{"status":"OK","data":{"id":209645,"identifier":"SS/PWKZME","persistentUrl":"https://doi.org/10.17026/SS/PWKZME","protocol":"doi","authority":"10.17026","separator":"/","publisher":"DANS Data Station Social Sciences and Humanities","publicationDate":"2024-01-18","storageIdentifier":"surf://10.17026/SS/PWKZME","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9983,"datasetType":"dataset","locks":[],"latestVersion":{"id":24096,"datasetId":209645,"datasetPersistentId":"doi:10.17026/SS/PWKZME","datasetType":"dataset","storageIdentifier":"surf://10.17026/SS/PWKZME","versionNumber":4,"internalVersionNumber":25,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","deaccessionLink":"","distributionDate":"2024-12-31","productionDate":"2023-12-01","UNF":"UNF:6:Va44JbwYM4K7in44/Pwecg==","lastUpdateTime":"2025-01-06T12:41:19Z","releaseTime":"2025-01-06T12:41:19Z","createTime":"2024-12-23T09:42:20Z","publicationDate":"2024-01-18","citationDate":"2024-01-18","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9983,"license":{"name":"CC-BY-4.0","uri":"http://creativecommons.org/licenses/by/4.0","iconUri":"https://licensebuttons.net/l/by/4.0/88x31.png"},"fileAccessRequest":true,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"Database of perceived cause-effect relations in migration aspirations and decisions"},{"typeName":"subtitle","multiple":false,"typeClass":"primitive","value":"Using Fuzzy Cognitive Mapping (FCM) to elicit migration-decision contexts in Ethiopia, Kenya, and Ghana"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"D. Reckien"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Faculty of Geo-Information Science and Earth Observation"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"0000-0002-1145-9509"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"R. Keeton"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Faculty of Geo-Information and Earth Observation, University of Twente"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"0000-0002-3550-1310"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"M. Abu"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"University of Ghana"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"0000-0002-6455-0162"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"E. Gurmu"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Addis Ababa University"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"0000-0001-7487-0058"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"J. Owour"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Samuel Hall"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"Faculty of Geo-Information Science and Earth Observation(ITC), University of Twente"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"The following database of perceived cause-effect relations in migration decisions brings together insights in the form of Fuzzy Cognitive Maps (FCMs) from both sending and receiving sites in Ethiopia, Kenya, and Ghana. Collected as part of the H2020 EU-funded HABITABLE project under grant agreement No. 869395, this dataset was jointly collected and developed by partners from the University of Twente, Addis Ababa University, Samuel Hall, and the University of Ghana. See https://habitableproject.org for more information on the project.\n \nThis dataset documents the role of perceptions of (changing) environmental and socioeconomic factors and how these have influenced migration decisions among rural households (sending location) and urban migrants (receiving location). The database consists of 320 translated, digitized, cleaned, and coded individual FCMs in the form of adjacency matrices. Data was collected between May 2022 – August 2023 as hand-drawn FCM networks in the following locations: Ethiopia (Adama/ Jima and Addis Ababa), Kenya (Kathyaka and Mombasa), and Ghana (Tolon and Tema, Accra). \n\nIn each location, data was collected on local affected populations' perceptions of an array of drivers of migration, such as social, economic, political and environmental conditions (e.g. climatic variability and change, land degradation), in the sending and receiving areas in order to determine the relationship between migration, environmental change