Public use data set on new legal immigrants to the U.S. that can address scientific and policy questions about migration behavior and the impacts of migration. A survey pilot project, the NIS-P, was carried out in 1996 to inform the fielding and design of the full NIS. Baseline interviews were ultimately conducted with 1,127 adult immigrants. Sample members were interviewed at baseline, 6 months, and 12 months, with half of the sample also interviewed at three months. The first full cohort, NIS-2003, is based on a nationally representative sample of the electronic administrative records compiled for new immigrants by the US government. NIS-2003 sampled immigrants in the period May-November 2003. The geographic sampling design takes advantage of the natural clustering of immigrants. It includes all top 85 Metropolitan Statistical Areas (MSAs) and all top 38 counties, plus a random sample of other MSAs and counties. Interviews were conducted in respondents'' preferred languages. The baseline was multi-modal: 60% of adult interviews were administered by telephone; 40% were in-person. The baseline round was in the field from June 2003 to June 2004, and includes in the Adult Sample 8,573 respondents, 4,336 spouses, and 1,072 children aged 8-12. A follow-up was planned for 2007. Several modules of the NIS were designed to replicate sections of the continuing surveys of the US population that provide a natural comparison group. Questionnaire topics include Health (self-reports of conditions, symptoms, functional status, smoking and drinking history) and use/source/costs of health care services, depression, pain; background; (2) Background: Childhood history and living conditions, education, migration history, marital history, military history, fertility history, language skills, employment history in the US and foreign countries, social networks, religion; Family: Rosters of all children; for each, demographic attributes, education, current work status, migration, marital status and children; for some, summary indicators of childhood and current health, language ability; Economic: Sources and amounts of income, including wages, pensions, and government subsidies; type, value of assets and debts, financial assistance given/received to/from respondent from/to relatives, friends, employer, type of housing and ownership of consumable durables. * Dates of Study: 2003-2007 * Study Features: Longitudinal * Sample Size: 13,981

United States Immigrants Admitted: All Countries data was reported at 1,127,167.000 Person in 2017. This records a decrease from the previous number of 1,183,505.000 Person for 2016. United States Immigrants Admitted: All Countries data is updated yearly, averaging 451,510.000 Person from Sep 1900 (Median) to 2017, with 118 observations. The data reached an all-time high of 1,827,167.000 Person in 1991 and a record low of 23,068.000 Person in 1933. United States Immigrants Admitted: All Countries data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s United States – Table US.G087: Immigration.

Many countries have become increasingly aggressive in their efforts to stop unauthorized migration, but most evidence suggests that immigration enforcement policies do not effectively deter migrants. We draw on literature from social psychology, specifically the dual-system model of decision-making, which differentiates between judgments that are subject to considerations of risks and costs and judgments that are ‘non-consequentialist’. Non-consequentialist decision-making is founded in moral intuition and rejects rational considerations of costs and benefits. This mental process would render the deterrence tools of the state powerless. We posit that some, but not all, forms of unauthorized migration will invoke non-consequentialist decision-making. When considering semi-legal strategies, which individuals may perceive as ‘bending the law’ rather than breaking it, aspiring migrants are likely to weigh the risks and costs of enforcement policies. Meanwhile, when considering fully illegal migration strategies, aspiring migrants will prioritize moral considerations for breaking the law rather than the consequences of breaking the law. We find evidence for our theory using original population-based list experiments along with focus groups with aspiring migrants in an origin country.

Description: To avoid data duplication, the author includes links to the metadata in the document. These data were obtained in Sprawy ważne dla obywateli | Rzecznik Praw Obywatelskich, and are publicly available, and details about them were accessed from:1) Zespół ds. Równego Traktowania RPO (e-mail on access to public information)Details: w 2022 r. było prowadzonych 567 spraw dotyczących cudzoziemców, w 2023 r. – 1246 takich spraw, natomiast w 2024 r. 1295 (tylko do dnia 30 października 2024 r.)2) OPCAT (Krajowy Mechanizm Prewencji Tortur), e-mail on access to public informationW 2023 r. skarg cudzoziemców dotyczących wjazdu i pobytu było 33, natomiast część spraw migranckich jest np. ujęta w (w 2023 r. były 42 takie sprawy).The model was created on the basis of an analysis of sources of the national and European law, administrative decisions, decisions of domestic and international courts, decisions and speeches made by ombudsmen as well as legal scholarship and commentary. Experiences of other countries and the analysis of legal solutions operating there will be used in an auxiliary scope.

