In 2023, Mongolia had the highest share of women employed in science, technology, engineering, and mathematics (STEM) fields, with ** percent of all those employed in STEM fields being women. Belarus, Lesotho, the United States, and Barbados rounded out the top five countries employing the highest share of women in STEM fields.

Worldwide, there are more men than women working within science, technology, engineering, and mathematics (STEM) across all industries. In utilities, for instance, almost 40 percent of men were working with STEM, compared to just above 20 percent of women. Worldwide, only five countries had half or more of their female population working in STEM.

The proportion of male and female postsecondary enrolments, by International Standard Classification of Education (ISCED), institution type, Classification of Instructional Programs (CIP) 2021, STEM (science, technology, engineering and mathematics) and BHASE (business, humanities, health, arts, social science and education) groupings, status of student in Canada and age group.

The statistic displays the barriers or sources of harm to the career success of women working in a science, technology, engineering, or mathematics (STEM) field worldwide, as of 2016. At that time, ** percent of respondents felt that gender discrimination had hindered their careers.

About this dataset

Context

The dataset tabulates the population of Stem by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Stem. The dataset can be utilized to understand the population distribution of Stem by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Stem. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Stem.

Key observations

Largest age group (population): Male # 5-9 years (78) | Female # 10-14 years (91). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Stem population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Stem is shown in the following column.
• Population (Female): The female population in the Stem is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Stem for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Stem Population by Gender. You can refer the same here

In the school year 2020-21, ******* males were awarded STEM certifications in the United States. In contrast, the number of female STEM graduates was *******. STEM refers to science, technology, engineering, and mathematics.

From 2016 to 2019, the percentage of women working in a STEM (science, technology, engineering, and mathematics) field in the United Kingdom (UK) has increased from ** to ** percent, a total of ******* more women according to the source. While this is a significant increase in women within the STEM workforce, the percentage still remains disproportionately low, highlighting the gender gap in the STEM field.

Females awarded bachelor’s degrees in STEM fields.

About this dataset

Context

The dataset tabulates the population of Stem by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Stem across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 57.52% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Stem is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Stem total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Stem Population by Race & Ethnicity. You can refer the same here

On average, in 2022 in OECD countries, around 16 percent of female new entrants chose a STEM field. Six percent decided to pursue a career in natural sciences, mathematics, and statistics, three percent chose to study Information and Communication technologies (ICTs), and seven percent started a degree in engineering, manufacturing, and construction.

This dataset tracks annual two or more races student percentage from 2015 to 2023 for Urban Assembly Institute Of Math And Science For Young Women vs. New York and New York City Geographic District #13 School District

In Portugal, during the academic year 2022/2023, the share of men graduating from science, technology, engineering, and mathematics (STEM) courses was superior to the share of women for all study cycles. While 65 percent of STEM degrees' graduates were men, only 35 percent were women.

Encouraging women to pursue STEM employment is frequently touted as a means of reducing the gender wage gap. We examine whether the attributes of computer science workers–who account for nearly half of those working in STEM jobs–explain the persistent gender wage gap in computer science, using American Community Survey (ACS) data from 2009 to 2019. Our analysis focuses on working-age respondents between the ages of 22 and 60 who had a college degree and were employed full-time. We use ordinary least squares (OLS) regression of logged wages on observed characteristics, before turning to regression decomposition techniques to estimate what proportion of the gender wage gap would remain if men and women were equally rewarded for the same attributes–such as parenthood or marital status, degree field, or occupation. Women employed in computer science jobs earned about 86.6 cents for every dollar that men earned–a raw gender gap that is smaller than it is for the overall labor force (where it was 82 percent). Controlling for compositional effects (family attributes, degree field and occupation) narrows the gender wage gap, though women continue to earn 9.1 cents per dollar less than their male counterparts. But differential returns to family characteristics and human capital measures account for almost two-thirds of the gender wage gap in computer science jobs. Women working in computer science receive both a marriage and parenthood premium relative to unmarried or childless women, but these are significantly smaller than the bonus that married men and fathers receive over their childless and unmarried peers. Men also receive sizable wage premiums for having STEM degrees in computer science and engineering when they work in computer science jobs, advantages that do not accrue to women. Closing the gender wage gap in computer science requires treating women more like men, not just increasing their representation.

Financial overview and grant giving statistics of Stem Atlanta Women

Although the proportion of women in science, and in evolutionary biology in particular, has substantially increased over the last century, women remain underrepresented in academia, especially at senior levels. Moreover, their scientific achievements do not always receive the same level of recognition as do men’s, which can be reflected in a lower relative representation of women among invited speakers at conferences or specialized courses. Using announcements sent to the EvolDir mailing list between April 2016 and July 2017, and the symposium programs of three large evolutionary biology congresses held in summer 2017, we quantified the representation of women announced as invited speakers in conferences, congress symposia and specialized courses. We compared the proportion of invited women to a baseline estimated using membership data of the associated scientific societies, and surveyed organizers to investigate their influence and that of potential gender-ratio guidelines on the proportion of invited women. We find that the average proportion of invited women is comparable (conferences), significantly lower (specialized courses) or significantly higher (congress symposia) than the current baseline (32% women). It is positively correlated to the proportion of women among the organizers, and it is on average higher for events whose organizers considered gender when choosing speakers than for those whose organizers did not. To investigate the impact of Equal Opportunity guidelines, we then collected longitudinal data on the proportion of invited women at two series of conferences, covering the 2001-2017 period. The proportion of invited women is higher when Equal Opportunity guidelines are announced. Encouraging women to sit on organizing committees of scientific events, and the establishment of visible Equal Opportunity guidelines, thus could be ways to ensure higher number of invited female speakers in the future. Our results suggest that change, if desired, requires deliberate actions.

Historical Dataset of Urban Assembly Institute Of Math And Science For Young Women is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2011-2023),Total Classroom Teachers Trends Over Years (2009-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2011-2023),American Indian Student Percentage Comparison Over Years (2012-2023),Asian Student Percentage Comparison Over Years (2011-2023),Hispanic Student Percentage Comparison Over Years (2011-2023),Black Student Percentage Comparison Over Years (2011-2023),White Student Percentage Comparison Over Years (2011-2023),Two or More Races Student Percentage Comparison Over Years (2015-2023),Diversity Score Comparison Over Years (2011-2023),Free Lunch Eligibility Comparison Over Years (2013-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2013-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2011-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2011-2022),Graduation Rate Comparison Over Years (2014-2022)

Lithuania had the highest share of women employed in science and technology of all countries in Central and Eastern Europe in 2023. Romania had the smallest share with less than ** percent.

This dataset tracks annual white student percentage from 2011 to 2023 for Urban Assembly Institute Of Math And Science For Young Women vs. New York and New York City Geographic District #13 School District

This dataset tracks annual asian student percentage from 2011 to 2023 for Urban Assembly Institute Of Math And Science For Young Women vs. New York and New York City Geographic District #13 School District

We examined the number of women participating in symposia at the Society for Conservation Biology Annual Meetings for 1999, 2002, 2006, 2007, 2009, 2010, 2011, 2013, 2014 (Society for Conservation Biology Oceania chapter, included because of an all-female lead and impressive strides in diversity equity), and 2015. And analyzed the percentage of women organizing symposia and the percentage of women speaking at those symposia.