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COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK

Assistant Director of Admissions Systems and Operations

• School of Social Work
• Morningside
• Opening on: Aug 30 2024
• Job Type: Officer of Administration
• Regular/Temporary: Regular
• Hours Per Week: 35
• Standard Work Schedule: Hybrid Schedule (3 Days On-site)
• Salary Range: $65,000-$73,000

Position Summary

Columbia School of Social Work (CSSW) has been a leader in social work education and research since 1898. Our mission is to foster social work education, practice, and research that strengthen and expand the opportunities, resources, and capabilities of all persons to achieve their full potential and well-being. Our mission extends beyond the classroom, aiming to create a tangible impact on communities around the world.

Reporting to the Director of Admissions, the Assistant Director of Systems and Operations will manage the integrity of the admissions process flow from application through enrollment. The Assistant Director of Systems and Operations will generate admissions enrollment and prospect reports, maintain Technolutions Slate and assist with core admissions functions including application review and student engagement.

Responsibilities

• Serve as a user and administrator for various systems including Technolutions Slate, Columbia's Student Information System (SIS), and others as assigned.
• Partner with the Director and Associate Directors on the daily operations of Slate, . Including investigating and configuring Slate forms, communications, events, interviews, portals, workflows, data imports, automations, queries, and reports.
• Manage and resolve Slate troubleshooting requests from Admissions team and partnering offices. Build and update queries and reports for enrollment data analysis as requested, collaborating closely with the Associate Directors and Director.
• Administer annual updates and cycle preparation for the Slate application.
• Identify opportunities to optimize Slate usage for the Admissions office. Proactively ensure data integrity across all systems through diligent monitoring of reports and processes.
• Work with both internal and external stakeholders to review and manage data, as well as application imports and exports.
• Facilitate staff development, training, and onboarding in the use of Slate, SIS, and other relevant software and technologies. This might involve creating documentation, leading training sessions, and acting as the primary point of contact for any Slate-related issues
• Perform other duties as assigned.

Minimum Qualifications

Bachelor’s degree or its equivalent, and 2-4 years of related experience.

Other Requirements

• Proficiency using databases and creating queries.
• Demonstrated computer proficiency, including knowledge of office productivity software, preferably MS Office & Google Suite. 
• Technical ability and desire to learn, navigate, improve upon, and build systems.
• Ability to work independently in a dynamic environment with changing priorities and multiple responsibilities.
• Ability to establish and maintain effective working relationships with supervisors, staff members and vendors.
• Excellent written and oral communication skills.

Preferred Qualifications

• Working knowledge of the following language: SQL, XML, HTML, CSS, and JavaScript.
• Technical experience working with Technolutions Slate CRM and Liaison Outcomes.
• Experience with Columbia’s Student Information Systems (SIS).
• Prior experience in Higher Education or a similar educational setting is advantageous.

Equal Opportunity Employer / Disability / Veteran

Columbia University is committed to the hiring of qualified local residents.

Commitment to Diversity 

Columbia university is dedicated to increasing diversity in its workforce, its student body, and its educational programs. achieving continued academic excellence and creating a vibrant university community require nothing less. in fulfilling its mission to advance diversity at the university, columbia seeks to hire, retain, and promote exceptionally talented individuals from diverse backgrounds.  , share this job.

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Constance and Martin Silver Endowed Professor in Data Science and Prevention; Director, Constance and Martin Silver Center on Data Science and Social Equity

Areas of Expertise: Environmental influences and population-level interventions on obesity, weight-related behaviors and outcomes across the life course; Social and economic determinants and policies affecting physical, mental, and cognitive health in children, adults of all ages, and individuals with disabilities; Applications of artificial intelligence and data analytics for public health and social equity; Using data and statistical research methods to evaluate the effects of policies; Systematic review and meta-analysis to identify and appraise existing research.

Dr. Ruopeng An is a leading expert in obesity epidemiology and policy evaluation, a noted interdisciplinary data scientist, and an internationally recognized scholar in applying artificial intelligence to address public health disparities and social inequities.

He currently holds the Constance and Martin Silver Endowed Professorship in Data Science and Prevention and serves as the Director of the Constance and Martin Silver Center on Data Science and Social Equity. Dr. An is also an elected Fellow of the American Academy of Health Behavior and the American College of Epidemiology.

His research has been funded by various federal agencies and public/private organizations, including OpenAI, Abbott, and Amgen. Recognized as one of Elsevier’s top 2% most cited scientists, his work has been featured by major media outlets such as TIME , The New York Times , The Los Angeles Times , The Washington Post , Reuters , USA Today , Bloomberg , Forbes , The Atlantic , The Guardian , FOX, NPR , and CNN . He also serves on research grants and expert panels for the NIH, CDC, NSF, HHS, USDA, and the French National Research Agency.

Before joining NYU, Dr. An was the Faculty Lead in Public Health Sciences and Faculty Fellow for AI Innovations in Education at Washington University in St. Louis, where he also founded two certificate programs focused on artificial intelligence and data science.

Dr. An holds a PhD in Policy Analysis from the Pardee RAND Graduate School, a Master of Public Policy from the National Graduate Institute for Policy Studies, and a BA in Political Science and Public Administration from Peking University.

Recent Publications

An, R ., & Ji, M. (2023). Building Machine Learning Models to Correct Self-Reported Anthropometric Measures.  Journal of Public Health Management and Practice ,  29 (5), 671-674.

