after the first letter, the persons who had not filled in the online questionnaire received a printed questionnaire with a reminder to participate in the survey. Two weeks after that, out of those who had not filled in the questionnaire, potential respondents were selected from neighbourhoods in which the response rates were low, taking age groups and gender into account. Interviewers then conducted home visits to approach these persons and offer them the possibility to fill in the questionnaire face-to-face.\n\n2.2. Rotterdam\n\nThe fieldwork was conducted by the fieldwork agency DESAN. In total 428 responses were collected.\n\nThe same scenario as in Amsterdam was followed, however, the potential respondents selected from neighbourhoods in which the response rates were low were either invited to fill in the questionnaire through a telephone survey (which was possible as the data files was enriched with telephone numbers by the company EDM) or the interviewers conducted home visits and offered the respondents the possibility to participate in a face-to-face survey.\n\n2.3. Antwerp\n\nThe fieldwork is conducted by the fieldwork agency DESAN. In total 646 responses were collected.\n\nThe exact same scenario as in Rotterdam was employed in Antwerp.\n\n2.4. Malmö\n\nThe fieldwork is conducted by the data collection provider Norstat. In total 561 responses were collected.\n\nIn the first part of the sampling the aim was to have about 17 respondents per neighbourhood (which, given the 24 neighbourhoods, would give a total of approx. 400 respondents), with a minimum of 10 respondents in neighbourhoods with a lower proportion and absolute number of our target group.\n\nIn the first step, Norstat sent postcards with an invitation to participate in the survey to all 5000 addresses, with an incentive of a value of 90 SEK (approximately 9 Euros). The postcard contained a link through which respondents could fill in the survey online. In the second step, Norstat sent text message reminders to those that had not responded two weeks after the postcards were sent. In total, Norstat sent out 2140 text message reminders. In the third step, approximately one week after the text message reminders, Norstat commenced phone interviews, focusing on neighbourhoods where the lowest desired target of respondents (10) was not reached and in particular on neighbourhoods with an especially low response rate (under 5 respondents). This resampling yielded 188 new names.\n\nIn the second part of the sampling, the aim was to collect 10 interviews per area, giving a total of 90 responses. As a first step Norstat sent out text messages including a link to the study. A reminder was sent out to those that had not answered after a week. After three weeks, the text messages were followed up by telephone interviews, conducted only in areas with less than 10 respondents.\n\n2.5. Vienna\n\nThe fieldwork is conducted by the market research and social research institute IFES. In total 400 responses were collected.\n\nIn the first step, interviewers were given maps with the boundaries of the selected Zählsprengel, including a fixed starting point and walking instructions. They were also required to conduct only one interview per household, and a maximum of 15 interviews per Zählsprengel. The random walks had to take place at different times of the day and on different days of the week. Then, the interviewers screened for suitable target groups in the households. If the screening was successful, the target person was given the invitation letter to the study, on which the web link to the survey was printed. The person was free to complete the face-to-face interview or the questionnaire online.\n\n2.6. Hamburg\n\nIndividuals in the sample received a cover letter and a privacy sheet. The cover letter explained the purpose of the study. The cover letter further contained the link to the online questionnaire and the access password. The privacy sheet explained the legality of the procedure and data protection. The initial mailing of the letters took place on 19.05.2020. A reminder was sent two weeks later.\n\nAt the end of the study, 694 individuals had participated in the study. Onomastics reduced the number of respondents. Just under 14 percent (114 out of 808) of the participants were not in the target group of persons without an immigrant background."