6 datasets found
  1. z

    Population dynamics and Population Migration

    • zenodo.org
    Updated Apr 8, 2025
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    Rutuja Sonar Riya Patil; Rutuja Sonar Riya Patil (2025). Population dynamics and Population Migration [Dataset]. http://doi.org/10.5281/zenodo.15175736
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    Dataset updated
    Apr 8, 2025
    Dataset provided by
    Zenodo
    Authors
    Rutuja Sonar Riya Patil; Rutuja Sonar Riya Patil
    Description

    Population dynamics, its types. Population migration (external, internal), factors determining it, main trends. Impact of migration on population health.

    Under the guidance of Moldoev M.I. Sir By Riya Patil and Rutuja Sonar

    Abstract

    Population dynamics influence development and vice versa, at various scale levels: global, continental/world-regional, national, regional, and local. Debates on how population growth affects development and how development affects population growth have already been subject of intensive debate and controversy since the late 18th century, and this debate is still ongoing. While these two debates initially focused mainly on natural population growth, the impact of migration on both population dynamics and development is also increasingly recognized. While world population will continue growing throughout the 21st century, there are substantial and growing contrasts between and within world-regions in the pace and nature of that growth, including some countries where population is stagnating or even shrinking. Because of these growing contrasts, population dynamics and their interrelationships with development have quite different governance implications in different parts of the world.

    1. Population Dynamics

    Population dynamics refers to the changes in population size, structure, and distribution over time. These changes are influenced by four main processes:

    Birth rate (natality)

    Death rate (mortality)

    Immigration (inflow of people)

    Emigration (outflow of people)

    Types of Population Dynamics

    Natural population change: Based on birth and death rates.

    Migration-based change: Caused by people moving in or out of a region.

    Demographic transition: A model that explains changes in population growth as societies industrialize.

    Population distribution: Changes in where people live (urban vs rural).

    2. Population Migration

    Migration refers to the movement of people from one location to another, often across political or geographical boundaries.

    Types of Migration

    External migration (international):

    Movement between countries.

    Examples: Refugee relocation, labor migration, education.

    Internal migration:

    Movement within the same country or region.

    Examples: Rural-to-urban migration, inter-state migration.

    3. Factors Determining Migration

    Migration is influenced by push and pull factors:

    Push factors (reasons to leave a place):

    Unemployment

    Conflict or war

    Natural disasters

    Poverty

    Lack of services or opportunities

    Pull factors (reasons to move to a place):

    Better job prospects

    Safety and security

    Higher standard of living

    Education and healthcare access

    Family reunification

    4. Main Trends in Migration

    Urbanization: Mass movement to cities for work and better services.

    Global labor migration: Movement from developing to developed countries.

    Refugee and asylum seeker flows: Due to conflict or persecution.

    Circular migration: Repeated movement between two or more locations.

    Brain drain/gain: Movement of skilled labor away from (or toward) a country.

    5. Impact of Migration on Population Health

    Positive Impacts:

    Access to better healthcare (for migrants moving to better systems).

    Skills and knowledge exchange among health professionals.

    Remittances improving healthcare affordability in home countries.

    Negative Impacts:

    Migrants’ health risks: Increased exposure to stress, poor living conditions, and occupational hazards.

    Spread of infectious diseases: Especially when health screening is lacking.

    Strain on health services: In receiving areas, especially with sudden or large influxes.

    Mental health challenges: Due to cultural dislocation, discrimination, or trauma.

    Population dynamics is one of the fundamental areas of ecology, forming both the basis for the study of more complex communities and of many applied questions. Understanding population dynamics is the key to understanding the relative importance of competition for resources and predation in structuring ecological communities, which is a central question in ecology.

    Population dynamics plays a central role in many approaches to preserving biodiversity, which until now have been primarily focused on a single species approach. The calculation of the intrinsic growth rate of a species from a life table is often the central piece of conservation plans. Similarly, management of natural resources, such as fisheries, depends on population dynamics as a way to determine appropriate management actions.

