The Gurukulam is a Sanskrit word and is an ancient Indian system of teaching derived from Vedic traditions. In this system of learning, a student lives with the teacher, who in addition to teaching them, guides them through their daily life.[5] Labour India Gurukulam Public School and Junior College was founded by V. J. George Kulangara in 1993. It is owned by the registered Labour India Educational Society and is located in hilly terrain, recently renamed as Labour India Hills in Marangattupilly village.[citation needed]

The is based on the Central Board of Secondary Education (CBSE), New Delhi and the text books are as prescribed by the National Council of Educational Research and Training (NCERT). The medium of instruction is English. However, a three-language method is adopted in all classes, to enable students to be functionally multilingual.

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Labour India Gurukulam Public School is a force to reckon with when it comes to model united nations conferences in India.The majority of school's glory in model united nations comes from the one man army led by secretary general, master " Domil Antony Johnson ", who alone have represented the school in more than 150+ model united nations conferences across the United States of America, Turkey, Mexico, Israel,United Arab Emirates, Singapore, Pakistan, Panama, Philippines, Bangladesh and India.The Model United Nations Society of Labour India Gurukulam Public School reached its highest glory, when for the first time in history, " Domil Antony Johnson " then the 16 Year old became " The Reigning World Champion " at the International Model United Nations Conference and India's International Movement to Unite Nations Conference 2020.

Despite of the larger glory, he then continued to represent the school and further went on to win the most prestigious model united nations conferences in the world such as the Harvard Model United Nations - India, Nanyang Technological University Model United Nations - Singapore and even 7 Major Indian Institute of Technology - National Institute of Technology Model UN Championships.

Adding on, in June 2021, he has the taken standard of model united nations in Kerala to the highest level ever possible by becoming the first Keralite to ever jury the Harvard Model United Nations - Dubai as an assistant director in committee United Nations Development Programme, and youngest Indian to ever qualify for Harvard National Model United Nations - Latin America.

Apart from Domil, the Model United Nations Society of Labour India Gurukulam Public School has also produced talented Model United Nations delegates which include the likes of master Advaith Vijay, winner of outstanding delegate award in India and Abroad Model United Nations and special mention award in United Nations Replica, master Kevin Charles Deepu, winner of special mention award in both United Nations Replica and India Abroad Model United Nations, master Apoorva Cinubal, and miss Shreya Nair, winner of outstanding delegate and best delegate award at India and Abroad Model United Nations Conference.

This briefing relies on data from the Labour Force Survey (LFS) for 2007 to 2022 and the Annual Population Survey (APS) for 2022. The LFS is the largest household study in the UK and provides the official measures of employment and unemployment. The APS includes most of the same individuals as the LFS but also an additional boost to the sample. However, Some variables are unavailable in the APS, and in those cases, this briefing uses the LFS instead. The LFS/APS have some important limitations. Some people are excluded, such as residents of communal establishments like hostels, and other groups may be undercounted due to survey non-response.

Because the LFS and APS are sample surveys, the estimates come with margins of error. This means minor differences between numbers or percentages may not be statistically significant. However, all the differences between groups described in the briefing text are statistically significant. A difference between two groups is considered statistically significant when the probability that this difference is caused by chance is very small. In that case, we assume that the differences we observe in the data will likely exist in the population. Note that minor differences between estimates for different groups may not be statistically significant if not described in the briefing narrative.

For the majority, work will not have been the main reason for migration (see the Migration Observatory briefing Where do migrants live in the UK for information on the main reason for migration of the foreign-born population). For more information on work visas and people who move specifically for work, see the Migration Observatory briefing, Work visas and migrant workers in the UK.

Across Europe, labour market integration policies focus on recently arrived migrants and could include job search assistance, recognition of foreign qualifications or provision of specific skills, such as language courses or vocational and non-vocational training (Bilgili, 2015). For an overview of European labour market integration policies, see the MIPEX report Evaluating Impact: Lessons Learned from Robust Evaluations of Labour Market Integration Policies.

