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.

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

Legal permanent residents (LPRs) are foreign nationals who have been granted the right to reside permanently in the United States. LPRs are often referred to as simply 'immigrants,' but they are also known as 'permanent resident aliens' and 'green card holders.

ObjectiveThis paper describes the impact that the different COVID-19 related restrictions have had on the mental health and wellbeing of 57 Central American and Caribbean immigrants stranded in Mexico due to the pandemic.MethodsEthnographic data was obtained through the application of in-depth interviews centered on topics such as migration history, personal experience with COVID-19 and beliefs about the pandemic. This information was further analyzed through a narrative approach and Atlas Ti.Main findingsUS Title 42 and the Migrant Protection Protocols (MPP) have stranded thousands of individuals in the US-Mexico border region, a situation that has overcrowded the available shelters in the area and forced many of the immigrants to live on the streets and in improvised encampments. Thus, exposing them to a higher risk of contagion. Furthermore, the majority of the interviewed Central American and Caribbean immigrants consider that Mexico is more lenient when it comes to the enforcement of sanitary measures, especially when compared to their countries of origin. Finally, vaccination hesitancy was low among the interviewees, mainly due to the operative aspects of the vaccination effort in Mexico and the fear of ruining their chances to attain asylum in the US. These findings are backed up by the discovery of five recurring narratives among the interviewees regarding: (1) The pandemic's psychological impact. (2) The uncertainty of being stranded in Mexico and the long wait. (3) Their fear of violence over the fear of contagion. (4) The perceived leniency of Mexico with the pandemic when compared to their countries of origin, and (5) their beliefs about the pandemic and vaccines.Key findingThe mental health of stranded Central American and Caribbean immigrants in Mexico during the COVID-19 pandemic is mostly affected by their inability to make it across the US-Mexico border using legal means.

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

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 UK's decision to leave the EU has necessitated a wholesale rethink of UK immigration policy with the ending of free movement of workers. The motivations for this work then were to examine the immigration/worker protection boundary from a number of perspectives, with particular emphasis on the legal dimension. While understanding the developing EU and domestic (macro) perspective our aims at a micro level were to understand the legal problems EU citizens in low paid work in the UK were facing and how they resolve those problems. These legal problems were at times exacerbated by Brexit, particularly with the advent of the new digital EUSS (EU Settlement Scheme)- our research followed this in real time and recorded issues. One of our key findings and covered by the book published as a result of the dataset here is that of Pragmatic Law and the role of everyday community advice in the wider legal advice eco-system. This is an element of legal advice which to date had been little researched. Another key outcome was the contribution to literature on both EU free movement and citizenship studies, particularly in the context of vulnerable EU citizens.

Our aim was to chart the experience and perceptions of EU migrants in the UK before, during and after Brexit to enable us to analyse the experience of EU migrants in seeking access to the social welfare system in the UK, the issues they have with immigration law and employment law, specifically the relationship between race and nationality discrimination and the Brexit process. We will seek to collect robust empirical evidence to establish whether the fact of Brexit, together with the policy changes, media pronouncements and political rhetoric, have an impact on both the experience of, and perceptions surrounding, the experience of EU migrants.

List of all Citywide Hard to Reach Know Your Rights conducted by MOIA partners. This dataset include event information such as date/time, borough, zip code, primary language, languages, total attendees, total households reporting children, number of people receiving inhouse referrals, and number of people requesting immigration legal referrals.