},{"typeName":"language","multiple":true,"typeClass":"controlledVocabulary","value":["English"]},{"typeName":"producer","multiple":true,"typeClass":"compound","value":[{"producerName":{"typeName":"producerName","multiple":false,"typeClass":"primitive","value":"BaM Project"},"producerAffiliation":{"typeName":"producerAffiliation","multiple":false,"typeClass":"primitive","value":"Vrije Universiteit Amsterdam"},"producerAbbreviation":{"typeName":"producerAbbreviation","multiple":false,"typeClass":"primitive","value":"BaM"},"producerURL":{"typeName":"producerURL","multiple":false,"typeClass":"primitive","value":"https://bamproject.eu/survey"},"producerLogoURL":{"typeName":"producerLogoURL","multiple":false,"typeClass":"primitive","value":"https://bamproject.eu/survey"}}]},{"typeName":"productionDate","multiple":false,"typeClass":"primitive","value":"2020-05-01"},{"typeName":"productionPlace","multiple":true,"typeClass":"primitive","value":["Amsterdam"]},{"typeName":"contributor","multiple":true,"typeClass":"compound","value":[{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Project Leader"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Crul, Maurice"}}]},{"typeName":"grantNumber","multiple":true,"typeClass":"compound","value":[{"grantNumberAgency":{"typeName":"grantNumberAgency","multiple":false,"typeClass":"primitive","value":"ERC"},"grantNumberValue":{"typeName":"grantNumberValue","multiple":false,"typeClass":"primitive","value":"Research Council (ERC) Advanced Grant 741532."}}]},{"typeName":"distributor","multiple":true,"typeClass":"compound","value":[{"distributorName":{"typeName":"distributorName","multiple":false,"typeClass":"primitive","value":"Crul, Maurice"},"distributorAffiliation":{"typeName":"distributorAffiliation","multiple":false,"typeClass":"primitive","value":"Vrije Universiteit Amsterdam"},"distributorAbbreviation":{"typeName":"distributorAbbreviation","multiple":false,"typeClass":"primitive","value":"BaM Project"},"distributorURL":{"typeName":"distributorURL","multiple":false,"typeClass":"primitive","value":"https://bamproject.eu/survey"},"distributorLogoURL":{"typeName":"distributorLogoURL","multiple":false,"typeClass":"primitive","value":"https://bamproject.eu/survey"}}]},{"typeName":"distributionDate","multiple":false,"typeClass":"primitive","value":"2024-03-08"},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Keskiner, Elif"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2024-03-08"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2019-03-01"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2020-07-01"}}]},{"typeName":"dateOfCollection","multiple":true,"typeClass":"compound","value":[{"dateOfCollectionStart":{"typeName":"dateOfCollectionStart","multiple":false,"typeClass":"primitive","value":"2019-03-01"},"dateOfCollectionEnd":{"typeName":"dateOfCollectionEnd","multiple":false,"typeClass":"primitive","value":"2020-07-01"}}]},{"typeName":"kindOfData","multiple":true,"typeClass":"primitive","value":["Survey Data"]},{"typeName":"relatedMaterial","multiple":true,"typeClass":"primitive","value":["Appendices\n\n1. Details sampling BaM survey: neighborhood selection and sampling\n\n1.1. Amsterdam\n\nThe city of Amsterdam is divided up into 7 city districts, 22 city areas, 99 neighbourhoods and 481 smaller units. The neighbourhood level (which the municipality calls ‘wijken’) was used in the sampling process. Out of the 99 neighbourhoods, 12 have less than 2.000 inhabitants and were therefore excluded from the sampling. Out of the remaining 87 neighbourhoods, 42 are majority minority neighbourhoods (MMN), which were all included in the sampling.\n\nThe municipal register (Basisregistratie Personen, BRP) was used to conduct the sampling. This was done by the research department of Amsterdam (OIS) on the basis of the composition of the population as of March/ April 2019. In total a sample of 2.000 inhabitants was selected with an equal number of persons per majority minority neighbourhood. It is important to note that only one person per independent domicile could be selected.\n\nTo ensure that only individuals, who fit the BaM project definition of ‘no migration background’ participate in the study, at the beginning of the survey in all cities all respondents were screened by asking about their birthplace and the birthplace of their parents. Those who did not fit the study’s target group were excluded from the remainder of the questionnaire.\n\n1.2. Rotterdam\n\nRotterdam, the other Dutch city in the BaM survey, is divided into 15 areas and 86 neighbourhoods. Here too the neighbourhood level was used in the sampling process. Out of the 86 neighbourhoods, 23 have less than 2.000 inhabitants and were therefore excluded from the sampling. Out of the remaining 63 neighbourhoods, 35 are sampled in the BAM survey as MMN.