Millennials were the largest generation group in the United States in 2024, with an estimated population of ***** million. Born between 1981 and 1996, Millennials recently surpassed Baby Boomers as the biggest group, and they will continue to be a major part of the population for many years. The rise of Generation Alpha Generation Alpha is the most recent to have been named, and many group members will not be able to remember a time before smartphones and social media. As of 2024, the oldest Generation Alpha members were still only aging into adolescents. However, the group already makes up around ***** percent of the U.S. population, and they are said to be the most racially and ethnically diverse of all the generation groups. Boomers vs. Millennials The number of Baby Boomers, whose generation was defined by the boom in births following the Second World War, has fallen by around ***** million since 2010. However, they remain the second-largest generation group, and aging Boomers are contributing to steady increases in the median age of the population. Meanwhile, the Millennial generation continues to grow, and one reason for this is the increasing number of young immigrants arriving in the United States.

In 2024, Millennials were the largest generation group in the United States, making up about 21.81 percent of the population. However, Generation Z was not far behind, with Gen Z accounting for around 20.81 percent of the population in that year.

The statistic shows the number of people in the U.S. in 2011 and 2030, by generation. By 2030, the Millennial generation will have 78 million people whereas the Boomer generation will only have 56 million people in the United States.

In 2023, there were about 72.7 million Millennials estimated to be living in the United States, making them the largest generation group in the country. In comparison, there were 69.31 million Gen Z and 65.35 million Gen X estimated to be in the United States in that year.

Estimates of effective population size are critical for species of conservation concern. Genetic datasets can be used to provide robust estimates of this important parameter. However, the methods used to obtain these estimates assume that generations are discrete. We used simulated data to assess the influences of overlapping generations on estimates of effective size provided by the linkage disequilibrium method. Our simulations focus on two factors: the degree of reproductive skew exhibited by the focal species and the generation time, without considering sample size or the level of polymorphism at marker loci. In situations where a majority of reproduction is achieved by a small fraction of the population, the effective number of breeders can be much smaller than the per generation effective population size. The linkage disequilibrium in samples of newborns can provide estimates of the former size, while our results indicate that the latter size is best estimated using random samples of reproductively mature adults. Using samples of adults, the downwards bias was less than ~15% across our simulated life histories. As noted in previous assessments, precision of the estimate depends on the magnitude of effective size itself, with greater precision achieved for small populations.

In 2023, there were approximately ***** million millennials in the United Kingdom, making it the largest generational cohort at that time. Millennials surpassed the Baby Boomer generation as the largest generation for the first time in 2019. The two youngest generations, Gen Z and Gen Alpha, numbered approximately **** million, and *** million respectively. Gen X are, as of the most recent year, the second-largest generation in the UK at ***** million people, with their parent's generation, the Silent Generation, numbering around *** million people in the same year. There were estimated to be ****** people who belonged to the Greatest Generation, the parents of the Baby Boomer generation, who lived through major events such as the Great Depression and World War Two. Post-War Baby Boom The baby boomer generation was the largest generation for much of this period due to the spike in births that happened after the Second World War. In 1947, for example, there were over *** million live births in the United Kingdom, compared with just ******* live births just thirty years later in 1977. Members of this generation are typically the parents of millennials, and were the driving force behind the countercultural movement of the 1960s, due to their large numbers relative to older generations at the time. The next generational cohort after Boomers are Generation X, born between 1965 and 1980. This generation had fewer members than the Boomer generation for most of its existence, and only became larger than it in 2021. Millennials and Gen Z As of 2022, the most common single year of age in the United Kingdom in 2020 was 34, with approximately ******* people this age. Furthermore, people aged between 30 and 34 were the most numerous age group in this year, at approximately 4.67 million people. As of 2022, people in this age group were Millennials, the large generation who came of age in the late 1990s and early 2000s. Many members of this generation entered the workforce following the 2008 financial crash, and suffered through high levels of unemployment during the early 2010s. The generation that followed Millennials, Generation Z, have also experienced tough socio-economic conditions recently, with key formative years dominated by the COVID-19 pandemic, climate change, and an increasingly unstable geopolitical situation.

The Generations Study was conducted by infratest dimap on behalf of the Konrad Adenauer Foundation. During the survey period from 27.10.2022 to 16.01.2023, the German population aged 16 and over (German citizens) was surveyed in telephone interviews (CATI) on the following topics: political interest, satisfaction with democracy, position on various political issues and current voting intention. In addition, questions were used to identify divergent attitudes of the different age groups, e.g. on consumer and nutritional behavior, value orientations, perceived conflicts in society and the use of social media. The respondents were selected using a stratified random sample from an ADM selection frame including landline and mobile phone numbers (dual-frame sample). The study consists of two separate sample parts with an identical question program: a classic population sample with a standard design and an age group sample with a targeted equal distribution of interviews across seven age groups.
Climate-friendly consumer behaviour (avoid air travel, avoid travelling by car, pay attention to ecologically produced clothing, take care to behave in an environmentally and climate-friendly manner in everyday life); importance of various food characteristics (e.g. own and fresh preparation, balanced, healthy diet, vegetarian or vegan food, etc.); vegetarian diet; vegan diet; value orientations; perceived conflicts in various social groups (young and old, poor and rich, foreigners and Germans, urban and rural areas); interest in politics; satisfaction with democracy; political commitment; feelings of threat (e.g. due to climate change, immigration to Germany, economic crisis in Germany, tensions between Europe and Russia, tensions between Europe and China, xenophobia in Germany, etc.); Position statements on political issues (taxes and duties, immigration, climate); agreement with political statements (leadership positions in politics and business should be filled by a binding proportion of women/ people with a migration background, I can rely on my abilities in difficult situations, all in all, I think things are fair in Germany, today´s pensioners should get more pension, even if everyone has to pay more contributions); credibility of public service media such as ARD and ZDF; use of social media in general (e.g. WhatsApp, Facebook, etc.); use of these social media for political information; importance of gender-appropriate language in the media; party preference (Sunday question); alternative vote Sunday question; importance of various criteria for a satisfying job (e.g. high income, good promotion opportunities, secure job, etc.).