    Population dynamics can be characterized by a nonlinear system of difference or differential equations between the birth sizes of consecutive periods. In such a nonlinear system, when the feedback elasticity of previous events on current birth size is larger, the more likely the dynamics will be volatile. Depending on the classification criteria of the population, the revealed cyclical behavior has various interpretations. Under different contextual scenarios, Malthusian cycles, Easterlin cycles, predator–prey cycles, dynastic cycles, and capitalist–laborer cycles have been introduced and analyzed

    Generally, population dynamics is a nonlinear stochastic process. Nonlinearities tend to be complicated to deal with, both when we want to do analytic stochastic modelling and when analysing data. The way around the problem is to approximate the nonlinear model with a linear one, for which the mathematical and statistical theories are more developed and tractable. Let us assume that the population process is described as:

    (1)Nt=f(Nt−1,εt)

    where Nt is population density at time t and εt is a series of random variables with identical distributions (mean and variance). Function f specifies how the population density one time step back, plus the stochastic environment εt, is mapped into the current time step. Let us assume that the (deterministic) stationary (equilibrium) value of the population is N* and that ε has mean ε*. The linear approximation of Eq. (1) close to N* is then:

    (2)xt=axt−1+bϕt

    where xt=Nt−N*, a=f

    f(N*,ε*)/f

    N, b=ff(N*,ε*)/fε, and ϕt=εt−ε*

    The term population refers to the members of a single species that can interact with each other. Thus, the fish in a lake, or the moose on an island, are clear examples of a population. In other cases, such as trees in a forest, it may not be nearly so clear what a population is, but the concept of population is still very useful.

    Population dynamics is essentially the study of the changes in the numbers through time of a single species. This is clearly a case where a quantitative description is essential, since the numbers of individuals in the population will be counted. One could begin by looking at a series of measurements of the numbers of particular species through time. However, it would still be necessary to decide which changes in numbers through time are significant, and how to determine what causes the changes in numbers. Thus, it is more sensible to begin with models that relate changes in population numbers through time to underlying assumptions. The models will provide indications of what features of changes in numbers are important and what measurements are critical to make, and they will help determine what the cause of changes in population levels might be.

    To understand the dynamics of biological populations, the study starts with the simplest possibility and determines what the dynamics of the population would be in that case. Then, deviations in observed populations from the predictions of that simplest case would provide information about the kinds of forces shaping the dynamics of populations. Therefore, in describing the dynamics in this simplest case it is essential to be explicit and clear about the assumptions made. It would not be argued that the idealized population described here would ever be found, but that focusing on the idealized population would provide insight into real populations, just as the study of Newtonian mechanics provides understanding of more realistic situations in physics.

    Population migration

    The vast majority of people continue to live in the countries where they were born —only one in 30 are migrants.

    In most discussions on migration, the starting point is usually numbers. Understanding changes in scale, emerging trends, and shifting demographics related to global social and economic transformations, such as migration, help us make sense of the changing world we live in and plan for the future. The current global estimate is that there were around 281 million international migrants in the world in 2020, which equates to 3.6 percent of the global population.

    Overall, the estimated number of international migrants has increased over the past five decades. The total estimated 281 million people living in a country other than their countries of birth in 2020 was 128 million more than in 1990 and over three times the estimated number in 1970.

    There is currently a larger number of male than female international migrants worldwide and the growing gender gap has increased over the past 20 years. In 2000, the male to female split was 50.6 to 49.4 per cent (or 88 million male migrants and 86 million female migrants). In 2020 the split was 51.9 to 48.1 per cent, with 146 million male migrants and 135 million female migrants. The share of

  2. Gun ownership U.S. 2022, by party affiliation

    • statista.com
    • ai-chatbox.pro
    Updated Jun 26, 2025
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    Statista (2025). Gun ownership U.S. 2022, by party affiliation [Dataset]. https://www.statista.com/statistics/249775/percentage-of-population-in-the-us-owning-a-gun-by-party-affiliation/
    Explore at:
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 3, 2022 - Oct 20, 2022
    Area covered
    United States
    Description