Context

I first encountered this dataset in the Data visualization course of the IBM Professional Certificate.

Content

I actually obtained this data from a Github repo (now can’t find it), but found a copy under the ‘Canada by Citizenship’ tab here. The dataset contains annual time series data on the flows of international migrants as recorded by Canada from 1980-2013.

The official CD-ROM documentation for the UN International Migration flows: The 2015 revision has additional information under Section D.

These data were compiled within the scope of the author's doctoral thesis research on ‘Turkish Migration Policy’. These data reflect the numerical results of the immigration and asylum policy of Republican Turkey. The purpose of compiling the data is to determine the results of the Turkish migration policy in the context of immigration and asylum policies in the historical process. The language and explanations of the table are in Russian.

Notes: No official statistics on Greek-Turkish exchanges between 1923 and 1925 were published. The Turkish State Institute of Statistics stopped publishing statistics on migrants in 1961. Figures after this date can be obtained from reports and statistics published by the relevant state institutions. In 1939, after the amendment of the Settlement Law No. 2510, migrants and refugees were given the freedom to choose their place of residence. However, official statistics on migrants whose resettlement was subsidised by the state were published in detail after 1945 until 1961.

In 2017, the canton of Geneva implemented Operation Papyrus, an innovative policy to regularize undocumented migrants. The Parchemins study was initiated in this context in order to measure the consequences of access to a residence permit on health, well-being and living conditions. Adopting an approach combining social determinants of health and life course, this interdisciplinary study collects quantitative and qualitative longitudinal data by following a cohort of people over several years. The study describes the characteristics and motivations of undocumented economic migrants living and working in the canton of Geneva, their family and social situation, their housing and employment conditions, as well as their health status. These results fill a gap in the empirical data for this population in Switzerland and Europe.

Due to anonymisation issues, only quantitative data for all four waves are available. The published datasets are reduced datasets due to anonymization. Additional information can be obtained upon request by email to the PIs: Prof. Claudine Burton-Jeangros and Prof. Yves-Laurent Jackson.

A comprehensive dataset of top immigration law firms for H-1B Visa sponsorships in 2025, including salary data, petition trends, and employer insights. Updated annually with the latest trends and employer behavior regarding H-1B visa sponsorship.

The dissertation consists of three chapters relating to the measurement of immigration policies, which developed out of my work as an initial co-author of the International Migration Policy and Law Analysis (IMPALA) Database Project. The first chapter entitled, “Brain Gain? Measuring skill bias in U.S. migrant admissions policy,” develops a conceptual and operational definition of skill bias. I apply the measure to new data revealing the level of skill bias in U.S. migrant admissions policy between 1965 and 2008. Skill bias in U.S. migrant admissions policy is both a critical determinant of the skill composition of the migrant population and a response to economic and public demand for highly skilled migrants. However, despite its central role, this is the first direct, comprehensive, annual measure of skill bias in U.S. migrant admissions policy. The second chapter entitled, “Stalled in the Senate: Explaining change in US migrant admissions policy since 1965,” presents new data characterizing change in U.S. migrant admissions policy as both expansive and infrequent over recent decades. I present a new theory of policy change in U.S. migrant admissions policy that incorporates the role of supermajoritarian decision making procedures and organized anti-immigration groups to better account for both the expansive nature and t he infrequency of policy change. The theory highlights the importance of a coalition of immigrant advocacy groups, employers and unions in achieving policy change and identifies the conditions under which this coalition is most likely to form and least likely to be blocked by an anti-immigration group opposition. The third chapter entitled, “Post-coding aggregation: A methodological principle for independent data collection,” presents a new technique developed to enable independent collection of flexible, high quality data: post-coding aggregation. Post-coding aggregation is a methodological principle that minimizes data loss, increases transparency, and grants data analysts the ability to decide how best to aggregate information to produce measures. I demonstrate how it increases the fl exibility of data use by expanding the utility of data collections for a wider range of research objectives and improves the reliability and the content validity of measures in data analysis.