Demography: sex; age; age group; household size; number of persons in household under 16 years; employment; unemployment longer than 6 months; job security; religious denomination; religiosity; highest general educational qualification; aspired educational qualification; personal migration background or migration background of parents; income situation; willingness to participate in a qualitative interview.

Additionally coded were: Interview number; sample (standard, age cohorts); federal state; urban/rural districts; location size (political municipality size class; interview date; interview start time, interview duration; weighting factor; INKAR spatial unit; INKAR aggregate; INKAR: total net migration per 1000 inhabitants; inflows per 1000 inhabitants; 2017 Bundestag election: Share of votes CDU/CSU, SPD, Greens, FDP, other parties, Die Linke, and AfD; Share of settlement and transport area in percent of area, inhabitants per sq km of settlement and transport area; Hospital beds per 1000 inhabitants, doctors per 1000 inhabitants, share of inhabitants in municipality with a population density of less than 150 inhabitants per sq km; Share of population living in medium-sized centers; Share of population living in regional centers. Inhabitants per square kilometer; average car journey time to the nearest motorway junction in minutes; population-weighted linear distance to the nearest public transport stop with at least 20 departures per day; interview number qualitative interview.

This document provides a map of California and at each county a pie-chart depicts the proportion of electrical generation from small or large hydroelectric facilities. The second page provides the same county-level data except each county's total hydroelectric generation (gigwatt hours) is also given. The total statewide utility-scale electrical generation from these sources is depicted as well as the total contribution from each source. All data is from 2019.

Energy generation data and map are from the California Energy Commission for all power plants that have a nameplate capacity of 1MW or more. Small hydroelectric plants are designated as a renewable energy source if their nameplate capacity is more than 30MW, it is classified as a large hydroelectric plant. Counties without symbols either did not report data or had no utility-scale hydroelectric power generation. Data is from 2022 and is current as of July 10, 2023.

Energy generation data and map are from the California Energy Commission and include utility scale power plants, with a nameplate capacity of 1MW or more. Small hydroelectric plants are designated as renewable energy sources. Large hydroelectric plants are classified as nonrenewable. Counties without symbols either did not have plants reporting data or had no utility-scale hydroelectric power generation. Data is for2020 and is current as of July 15, 2022. For more information, contact Rebecca Vail at (916) 477-0738 or John Hingtgen at (916) 510-9747.

This document provides a map of California and at each county a pie-chart depicts the proportion of utility-scale electrical production capacity coming from small or large hydroelectric facilities. The second page provides the same county-level data except each county's total hydroelectric capacity (megawatts) is also given. The total statewide capacity generated from these sources is depicted as well as the total contribution from each source. All data is from 2012.

As of 2021, Millennials and Baby Boomers made up an equal share of the Australian population at around 21.5 percent each, making them the largest generational groups at the time. Those aged 75 years and over made up the smallest portion of the population, followed by Gen Alpha, or those aged 0 to 9 years at the time.

Gain in-depth insights into Next Generation Titrator Market Report from Market Research Intellect, valued at USD 550 million in 2024, and projected to grow to USD 800 million by 2033 with a CAGR of 5.0% from 2026 to 2033.

Variation in life histories influences demographic processes, from adaptive changes to population declines leading to extinction. Among life history traits, generation length offers a critical feature to forecast species’ demographic trajectories such as population declines (widely used by the IUCN Red List) and adaptability to environmental change over time. Therefore, estimates of generation length are crucial to monitor demographic stability or predict future changes in highly threatened organisms, particularly amphibians and reptiles, which are particularly threatened among vertebrates and for which uncertainty in future impacts remains high. Despite its importance, generation length for amphibians and reptiles is largely missing. Here, we aim to fill-in this gap by modeling generation lengths for amphibians, squamates and testudines as a function of species size, climate, life history, and phylogeny using generalized additive models and phylogenetic generalized least squares. We es..., , , # Generation length of the world's amphibians and reptiles

https://doi.org/10.5061/dryad.w0vt4b93t

Description of the data and file structure

Files and variables

File: amphibian_full_data.csv

Description:Â

Variables

• scientificName: (character) species binomial
• generation_length_y: (numeric) average generation length in years
• source_GL: (character) source of generation length
• generation_length_y.pgls: (numeric) average generation length in years predicted by PGLS
• generation_length_y.gam: (numeric) average generation length in years predicted by GAM
• Body_mass_g: (numeric) species body mass in grams, NAs represent missing data
• source_bodymass: (character) source of body mass, NAs represent missing data
• SVL_mm: (numeric) species snout-vent length in mm, NAs represent missing data
• source_SVL: (character) source of SVL, NAs represent missing data
• bio01: (numeric) annual temperature in °C
• bio04: (n...,

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