There have always been more non-EU-born than EU-born workers in the UK labour market. The gap in the number of EU and non-EU-born workers narrowed from 2012 to 2016 when EU net migration to the UK was high. However, more recently, non-EU citizens have been the major source of growth in the migrant workforce. This results primarily from the fact that EU net migration remained low after the pandemic while non-EU net migration rose markedly. For more information about net migration from EU and non-EU countries, see the Migration Observatory Briefing, Net Migration to the UK.

Women from MENA, Central Asia and South Asian countries, excluding India, were far less likely to be employed, with looking after the family home the primary reason: among women from these regions who were not in employment in 2022, 43% of those born in MENA, Central Asia cited this as the reason they were not employed, as did 59% of women who were born South Asian countries excluding India.

Unemployment rates have generally followed similar trends for both migrants and UK-born over the past two decades, with sharp increases in the aftermath of the 2008 financial crisis and steady declines from 2012 to 2019 (Figure 3). The unemployment rate tended to be lower among EU migrants than the UK-born from 2008 until the beginning of the pandemic, while non-EU migrants have always had higher unemployment rates than their UK-born counterparts.

The economic downturn caused by the COVID-19 pandemic led to a steep rise in the unemployment rates of both UK- and foreign-born workers, which peaked at the end of 2020 and the beginning of 2021. By the end of 2022, however, the unemployment rate for migrants had fallen to 5%.

Migrants who came to the UK for work were the most likely to be employed and the least likely to be unemployed in 2022. Among non-EU migrants, those who initially came to the UK seeking asylum had both a lower employment rate and a higher unemployment rate than other non-EU migrants (Figure 6). Several factors may have contributed to this, including that refugees tend to have smaller social networks to support the process of finding a job and often have a lower health status, particularly in terms of mental health (Ruiz and Vargas-Silva, 2018). There is also some evidence that restrictions on asylum seekers working while their applications are being processed can lead to worse outcomes in the labour market in the long run.

In 2022, nearly one in five workers born in non-EU countries worked in the health and care sector (19%), almost twice as many as the next most common sector: retail (10%) (Figure 7). Workers born in Sub-Saharan Africa and East & Southeast Asia were more likely to work in health and care than any other region-of-origin group, although workers from these regions did different types of work in the sector: 42% of Sub-Saharan Africans were care workers, while 40% of East & Southeast Asians were working as nurses.

By contrast, EU workers were more evenly distributed across sectors, with manufacturing, retail, health, and care the most common. Almost a third of workers born in EU-8 countries were working in either retail or manufacturing jobs in 2022, while workers from EU-14 countries were most likely to work in education.

Around a fifth of the employed workforce in 2022 were migrants, but their presence varied considerably across sectors. For example, migrants were over-represented in the IT and communications, transport and storage, and hospitality sectors and under-represented in public administration.

EU-8 workers made up only 1% of the working-age population in employment but represented 6% of workers in the transport and storage sector. Indian workers were over-represented in the IT and communication sector, which includes jobs such as computer programmers.

Taken as a whole, the occupational distribution of migrant workers did not differ much from that of UK-born workers in 2022, although migrants were slightly more likely to be working in jobs classed as both high- and low-skill than the UK-born (Figure 8). In this context, job skills mainly indicate the educational credentials and training required to perform a job and do not consider other types of personal skills valued in the labour market. A majority of both migrants and UK-born workers were in middle-skilled jobs, which included occupations such as associate professionals, administrative jobs, sales assistants and some care work.

There are considerable differences in the type of jobs that workers do by region of birth. Over half of workers born in North America, Oceania, and India were in high-skilled jobs in 2022, the most common of which among the overall migrant population were IT specialists, teachers, managers, and nurses. By contrast, fewer than 1 in 5 workers born in new EU accession countries (EU-8 and EU-2) were working in high-skill jobs. Migrants from these countries are most likely to work in low-skill occupations, including cleaners, waiters, and packers (Figure 8). 152ee80cbc

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