\n\nThe municipal register (Basisregistratie Personen, BRP) was used to conduct the sampling. This was done by the research department of Rotterdam (OBI) on the basis of the composition of the population as of March/ April 2019. In total a sample of 2.000 inhabitants was selected with an equal number of persons per neighbourhood. Again, one person per independent domicile could be selected.\n\n1.3. Antwerp\n\nAntwerp is divided into 9 districts, 70 neighbourhoods and 298 smaller units. The neighbourhood level was used in the sampling process. Out of the 70 neighbourhoods, 14 have less than 2.000 inhabitants and were therefore excluded from the sampling. Out of the remaining 56 neighbourhoods, 27 are sampled as MMN.\n\nThe city of Antwerp does not provide data on the country of birth. The city however does provide figures on the nationality of the person, or on their first nationality and the nationality or the parents. This is done as in the following order: 1. First nationality of the father; 2. First nationality of the mother; 3. First nationality of the person; 4. Current nationality of the person. If all four nationalities are Belgian, the person is labelled as having no migration background (in Flemish ‘autochtoon’). As this definition might lead to an underestimation of the population with migration background3, we considered neighbourhoods where more than 45% (rather than 50%) of the population is defined as ‘allochtoon’ as MMN in Antwerp and also included them in the sampling.\n\nData from the Belgian postal company Bpost was used to conduct the sampling. This was done by the fieldwork bureau DESAN. In total a sample of 3.000 inhabitants was selected. DESAN acquired lists of names, addresses and age of people living in the selected neighbourhoods from the Belgian postal company Bpost. It then applied onomastic sampling (i.e. they selected Belgian sounding names) to the file obtained to isolate persons without migration background. DESAN has extensive experience with this and estimates that onomastic method applied is valid for 90% of the records. The selected respondents were first screened if they belonged to our target group.\n\n1.4. Malmö\n\nMalmö is divided into 5 city areas, 10 city parts, and 135 subareas (neighbourhoods). The subarea (neighbourhood) level was used in the sampling process since it was more comparable to the area levels in the other cities. Out of the 135 neighbourhoods, 73 had less than 2000 inhabitants and were therefore excluded from the sampling. Out of the remaining 62 neighbourhoods, 33 are MMN and are sampled.\n\nIt is important to note that the Swedish definition of migration background deviates from the BaM one, i.e. in Sweden a person has a migration background if they were born abroad or had two parents that were born abroad (compared to the definition used in the BaM project, in which a person is considered to have a migration background if they were born abroad or at least one of their parents were born abroad). We based the neighbourhood selection on the Swedish definition, as that was the available data. As this definition might lead to an underestimation of the population with migration background, we also considered neighbourhoods where more than 40% (rather than 50%) of the population is defined as having a migration background as MMN in Malmö. Data collection provider Norstat used data provided by Itesco to conduct the sampling. In total a sample of 8500 inhabitants was selected in two sampling rounds. The sample file contained the following information: name, address, age and neighbourhood. Initially Norstat purchased a sample from a database provided by Itesco that covers addresses and phone numbers of about 80% of the Swedish population. Using this database, Norstat first conducted onomastic sampling (i.e. they selected Swedish sounding names) and then selected individuals between 25 and 45 years of age. The first sampling round only considered individuals living in neighbourhoods that in 2017 (i) had more than 2000 inhabitants, and (ii) had more than 50% of inhabitants with a migration background (according to the official Swedish definition). This step resulted in the selection of 5000 names in 24 neighbourhoods. Given that Sweden uses a less strict definition of migration background than we do in the BaM project (see neighborhood selection) which might result in an underestimation of the