Analysis of ‘MISSING MIGRANTS (2014-2021)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/methoomirza/missing-migrants-20142021 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Missing Migrants Project tracks deaths of migrants, including refugees and asylum-seekers, who have died or gone missing in the process of migration towards an international destination. Please note that these data represent minimum estimates, as many deaths during migration go unrecorded

What is included in Missing Migrants Project data?

Missing Migrants Project counts migrants who have died at the external borders of states, or in the process of migration towards an international destination, regardless of their legal status. The Project records only those migrants who die during their journey to a country different from their country of residence. Missing Migrants Project data include the deaths of migrants who die in transportation accidents, shipwrecks, violent attacks, or due to medical complications during their journeys. It also includes the number of corpses found at border crossings that are categorized as the bodies of migrants, on the basis of belongings and/or the characteristics of the death. For instance, a death of an unidentified person might be included if the decedent is found without any identifying documentation in an area known to be on a migration route. Deaths during migration may also be identified based on the cause of death, especially if is related to trafficking, smuggling, or means of travel such as on top of a train, in the back of a cargo truck, as a stowaway on a plane, in unseaworthy boats, or crossing a border fence. While the location and cause of death can provide strong evidence that an unidentified decedent should be included in Missing Migrants Project data, this should always be evaluated in conjunction with migration history and trends.

What is excluded?

The count excludes deaths that occur in immigration detention facilities or after deportation to a migrant’s homeland, as well as deaths more loosely connected with migrants´ irregular status, such as those resulting from labour exploitation. Migrants who die or go missing after they are established in a new home are also not included in the data, so deaths in refugee camps or housing are excluded. The deaths of internally displaced persons who die within their country of origin are also excluded. There remains a significant gap in knowledge and data on such deaths. Data and knowledge of the risks and vulnerabilities faced by migrants in destination countries, including death, should not be neglected, but rather tracked as a distinct category.

What sources of information are used in the Missing Migrants Project database?

The Missing Migrants Project currently gathers information from diverse sources such as official records – including from coast guards and medical examiners – and other sources such as media reports, NGOs, and surveys and interviews of migrants. In the Mediterranean region, data are relayed from relevant national authorities to IOM field missions, who then share it with the Missing Migrants Project team. Data are also obtained by IOM and other organizations that receive survivors at landing points in Italy and Greece. IOM and UNHCR also regularly coordinate to validate data on missing migrants in the Mediterranean. Data on the United States/Mexico border are compiled based on data from U.S. county medical examiners, coroners, and sheriff’s offices, as well as media reports for deaths occurring on the Mexican side of the border. In Africa, data are obtained from media and NGOs, including the Regional Mixed Migration Secretariat and the International Red Cross/Red Crescent. The quality of the data source(s) for each incident is assessed through the ‘Source quality’ variable, which can be viewed in the data. Across the world, the Missing Migrants Project uses social and traditional media reports to find data, which are then verified by local IOM staff whenever possible. In all cases, new entries are checked against existing records to ensure that no deaths are double-counted. In all regions, Missing Migrants Project data represent a minimum estimate of the number of migrant deaths. To learn more about data sources, visit the thematic page on migrant deaths and disappearances in the Global Migration Data Portal.

Content

What are the variables used in the Missing Migrants Project database?

This section presents the list of variables that constitute the Missing Migrants Project database. While ideally, all incidents recorded would include entries for each of these variables, the challenges described above mean that this is not always possible. The minimum information necessary to register an incident is the date of the incident, the number of dead and/or the number of missing, and the location of death. If the information is unavailable, the cell is left blank or “unknown” is recorded, as indicated in below.

1. Web ID - An automatically generated number used to identify each unique entry in the dataset.

2. Region - Region in which an incident took place. For more about regional classifications used in the dataset, click here.

3. Incident Date - Estimated date of death. In cases where the exact date of death is not known, this variable indicates the date in which the body or bodies were found. In cases where data are drawn from surviving migrants, witnesses or other interviews, this variable is entered as the date of the death as reported by the interviewee. At a minimum, the month and the year of death is recorded. In some cases, official statistics are not disaggregated by the incident, meaning that data is reported as a total number of deaths occurring during a certain time period. In such cases the entry is marked as a “cumulative total,” and the latest date of the range is recorded, with the full dates recorded in the comments.