    In the United States in 2022, ** percent of Republicans reported that they owned at least one gun, and ** percent said that they lived in a household with a gun. In comparison, only ** percent of Democrats owned at least one gun, and ** percent lived in a gun household. Who are gun owners? In 2022, significantly more Democrats were in favor of limiting gun ownership in comparison to Republicans. On the other hand, more Republicans were in favor of protecting the right to own guns in comparison to Democrats. When examined by education level, respondents who said they only had some college, but no degree, were the most likely to have said that there is at least one gun in their household. However, nearly a ******* of Americans over 18 years old said that they rarely carry a gun on their person. Republicans vs Democrats Debate The gun control debate in the United States has been a highly contested one. In light of frequent mass shootings, gun control laws have become the center of policy discussions. Democratic politicians tend to put significant emphasis on their gun control policies, and are overall more in favor of stricter gun control laws and want more background checks for those who want to purchase a gun. However, Republicans tend to work in favor of gun rights.

  3. Z

    Data from: Evaluating the effects of nest management on a recovering raptor...

    • data.niaid.nih.gov
    Updated Jun 19, 2024
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    Cappello, Caroline D. (2024). Evaluating the effects of nest management on a recovering raptor using integrated population modeling [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_11051070
    Explore at:
    Dataset updated
    Jun 19, 2024
    Dataset provided by
    Cappello, Caroline D.
    Driscoll, James T.
    McCarty, Kyle M.
    Jacobson, Kenneth V.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data and code from Cappello et al. 2024 Ecosphere

    Evaluating the effects of nest management on a recovering raptor using integrated population modeling.

    Abstract: Evaluating population responses to management is a crucial component of successful conservation programs. Models predicting population growth under different management scenarios can provide key insights into the efficacy of specific management actions both in reversing population decline and in maintaining recovered populations. Bald eagle (Haliaeetus leucocephalus) conservation in the United States has seen many successes over the last 50 years, yet the extent to which the bald eagle population has recovered in Arizona, an important population within the Southwest region, remains an area of debate. Estimates of the species’ population trend and an evaluation of ongoing nest-level management practices are needed to inform management decisions. We developed a Bayesian integrated population model (IPM) and population viability analysis (PVA) using a 36-year dataset to assess Arizona bald eagle population dynamics and their underlying demographic rates under current and possible future management practices. We estimated that the population grew from 77 females in 1993 to 180 females in 2022, an average yearly increase of 3%. Breeding sites that had trained personnel (i.e., nestwatchers) stationed at active nests to mitigate human disturbance had 28% higher reproductive output than nests without this protection. Uncertainty around population trends was high, but scenarios that continued the nestwatcher program were less likely to predict abundance declines than scenarios without nestwatchers. Here, the IPM-PVA framework provides a useful tool both for estimating the effectiveness of past management actions and for exploring the management needs of a delisted population, highlighting that continued management action may be necessary to maintain population viability even after meeting certain recovery criteria.

  4. f

    Table_1_Co-management brings hope for effective biodiversity conservation...

    • frontiersin.figshare.com
    pdf
    Updated Aug 17, 2023
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    Leonard Manda; Kolawolé Valère Salako; Andrew Kataya; Sèdjro A. T. Affossogbe; Dalo Njera; William O. Mgoola; Achille Ephrem Assogbadjo; Brice Sinsin (2023). Table_1_Co-management brings hope for effective biodiversity conservation and socio-economic development in Vwaza Marsh Wildlife Reserve in Malawi.pdf [Dataset]. http://doi.org/10.3389/fcosc.2023.1124142.s003
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Aug 17, 2023
    Dataset provided by
    Frontiers
    Authors
    Leonard Manda; Kolawolé Valère Salako; Andrew Kataya; Sèdjro A. T. Affossogbe; Dalo Njera; William O. Mgoola; Achille Ephrem Assogbadjo; Brice Sinsin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Malawi
    Description