population with a migration background, we also initiated a second sampling round in September 2019. We did this in neighborhoods in which 40-49% of the inhabitants had a migration background according to the official Swedish definition (an additional 9 neighborhoods). The same sampling procedure as during the first round was used, and approximately 3500 people were selected. To ensure that only individuals, who fit the BaM project definition of ‘no migration background’ participate in the study, Norstat screened the respondents at the beginning of the survey by asking about their birthplace and the birthplace of their parents. Those who did not fit the study’s target group were excluded from the remainder of the questionnaire. This strategy is in fact applied to all the fieldworks we have conducted in other cities.\n\n1.5. Vienna\n\nVienna is divided into 23 districts (‘Bezirke’), 250 Zählbezirke, and 1364 smaller units, called the Zählsprengel. The Zählbezirke level (which is comparable to the neighbourhood level) was used in the sampling process. It is important to note, that on the Zählbezirk-level, the city of Vienna provides information about the migration background of the inhabitants (‘ausländische Herkunft’) based on nationality or country of birth. According to this definition, Zählbezirke in Vienna that have 50% or more people with a migration background fall into the sample population of the BaM survey. Out of the 250 Zählbezirke, 32 are MMN and they were all used for sampling.\n\nData was collected by the fieldwork bureau IFES through random walks (285 responses, CAPI, 71%) and online interviews (115 responses, CAWI, 29%) in majority minority neighborhoods. Within a larger Zählbezirk only majority-minority sub-levels of Zählbezirke, so-called Zählsprengel, were considered for the random walks. The selected respondents out of the random walks were screened if they belonged to our target group.\n\n1.6. Hamburg\n\nHamburg is divided into seven city areas (Bezirke), 104 city parts (Stadtteile) and 943 statistical areas. For the project, only people without a migration background were to be interviewed in neighborhoods in which a high proportion of the population has a migration background. 15 city districts were selected for this purpose.\n\nData was collected by the fieldwork bureau Infas. Infas was given 9944 address entries from the statistical office in Hamburg. In the study, only people without migration background were included. The address entries provided to Infas were subjected to a classification procedure to determine whether the person in question had a migration background. For this purpose, the proven onomastic procedure was used. For each combination of name and first name, linguistic and static procedures are used to determine whether a migration background can be assumed or not. As a result of this procedure a migration background could be assumed for 21.2 percent of the gross sample. These cases were removed from the sample. Thus, 7839 cases were available for the field operation. A sample of 5183 cases was randomly drawn from these 7839 cases. The selected respondents were first screened if they belonged to our target group.\n\n2. Fieldwork\n\n2.1. Amsterdam\n\nThe fieldwork was conducted by OIS, the department for research, information and statistics of the municipality of Amsterdam. In total 422 responses were collected.\n\nIn the first step, the persons in the selected sample received an invitation letter to participate in the survey with a link to the online questionnaire and a personal password. Then, two weeks after the first letter, the persons who had not filled in the online questionnaire received a printed questionnaire with a reminder to participate in the survey. Two weeks after that, out of those who had not filled in the questionnaire, potential respondents were selected from neighbourhoods in which the response rates were low, taking age groups and gender into account. Interviewers then conducted home visits to approach these persons and offer them the possibility to fill in the questionnaire face-to-face.\n\n2.2. Rotterdam\n\nThe fieldwork was conducted by the fieldwork agency DESAN. In total 428 responses were collected.\n\nThe same scenario as in Amsterdam was followed, however, the potential respondents selected from neighbourhoods in which the response rates were low were either invited to fill in the questionnaire through a telephone survey (which was possible as the data files was enriched with telephone numbers by the company EDM) or the interviewers conducted home visits and offered the respondents the possibility to participate in a face-to-face survey.