4. Year - The year in which the incident occurred.

5. Reported month - The month in which the incident occurred.

6. Number dead - The total number of people confirmed dead in one incident, i.e. the number of bodies recovered. If migrants are missing and presumed dead, such as in cases of shipwrecks, leave blank.

7. Number missing - The total number of those who are missing and are thus assumed to be dead. This variable is generally recorded in incidents involving shipwrecks. The number of missing is calculated by subtracting the number of bodies recovered from a shipwreck and the number of survivors from the total number of migrants reported to have been on the boat. This number may be reported by surviving migrants or witnesses. If no missing persons are reported, it is left blank.

8. Total dead & missing - The sum of the ‘number dead’ and ‘number missing’ variables.

9. Number of survivors - The number of migrants that survived the incident, if known. The age, gender, and country of origin of survivors are recorded in the ‘Comments’ variable if known. If unknown, it is left blank.

10. Number of females - Indicates the number of females found dead or missing. If unknown, it is left blank. This gender identification is based on a third-party interpretation of the victim's gender from information available in official documents, autopsy reports, witness testimonies, and/or media reports.

11. Number of males - Indicates the number of males found dead or missing. If unknown, it is left blank. This gender identification is based on a third-party interpretation of the victim's gender from information available in official documents, autopsy reports, witness testimonies, and/or media reports.

12. Number of children - Indicates the number of individuals under the age of 18 found dead or missing. If unknown, it is left blank.

13. Age - The age of the decedent(s). Occasionally, an estimated age range is recorded. If unknown, it is left blank.

14. Country of origin - Country of birth of the decedent. If unknown, the entry will be marked “unknown”.

15. Region of origin - Region of origin of the decedent(s). In some incidents, region of origin may be marked as “Presumed” or “(P)” if migrants travelling through that location are known to hail from a certain region. If unknown, the entry will be marked “unknown”.

16. Cause of death - The determination of conditions resulting in the migrant's death i.e. the circumstances of the event that produced the fatal injury. If unknown, the reason why is included where possible. For example, “Unknown – skeletal remains only”, is used in cases in which only the skeleton of the decedent was found.

17. Location description - Place where the death(s) occurred or where the body or bodies were found. Nearby towns or cities or borders are included where possible. When incidents are reported in an unspecified location, this will be noted.

18. Location coordinates - Place where the death(s) occurred or where the body or bodies were found. In many regions, most notably the Mediterranean, geographic coordinates are estimated as precise locations are not often known. The location description should always be checked against the location coordinates.

19. Migration route - Name of the migrant route on which incident occurred, if known. If unknown, it is left blank.

20. UNSD geographical grouping - Geographical region in which the incident took place, as designated by the United Nations Statistics Division (UNSD) geoscheme. For more about regional classifications used in the dataset, click here.

21. Information source - Name of source of information for each incident. Multiple sources may be listed.

22. Link - Links to original reports of migrant deaths /

Canada’s appeal as an immigration destination has been increasing over the past two decades, with a total of 464,265 people immigrating to the country in 2024. This figure is an increase from 2000-2001, when approximately 252,527 immigrants came to Canada. Immigration to the Great White North Between July 1, 2022 and June 30, 2023, there were an estimated 199,297 immigrants to Ontario, making it the most popular immigration destination out of any province. While the number of immigrants has been increasing over the years, in 2024 over half of surveyed Canadians believed that there were too many immigrants in the country. However, in 2017, the Canadian government announced its aim to significantly increase the number of permanent residents to Canada in order to combat an aging workforce and the decline of working-age adults. Profiles of immigrants to Canada The gender of immigrants to Canada in 2023 was just about an even split, with 234,279 male immigrants and 234,538 female immigrants. In addition, most foreign-born individuals in Canada came from India, followed by China and the Philippines. The United States was the fifth most common origin country for foreign-born residents in Canada.

Data on countries of citizenship by immigrant status and period of immigration, by admission category and applicant type, age and gender for the population in private households in Canada, provinces and territories, census metropolitan areas, census agglomerations and parts.