    Co-management has been widely promoted in protected area management on the premise that it may simultaneously enhance biodiversity conservation outcomes and improve livelihoods of the park-border communities. However, the success of this management approach remains a growing debate raising the question of its effectiveness. To contribute to this debate, we used local community perceptions and secondary ecological data to assess the extent to which co-management has effectively contributed to biodiversity conservation and socio-economic development outcomes in the Vwaza Marsh Wildlife Reserve. Face-to-face individual interviews using a semi-structured questionnaire were used to collect data on the perceptions of co-management from 160 purposively selected heads of households. A desk study was used to collect data on trends in animal populations, animal mortality, and prohibited activities including incidences of poaching for the past 30 years (pre-and post-introduction of co-management). Results showed that local communities have positive perceptions of the conservation work in the Vwaza Marsh Wildlife Reserve. Further, there was an improved people-park relationship and a recovery of animal populations in the reserve after the introduction of co-management. These findings point to the success of co-management in the area. However, misunderstandings over revenue sharing were still a thorny issue, somehow creating mistrust between parties. We concluded that while it may still be early to achieve more demonstrable conservation outcomes, co-management appears to bring hope for effective biodiversity conservation and socio-economic development in the Vwaza Marsh Wildlife Reserve. Participatory evaluation of co-management involving key stakeholders is recommended in the Vwaza Marsh Wildlife Reserve based on the findings of this study and lessons learnt over the years.

  5. f

    Data_Sheet_1_Transparency About Values and Assertions of Fact in Natural...

    • frontiersin.figshare.com
    docx
    Updated Jun 2, 2023
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    Adrian Treves; Paul C. Paquet; Kyle A. Artelle; Ari M. Cornman; Miha Krofel; Chris T. Darimont (2023). Data_Sheet_1_Transparency About Values and Assertions of Fact in Natural Resource Management.docx [Dataset]. http://doi.org/10.3389/fcosc.2021.631998.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Frontiers
    Authors
    Adrian Treves; Paul C. Paquet; Kyle A. Artelle; Ari M. Cornman; Miha Krofel; Chris T. Darimont
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Worldwide, unsustainable use of nature threatens many ecosystems and the services they provide for a broad diversity of life, including humans. Yet, governments commonly claim that the best available science supports their policies governing extraction of natural resources. We confront this apparent paradox by assessing the complexity of the intersections among value judgments, fact claims, and scientifically verified facts. Science can only describe how nature works and predict the likely outcomes of our actions, whereas values influence which actions or objectives society ought to pursue. In the context of natural resource management, particularly of fisheries and wildlife, governments typically set population targets or use quotas. Although these are fundamentally value judgments about how much of a resource a group of people can extract, quotas are often justified as numerical guidance derived from abstracted, mathematical, or theoretical models of extraction. We confront such justifications by examining failures in transparency about value judgments, which may accompany unsupported assertions articulated as factual claims. We illustrate this with two examples. Our first case concerns protection and human use of habitats harboring the northern spotted owl (Strix occidentalis caurina), revealing how biologists and policy scholars have argued for divergent roles of scientists within policy debates, and how debates between scientists engaged in policy-relevant research reveal undisclosed value judgments about communication of science beyond its role as a source of description (observation, measurement, analysis, and inference). Our second case concerns protection and use of endangered gray wolves (Canis lupus) and shows how undisclosed value judgments distorted the science behind a government policy. Finally, we draw from the literature of multiple disciplines and wildlife systems to recommend several improvements to the standards of transparency in applied research in natural resource management. These recommendations will help to prevent value-based distortions of science that can result in unsustainable uses and eventual extinctions of populations. We describe methods for communicating about values that avoid commingling factual claims and discuss approaches to communicating science that do not perpetuate the misconception that science alone can dictate policy without consideration of values. Our remedies can improve transparency in both expert and public debate about preserving and using natural resources, and thereby help prevent non-human population declines worldwide.

  6. f

    Demographic and clinical details of study population.