\n\n2.3. Antwerp\n\nThe fieldwork is conducted by the fieldwork agency DESAN. In total 646 responses were collected.\n\nThe exact same scenario as in Rotterdam was employed in Antwerp.\n\n2.4. Malmö\n\nThe fieldwork is conducted by the data collection provider Norstat. In total 561 responses were collected.\n\nIn the first part of the sampling the aim was to have about 17 respondents per neighbourhood (which, given the 24 neighbourhoods, would give a total of approx. 400 respondents), with a minimum of 10 respondents in neighbourhoods with a lower proportion and absolute number of our target group.\n\nIn the first step, Norstat sent postcards with an invitation to participate in the survey to all 5000 addresses, with an incentive of a value of 90 SEK (approximately 9 Euros). The postcard contained a link through which respondents could fill in the survey online. In the second step, Norstat sent text message reminders to those that had not responded two weeks after the postcards were sent. In total, Norstat sent out 2140 text message reminders. In the third step, approximately one week after the text message reminders, Norstat commenced phone interviews, focusing on neighbourhoods where the lowest desired target of respondents (10) was not reached and in particular on neighbourhoods with an especially low response rate (under 5 respondents). This resampling yielded 188 new names.\n\nIn the second part of the sampling, the aim was to collect 10 interviews per area, giving a total of 90 responses. As a first step Norstat sent out text messages including a link to the study. A reminder was sent out to those that had not answered after a week. After three weeks, the text messages were followed up by telephone interviews, conducted only in areas with less than 10 respondents.\n\n2.5. Vienna\n\nThe fieldwork is conducted by the market research and social research institute IFES. In total 400 responses were collected.\n\nIn the first step, interviewers were given maps with the boundaries of the selected Zählsprengel, including a fixed starting point and walking instructions. They were also required to conduct only one interview per household, and a maximum of 15 interviews per Zählsprengel. The random walks had to take place at different times of the day and on different days of the week. Then, the interviewers screened for suitable target groups in the households. If the screening was successful, the target person was given the invitation letter to the study, on which the web link to the survey was printed. The person was free to complete the face-to-face interview or the questionnaire online.\n\n2.6. Hamburg\n\nIndividuals in the sample received a cover letter and a privacy sheet. The cover letter explained the purpose of the study. The cover letter further contained the link to the online questionnaire and the access password. The privacy sheet explained the legality of the procedure and data protection. The initial mailing of the letters took place on 19.05.2020. A reminder was sent two weeks later.\n\nAt the end of the study, 694 individuals had participated in the study. Onomastics reduced the number of respondents. Just under 14 percent (114 out of 808) of the participants were not in the target group of persons without an immigrant background."]}]},"dansDataVaultMetadata":{"displayName":"Data Vault Metadata","name":"dansDataVaultMetadata","fields":[{"typeName":"dansDataversePid","multiple":false,"typeClass":"primitive","value":"doi:10.34894/9EPVXF"},{"typeName":"dansDataversePidVersion","multiple":false,"typeClass":"primitive","value":"1.0"},{"typeName":"dansBagId","multiple":false,"typeClass":"primitive","value":"urn:uuid:bec85770-f70e-485a-8703-69358c66b45f"},{"typeName":"dansNbn","multiple":false,"typeClass":"primitive","value":"urn:nbn:nl:ui:13-a5621aa7-390a-457c-911e-058696551dc3"}]}},"files":[{"label":"bam_survey.sav","restricted":false,"version":1,"datasetVersionId":26105,"dataFile":{"id":410566,"persistentId":"","filename":"bam_survey.sav","contentType":"application/x-spss-sav","friendlyType":"SPSS Binary","filesize":47787611,"storageIdentifier":"surf://store:18e1ea17bff-1bf93d4fa952","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"9ec511d886b6721c6ade586b48f5a13c25f26ca6"},"tabularData":false,"creationDate":"2024-03-08","publicationDate":"2024-03-08","lastUpdateTime":"2024-03-08T15:16:17Z","fileAccessRequest":true}}]}}}