A detailed analysis of H-1B visa sponsorship trends, featuring data on labor certifications, top sponsoring employers, most common job titles, leading immigration law firms, key industries, and geographic distribution. This dataset provides valuable insights into employment-based immigration patterns, helping professionals, employers, and policymakers make informed decisions.

This research adds to the expanding field of data-driven analysis, scientific modeling, and forecasting on the impact of having access to the Internet and IoT on the general US population regarding immigrants and immigration policies. More specifically, this research focuses on the public opinion of undocumented immigrants in the United States and having access to the Internet in their local settings. The term Undocumented Immigrants refers to those who live in the United States without legal papers, documents, or visas. Undocumented immigrants may have come into the country unlawfully or with valid documentation, but their legal status has expired. Using the 2020 American National Election Studies (ANES) time series dataset, I investigated the relationship between internet access (A2I) and public perception of undocumented immigrants. According to my research and analysis, increasing internet access among non-Hispanic whites with at least a bachelors degree with an annual household income of less than 99K is more likely to oppose the deportation of undocumented immigrants and separating unaccompanied children from their families in borderland areas. The individuals with substantial Republican political ideology exhibit significantly lower opposing effects in deporting undocumented immigrants or separating unaccompanied children from their families. The evidence from multiple statistical models is resilient to a variety of factors. The findings show that increased internet access may improve undocumented immigrants social integration and acceptability. During health emergencies, it may be especially beneficial to make them feel safe, included, and supported in their local settings.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The main aim of this research is to study the criminal mobility of ethnic-based organized crime groups. The project examines whether organized crime groups are able to move abroad easily and to reproduce their territorial control in a foreign country, or whether these groups, and/or individual members, start a life of crime only after their arrival in the new territories, potentially as a result of social exclusion, economic strain, culture conflict and labeling. More specifically, the aim is to examine the criminal mobility of ethnic Albanian organized crime groups involved in a range of criminal markets and operating in and around New York City, area and to study the relevance of the importation/alien conspiracy model versus the deprivation model of organized crime in relation to Albanian organized crime. There are several analytical dimensions in this study: (1) reasons for going abroad; (2) the nature of the presence abroad; (3) level of support from ethnic constituencies in the new territories; (4) importance of cultural codes; (5) organizational structure; (6) selection of criminal activities; (7) economic incentives and political infiltration. This study utilizes a mixed-methods approach with a sequential exploratory design, in which qualitative data and documents are collected and analyzed first, followed by quantitative data. Demographic variables in this collection include age, gender, birth place, immigration status, nationality, ethnicity, education, religion, and employment status. Two main data sources were employed: (1) court documents, including indictments and court transcripts related to select organized crime cases (84 court documents on 29 groups, 254 offenders); (2) in-depth, face-to-face interviews with 9 ethnic Albanian offenders currently serving prison sentences in U.S. Federal Prisons for organized crime related activities, and with 79 adult ethnic Albanian immigrants in New York, including common people, undocumented migrants, offenders, and people with good knowledge of Albanian organized crime modus operandi. Sampling for these data were conducted in five phases, the first of which involved researchers examining court documents and identifying members of 29 major ethnic Albanian organized crime groups operating in the New York area between 1975 and 2013 who were or had served sentences in the U.S. Federal Prisons for organized crime related activities. In phase two researchers conducted eight in-depth interviews with law enforcement experts working in New York or New Jersey. Phase three involved interviews with members of the Albanian diaspora and filed observations from an ethnographic study. Researchers utilized snowball and respondent driven (RDS) recruitment methods to create the sample for the diaspora dataset. The self-reported criteria for recruitment to participate in the diaspora interviews were: (1) age 18 or over; (2) of ethnic Albanian origin (foreign-born or 1st/2nd generation); and (3) living in NYC area for at least 1 year. They also visited neighborhoods identified as high concentrations of ethnic Albanian individuals and conducted an ethnographic study to locate the target population. In phase four, data for the cultural advisors able to help with the project data was collected. In the fifth and final phase, researchers gathered data for the second wave of the diaspora data, and conducted interviews with offenders with ethnic Albanian immigrants with knowledge of the organized crime situation in New York City area. Researchers also approached about twenty organized crime figures currently serving a prison sentence, and were able to conduct 9 in-depth interviews.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.