and other factors as perceived by those affected. \n\nThe interview script developed for this study was framed around the question: “What caused you / your household member to decide to move?” This central question provided the basis for the development of the weighted causal networks (FCMs) of factors influencing the decision to migrate. Enumerators were provided with a script including the follow-up probing questions “What other reasons / causes / factors influenced the decision to move?” and “Was there a final trigger or event that influenced this decision?” The interview process began with the enumerators noting the concepts related by the respondent on paper, followed by a second part where the respondent was asked to draw directional relationships among these concepts and, finally, to give the relationships weighted values. This was explained in layman’s terms to the respondent. Finally, the respondent was asked to check the resulting FCM network and make any changes they deem appropriate.   \n\nA more detailed description is provided in the metadata file \"D2.1_FCM_database_descriptor_V3.pdf\"."}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Social Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Fuzzy Cognitive Mapping"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Climate migration"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Environmental migration"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Migration decision-making"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Climate mobilities"}}]},{"typeName":"language","multiple":true,"typeClass":"controlledVocabulary","value":["English"]},{"typeName":"producer","multiple":true,"typeClass":"compound","value":[{"producerName":{"typeName":"producerName","multiple":false,"typeClass":"primitive","value":"Habitable project"},"producerAffiliation":{"typeName":"producerAffiliation","multiple":false,"typeClass":"primitive","value":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente"},"producerURL":{"typeName":"producerURL","multiple":false,"typeClass":"primitive","value":"https://habitableproject.org"}}]},{"typeName":"productionDate","multiple":false,"typeClass":"primitive","value":"2023-12-01"},{"typeName":"productionPlace","multiple":true,"typeClass":"primitive","value":["Ethiopia","Kenya","Ghana","Thailand","Mali"]},{"typeName":"grantNumber","multiple":true,"typeClass":"compound","value":[{"grantNumberAgency":{"typeName":"grantNumberAgency","multiple":false,"typeClass":"primitive","value":"European Union"},"grantNumberValue":{"typeName":"grantNumberValue","multiple":false,"typeClass":"primitive","value":"Grant agreement No. 869395"}}]},{"typeName":"distributionDate","multiple":false,"typeClass":"primitive","value":"2024-12-31"},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Reckien, Diana"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2024-01-11"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2013-01-01"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2023-08-31"}}]},{"typeName":"dateOfCollection","multiple":true,"typeClass":"compound","value":[{"dateOfCollectionStart":{"typeName":"dateOfCollectionStart","multiple":false,"typeClass":"primitive","value":"2022-05-01"},"dateOfCollectionEnd":{"typeName":"dateOfCollectionEnd","multiple":false,"typeClass":"primitive","value":"2023-08-31"}}]},{"typeName":"kindOfData","multiple":true,"typeClass":"primitive","value":["Fuzzy Cognitive Maps (FCMs) as adjacency matrices"]},{"typeName":"series","multiple":true,"typeClass":"compound","value":[{"seriesInformation":{"typeName":"seriesInformation","multiple":false,"typeClass":"primitive","value":"Fuzzy Cognitive Maps (FCMs) of individual respondents/ migrant or household member of migrant"}}]}]},"dansRights":{"displayName":"Rights Metadata","name":"dansRights","fields":[{"typeName":"dansRightsHolder","multiple":true,"typeClass":"primitive","value":["Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente"]},{"typeName":"dansPersonalDataPresent","multiple":false,"typeClass":"controlledVocabulary","value":"No"},{"typeName":"dansMetadataLanguage","multiple":true,"typeClass":"controlledVocabulary","value":["English"]}]},"dansRelationMetadata":{"displayName":"Relation