    • plos.figshare.com
    xls
    Updated Apr 16, 2025
    + more versions
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    Sarah Schlaeger; Mark Mühlau; Guillaume Gilbert; Irene Vavasour; Thomas Amthor; Mariya Doneva; Aurore Menegaux; Maria Mora; Markus Lauerer; Viola Pongratz; Claus Zimmer; Benedikt Wiestler; Jan S. Kirschke; Christine Preibisch; Ronja C. Berg (2025). Demographic and clinical details of study population. [Dataset]. http://doi.org/10.1371/journal.pone.0318415.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 16, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Sarah Schlaeger; Mark Mühlau; Guillaume Gilbert; Irene Vavasour; Thomas Amthor; Mariya Doneva; Aurore Menegaux; Maria Mora; Markus Lauerer; Viola Pongratz; Claus Zimmer; Benedikt Wiestler; Jan S. Kirschke; Christine Preibisch; Ronja C. Berg
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Demographic and clinical details of study population.

  7. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Rutuja Sonar Riya Patil; Rutuja Sonar Riya Patil (2025). Population dynamics and Population Migration [Dataset]. http://doi.org/10.5281/zenodo.15175736

Population dynamics and Population Migration

Explore at:
Dataset updated
Apr 8, 2025
Dataset provided by
Zenodo
Authors
Rutuja Sonar Riya Patil; Rutuja Sonar Riya Patil
Description

Population dynamics, its types. Population migration (external, internal), factors determining it, main trends. Impact of migration on population health.

Under the guidance of Moldoev M.I. Sir By Riya Patil and Rutuja Sonar

Abstract

Population dynamics influence development and vice versa, at various scale levels: global, continental/world-regional, national, regional, and local. Debates on how population growth affects development and how development affects population growth have already been subject of intensive debate and controversy since the late 18th century, and this debate is still ongoing. While these two debates initially focused mainly on natural population growth, the impact of migration on both population dynamics and development is also increasingly recognized. While world population will continue growing throughout the 21st century, there are substantial and growing contrasts between and within world-regions in the pace and nature of that growth, including some countries where population is stagnating or even shrinking. Because of these growing contrasts, population dynamics and their interrelationships with development have quite different governance implications in different parts of the world.

1. Population Dynamics

Population dynamics refers to the changes in population size, structure, and distribution over time. These changes are influenced by four main processes:

Birth rate (natality)

Death rate (mortality)

Immigration (inflow of people)

Emigration (outflow of people)

Types of Population Dynamics

Natural population change: Based on birth and death rates.

Migration-based change: Caused by people moving in or out of a region.

Demographic transition: A model that explains changes in population growth as societies industrialize.

Population distribution: Changes in where people live (urban vs rural).

2. Population Migration

Migration refers to the movement of people from one location to another, often across political or geographical boundaries.

Types of Migration

External migration (international):

Movement between countries.

Examples: Refugee relocation, labor migration, education.

Internal migration:

Movement within the same country or region.

Examples: Rural-to-urban migration, inter-state migration.

3. Factors Determining Migration

Migration is influenced by push and pull factors:

Push factors (reasons to leave a place):

Unemployment

Conflict or war

Natural disasters

Poverty

Lack of services or opportunities

Pull factors (reasons to move to a place):

Better job prospects

Safety and security

Higher standard of living

Education and healthcare access

Family reunification

4. Main Trends in Migration

Urbanization: Mass movement to cities for work and better services.

Global labor migration: Movement from developing to developed countries.

Refugee and asylum seeker flows: Due to conflict or persecution.

Circular migration: Repeated movement between two or more locations.

Brain drain/gain: Movement of skilled labor away from (or toward) a country.

5. Impact of Migration on Population Health

Positive Impacts:

Access to better healthcare (for migrants moving to better systems).

Skills and knowledge exchange among health professionals.

Remittances improving healthcare affordability in home countries.

Negative Impacts:

Migrants’ health risks: Increased exposure to stress, poor living conditions, and occupational hazards.

Spread of infectious diseases: Especially when health screening is lacking.

Strain on health services: In receiving areas, especially with sudden or large influxes.

Mental health challenges: Due to cultural dislocation, discrimination, or trauma.