Metadata","name":"dansRelationMetadata","fields":[{"typeName":"dansAudience","multiple":true,"typeClass":"primitive","value":["https://www.narcis.nl/classification/E14000","https://www.narcis.nl/classification/E15000"],"expandedvalue":[{"@id":"https://www.narcis.nl/classification/E14000","termName":[{"lang":"nl","value":"Migratie, etnische relaties en multiculturaliteit"},{"lang":"en","value":"Migration, ethnic relations and multiculturalism"}],"vocabularyUri":"https://www.narcis.nl/classification/"},{"@id":"https://www.narcis.nl/classification/E15000","termName":[{"lang":"en","value":"Environmental studies"},{"lang":"nl","value":"Milieustudies"}],"vocabularyUri":"https://www.narcis.nl/classification/"}]}]},"dansSocialSciences":{"displayName":"Social Sciences and Humanities","name":"dansSocialSciences","fields":[{"typeName":"dansElsstClassification","multiple":true,"typeClass":"primitive","value":["https://elsst.cessda.eu/id/4/161264a3-d3d1-4c9f-8441-52b908b07498","https://elsst.cessda.eu/id/4/5a40a735-1eca-4afa-930c-0b131f06e8af","https://elsst.cessda.eu/id/4/ebf35305-df80-4770-8bfe-2311389c5331"],"expandedvalue":[{"@id":"https://elsst.cessda.eu/id/4/161264a3-d3d1-4c9f-8441-52b908b07498","termName":[{"lang":"de","value":"WAHRNEHMUNG"},{"lang":"sv","value":"VARSEBLIVNING"},{"lang":"fi","value":"HAVAITSEMINEN"},{"lang":"el","value":"ΑΝΤΙΛΗΨΗ"},{"lang":"cs","value":"VNÍMÁNÍ"},{"lang":"nl","value":"PERCEPTIE"},{"lang":"is","value":"SKYNJUN"},{"lang":"lt","value":"SUVOKIMAS"},{"lang":"fr","value":"PERCEPTION"},{"lang":"en","value":"PERCEPTION"},{"lang":"da","value":"PERCEPTION"},{"lang":"hu","value":"ÉSZLELÉS"},{"lang":"es","value":"PERCEPCIÓN"},{"lang":"no","value":"PERSEPSJON"},{"lang":"sl","value":"ZAZNAVANJE"},{"lang":"ro","value":"PERCEPȚIE"}]},{"@id":"https://elsst.cessda.eu/id/4/5a40a735-1eca-4afa-930c-0b131f06e8af","termName":[{"lang":"no","value":"MILJØENDRINGER"},{"lang":"es","value":"CAMBIOS MEDIOAMBIENTALES"},{"lang":"el","value":"ΠΕΡΙΒΑΛΛΟΝΤΙΚΕΣ ΜΕΤΑΒΟΛΕΣ"},{"lang":"nl","value":"MILIEUVERANDERINGEN"},{"lang":"en","value":"ENVIRONMENTAL CHANGES"},{"lang":"cs","value":"ZMĚNY ŽIVOTNÍHO PROSTŘEDÍ"},{"lang":"ro","value":"SCHIMBĂRI DE MEDIU"},{"lang":"sl","value":"OKOLJSKA SPREMEMBA"},{"lang":"fi","value":"YMPÄRISTÖNMUUTOKSET"},{"lang":"hu","value":"KÖRNYEZETI VÁLTOZÁS"},{"lang":"fr","value":"CHANGEMENTS DE L'ENVIRONNEMENT"},{"lang":"lt","value":"APLINKOS POKYČIAI"},{"lang":"is","value":"UMHVERFISBREYTINGAR"},{"lang":"sv","value":"MILJÖFÖRÄNDRINGAR"},{"lang":"da","value":"MILJØÆNDRING"},{"lang":"de","value":"UMWELTVERÄNDERUNGEN"}]},{"@id":"https://elsst.cessda.eu/id/4/ebf35305-df80-4770-8bfe-2311389c5331","termName":[{"lang":"fi","value":"MAAHANMUUTTO"},{"lang":"nl","value":"IMMIGRATIE"},{"lang":"is","value":"INNFLUTNINGUR FÓLKS"},{"lang":"sl","value":"PRISELJEVANJE"},{"lang":"hu","value":"BEVÁNDORLÁS"},{"lang":"en","value":"IMMIGRATION"},{"lang":"da","value":"IMMIGRATION"},{"lang":"sv","value":"IMMIGRATION"},{"lang":"fr","value":"IMMIGRATION"},{"lang":"ro","value":"IMIGRARE"},{"lang":"lt","value":"IMIGRACIJA"},{"lang":"el","value":"ΠΑΛΙΝΝΟΣΤΗΣΗ"},{"lang":"no","value":"IMMIGRASJON"},{"lang":"es","value":"INMIGRACIÓN"},{"lang":"cs","value":"IMIGRACE"},{"lang":"de","value":"EINWANDERUNG"}]}]},{"typeName":"dansUniverse","multiple":true,"typeClass":"primitive","value":["Our aim is to better understand the complex relationships between perceptions of environmental and socio-cultural changes and how these influence migration decisions. Migrations are characterized by a sending location and at least one receiving location; although in practice it is unclear what a (final) receiving location is as migrants often migrate from one place of origin to multiple receiving locations subsequently (i.e. also called intermediary locations). Therefore, households with a member who has migrated (in sending sites), or respondents who have migrated (in receiving sites) are our primary target groups. \n\nThis study addresses two respondent types: (1) In sending locations (characterised as agricultural communities with net out-migration), this was a member of a household where someone has migrated within the last 10 years for a period of 3 months or more. The respondent was older than 18, and both males and females were interviewed. (2) In receiving locations, the respondent was a person older than 18 who had migrated within the last 10 years for a period of 3 months or more. Both males and females were interviewed."]},{"typeName":"dansSamplingProcedureFreeText","multiple":false,"typeClass":"primitive","value":"Data collection proceeded according to the following phasing: \n\nPhase 1: Site selection \nSending locations (at third- and fourth-tier administrative levels) were selected by Country Leads based on selection criteria assembled by Method Leads. These criteria are described below, and were preceded by an understanding that the sites should be accessible to Country Teams (i.e. secure and low risk).\n\nCriterion 1: Exposure to environmental stressors \nThe sites should have some level of exposure to climate stressors, combined if possible with some evidence of change over time.  Possible main environmental stressors to be considered for the countries for primary site data collection include: In Mali, Ghana, Ethiopia, and Sudan: droughts, climate variability, floods, soil degradation and/or desertification. In Thailand: floods, climate variability. While other environmental stressors relevant to these countries (e.g. sea level rise) may not be analysed for primary sites (due to the difficulty to compare them across countries)- these will be considered in supplementary research conducted in secondary sites (e.g. research with small-scale coastal fishing communities in Senegal in WP3). The different sites selected will ideally show different climate characteristics between them. \n\nCriterion 2: Third-tier administrative level (district/sub-district) \nThe sites selected should be rural areas at third-tier administrative level. This will allow to better discern patterns and trends, which would be more difficult if the population of the site is too large. \n\nCriterion 3: Vulnerability to environmental stressors \nPopulations at the site are particularly vulnerable to the impacts of environmental stressors. This can be due to socio-economic factors (such as a relatively lower human development at the site – see e.g. the Global Data Lab’s Subnational Human Development Index) or a high reliance on agricultural resources and related food insecurity, among other reasons. Because of this greater vulnerability, environmental stressors have an increased chance of leading to a tipping point.\n\nCriterion 4: Similar destination from origin point \nThe sites should ideally encompass a migration system, i.e. the migrants surveyed at the origin point should have a similar or common destination, which will require determining some destination patterns during the site selection.\n\nThis set of criteria does not include specific migration criteria. This is a deliberate choice, acknowledging that climate stressors may cause non-linear shifts in migration (i.e. they may lead to an increase in migration but could also lead to a reduction of migration where people’s choice to migrate is restricted). \n\tReceiving locations were selected by preliminary analysis of FCM results from sending locations and the most frequently mentioned destination area was selected as the receiving location in this particular migration system. In all cases, this was the capital city of the corresponding country. Respondent selection then followed a similar purposive and snowball sampling procedure. \nThe site selection process was an iterative collaboration among Country Teams and WP2, WP4 and WP5 to ensure that data would be collected by all empirical WPs in at least one study site. Sites were selected from among the clusters surveyed by WP1 to ensure results could be compared.   \n\nPhase 2: Purposive sampling\nHouseholds meeting selection criteria in the sending sites (i.e. a household member has migrated within the last 10 years) were identified (by local leaders or through existing networks) and invited to participate if they so wished.