Population dynamics is one of the fundamental areas of ecology, forming both the basis for the study of more complex communities and of many applied questions. Understanding population dynamics is the key to understanding the relative importance of competition for resources and predation in structuring ecological communities, which is a central question in ecology.

Population dynamics plays a central role in many approaches to preserving biodiversity, which until now have been primarily focused on a single species approach. The calculation of the intrinsic growth rate of a species from a life table is often the central piece of conservation plans. Similarly, management of natural resources, such as fisheries, depends on population dynamics as a way to determine appropriate management actions.

Population dynamics can be characterized by a nonlinear system of difference or differential equations between the birth sizes of consecutive periods. In such a nonlinear system, when the feedback elasticity of previous events on current birth size is larger, the more likely the dynamics will be volatile. Depending on the classification criteria of the population, the revealed cyclical behavior has various interpretations. Under different contextual scenarios, Malthusian cycles, Easterlin cycles, predator–prey cycles, dynastic cycles, and capitalist–laborer cycles have been introduced and analyzed

Generally, population dynamics is a nonlinear stochastic process. Nonlinearities tend to be complicated to deal with, both when we want to do analytic stochastic modelling and when analysing data. The way around the problem is to approximate the nonlinear model with a linear one, for which the mathematical and statistical theories are more developed and tractable. Let us assume that the population process is described as:

(1)Nt=f(Nt−1,εt)

where Nt is population density at time t and εt is a series of random variables with identical distributions (mean and variance). Function f specifies how the population density one time step back, plus the stochastic environment εt, is mapped into the current time step. Let us assume that the (deterministic) stationary (equilibrium) value of the population is N* and that ε has mean ε*. The linear approximation of Eq. (1) close to N* is then:

(2)xt=axt−1+bϕt

where xt=Nt−N*, a=f

f(N*,ε*)/f

N, b=ff(N*,ε*)/fε, and ϕt=εt−ε*

The term population refers to the members of a single species that can interact with each other. Thus, the fish in a lake, or the moose on an island, are clear examples of a population. In other cases, such as trees in a forest, it may not be nearly so clear what a population is, but the concept of population is still very useful.

Population dynamics is essentially the study of the changes in the numbers through time of a single species. This is clearly a case where a quantitative description is essential, since the numbers of individuals in the population will be counted. One could begin by looking at a series of measurements of the numbers of particular species through time. However, it would still be necessary to decide which changes in numbers through time are significant, and how to determine what causes the changes in numbers. Thus, it is more sensible to begin with models that relate changes in population numbers through time to underlying assumptions. The models will provide indications of what features of changes in numbers are important and what measurements are critical to make, and they will help determine what the cause of changes in population levels might be.

To understand the dynamics of biological populations, the study starts with the simplest possibility and determines what the dynamics of the population would be in that case. Then, deviations in observed populations from the predictions of that simplest case would provide information about the kinds of forces shaping the dynamics of populations. Therefore, in describing the dynamics in this simplest case it is essential to be explicit and clear about the assumptions made. It would not be argued that the idealized population described here would ever be found, but that focusing on the idealized population would provide insight into real populations, just as the study of Newtonian mechanics provides understanding of more realistic situations in physics.

Population migration

The vast majority of people continue to live in the countries where they were born —only one in 30 are migrants.

In most discussions on migration, the starting point is usually numbers. Understanding changes in scale, emerging trends, and shifting demographics related to global social and economic transformations, such as migration, help us make sense of the changing world we live in and plan for the future. The current global estimate is that there were around 281 million international migrants in the world in 2020, which equates to 3.6 percent of the global population.

Overall, the estimated number of international migrants has increased over the past five decades. The total estimated 281 million people living in a country other than their countries of birth in 2020 was 128 million more than in 1990 and over three times the estimated number in 1970.

There is currently a larger number of male than female international migrants worldwide and the growing gender gap has increased over the past 20 years. In 2000, the male to female split was 50.6 to 49.4 per cent (or 88 million male migrants and 86 million female migrants). In 2020 the split was 51.9 to 48.1 per cent, with 146 million male migrants and 135 million female migrants. The share of

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