\n\nPhase 3: Snowball sampling\nHousehold members were asked to identify other households who also met sampling criteria until 60 respondents were identified and interviewed in each site. \nWorking closely with WP8, WP2 prioritized the integration of Feminist Political Ecology (FPE) into its methodology. FPE is a relatively recent theory that emerged in the 1990s, spearheaded by feminist thinkers such as Dianne Rocheleau who frames gender as a “critical variable in shaping resource access and control, often interacting with class, race, culture, and ethnicity to shape processes of ecological change, and the struggle of men and women to sustain ecologically viable livelihoods” (1996: 4). FPE thus introduces multi-scalar power analysis and can be applied across disciplines. In recent years, FPE has been effectively merged with other methods in innovative ways (Kwan, 2002; Nyantakyi-Frimpong, 2019). Our aim is to add to the knowledge around merging FPE with methods from other disciplines through this project. To do so, we achieved gender balance in responses (50% female respondents 50% male respondents), as well as a range ages (18 – 80) and socio-economic backgrounds (indicated by employment and streamlined with WP1). Furthermore, we employed enumerators with a gender balance of 50% female, 50% male, with the aim of pairing same gender enumerators and respondents in order to minimise the impact of the interviewer’s gender on the data collected (Harling et al, 2019). \n\nThe sample size for each site was 60 individual FCM maps. Individual FCM studies generally employ a smaller sample size as they tend to reach saturation, sometimes as early as after 15-30 FCM networks, and earlier than other traditional qualitative methods (Özesmi and Özesmi, 2004). This study aimed for excellence and as a mitigation response to the method leads not being present to supervise data collection, it was decided to increase the sample size to a minimum of 60 FCM networks in order to ensure a sufficient number of valid FCM networks for the final analysis."},{"typeName":"dansDataCollectionSituation","multiple":false,"typeClass":"primitive","value":"Data collection followed a protocol designed to ensure replicability and best practices in the field. Enumerators were provided with the following instructions: \n\nInterview protocol for enumerators\n4.\tFill in your personal information on A3 interview instruments before entering field \n5.\tIntroduce yourself and the project \n6.\tDetermine whether respondent meets criteria\n7.\tRead Informed Consent Sheet out loud to the respondent and determine whether they are willing to participate. Have respondent sign a copy of an Informed Consent Sheet: the respondent is given the “Participant Copy” and the enumerator should keep the signed version “Researcher Copy” to file.\n8.\tFollow interview script (interview will take between 40 minutes – 1 hour) \n9.\tProvide hand sanitizer gel as a small thank you (if possible)\n10.\tLabel and process FCM map, audio recording, and informed consent forms\n11.\tUpload maps (high quality photographs or scans) and audio files to appropriate project online folders\n\nFor each data collection site, 4-6 enumerators (balanced for gender parity) completed data collection in about one week. Interviews averaged about an hour per respondent. \nEnumerators in the field were supplied with the FCM mapping tool, the interview instrument/script, pens, an audio recorder, an ink pad (for thumb print signatures), a clipboard, face masks, and hand sanitizer. A small gift for respondents was decided per Primary Site as deemed appropriate by Country Teams. Enumerators went to the field in pairs or alone, and their backgrounds ranged from MSc students to experienced enumerators and field coordinators."},{"typeName":"dansActionsToMinimizeLoss","multiple":false,"typeClass":"primitive","value":"Online trainings, pilot studies, field coordination and quality checks"}]},"dansTemporalSpatial":{"displayName":"Temporal and Spatial Coverage","name":"dansTemporalSpatial","fields":[{"typeName":"dansTemporalCoverage","multiple":true,"typeClass":"primitive","value":["2022-2023, contemporary"]},{"typeName":"dansSpatialCoverageControlled","multiple":true,"typeClass":"controlledVocabulary","value":["Ethiopia","Ghana","Kenya"]}]},"dansDataVaultMetadata":{"displayName":"Data Vault 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