An, R ., Perez-Cruet, J., & Wang, J. (2024). We got nuts! use deep neural networks to classify images of common edible nuts.  Nutrition and Health ,  30 (2), 301-307.

An, R. , Perez-Cruet, J. M., Wang, X., & Yang, Y. (2024). Build Deep Neural Network Models to Detect Common Edible Nuts from Photos and Estimate Nutrient Portfolio.  Nutrients ,  16 (9), 1294.

An, R ., Yang, Y., Batcheller, Q., & Zhou, Q. (2023). Sentiment analysis of tweets on soda taxes.  Journal of Public Health Management and Practice ,  29 (5), 633-639.

Yang, Y., Lin, N., Batcheller, Q., Zhou, Q., Anderson, J., & An, R. (2023). Sentiment Analysis of Tweets on Menu Labeling Regulations in the US.  Nutrients ,  15 (19), 4269.

Huang, J., Guo, P., Zhang, S., Ji, M., & An, R. (2024). Use of Deep Neural Networks to Predict Obesity With Short Audio Recordings: Development and Usability Study.  JMIR Artificial Intelligence ,  3 , e54885.

An, R. , Batcheller, Q., Wang, J., & Yang, Y. (2023). Build neural network models to identify and correct news headlines exaggerating obesity-related scientific findings.  Journal of Data and Information Science ,  8 (3), 88-97.

An, R ., Byron Jr, C. W., Chen, C., & Xiang, X. (2023). A Field Test of Popular Chatbots’ Responses To Questions Concerning Negative Body Image.  Health Behavior Research ,  6 (1), 3.

An, R. , Yang, Y., Yang, F., & Wang, S. (2023). Use prompt to differentiate text generated by ChatGPT and humans.  Machine Learning with Applications ,  14 , 100497.

An, R. , Zheng, J., & Xiang, X. (2022). Projecting the influence of sugar-sweetened beverage warning labels and restaurant menu labeling regulations on energy intake, weight status, and health care expenditures in US adults: a microsimulation.  Journal of the Academy of Nutrition and Dietetics ,  122 (2), 334-344.

An, R. (2020). Projecting the impact of COVID-19 pandemic on childhood obesity in the US: A microsimulation model.  Journal of Sport and Health Science, 9 (4): 302-312.

Tainio, M., Andersen, Z. J., Nieuwenhuijsen, M. J., Hu, L., De Nazelle, A., An, R. , ... & de Sá, T. H. (2021). Air pollution, physical activity and health: A mapping review of the evidence.  Environment international ,  147 , 105954.

An, R. , Kang, H., Cao, L., & Xiang, X. (2022). Engagement in outdoor physical activity under ambient fine particulate matter pollution: A risk-benefit analysis.  Journal of Sport and Health Science ,  11 (4), 537-544.

Si, Y., Yang, Y., Wang, X., An, R. , Zu, J., Chen, X., ... & Gong, S. (2024).  Quality and Accountability of Large Language Models (LLMs) in Healthcare in Low-and Middle-Income Countries (LMIC): A Simulated Patient Study using ChatGPT  (No. 1472). GLO Discussion Paper.

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New York at Work Annual Report 2023-24

Previous years’ reports

We are thrilled to release the fourth annual New York at Work report from Cornell University’s New York State School of Industrial and Labor Relations (ILR). The report draws on ILR expertise, research-based data and policy analysis on a broad range of key issues affecting the state’s workers, unions, communities and employers. The report, which includes work from our Center for Applied Research on Work (CAROW), is intended to serve as an informative, accessible and relevant resource for policymakers and the public. We hope that you find it useful and we look forward to engaging with you to advance the important work that you do related to work, employment and labor.

For further assistance, please see the list of ILR Outreach institutes and programs with contact information at the end of the report.

Established by the New York State Legislature in 1945, ILR is guided by a commitment to social and economic justice and to improving the lives of New York’s working people. Consistent with our mission and to honor New York’s workers, the report is published annually around Labor Day.

Alexander J.S. Colvin, Ph.D. ’99 Kenneth F. Kahn ’69 Dean Martin F. Scheinman ’75, M.S. ’76, Professor

Ariel Avgar, Ph.D. ’08 David M. Cohen ’73 Professor of Labor Relations Senior Associate Dean for Outreach and Sponsored Research Director, Center for Applied Research on Work

Table of Contents

Buffalo co-lab, the status of child care in new york.

• Updated NYS Digital Equity Portal + Data Brief: New York State’s Recent Progress in, and Remaining Barriers to, Universal Broadband Internet Access
• Building Responsible Projects in New York City: Assessing the Impact of Prevailing Wage Benefits on Workers, Contractors and the New York City Economy
• Updated Cornell ILR Wage Atlas + Data Brief: New York State’s Minimum Wage is not Keeping Pace with the Rising Cost of Living

Center for Applied Research on Work

Empire state poll 2024, climate jobs institute.

• Building an Equitable, Diverse, and Unionized Clean Energy Economy: What We Can Learn From Apprenticeship
• Exploring the Conditions of the New Solar Workforce

Criminal Justice and Employment Initiative

Making fair chance hiring a reality through hr innovation, ithaca co-lab, labor and employment law program, building a diverse, fair and equitable new industry for nys, the worker institute, yang-tan institute on employment and disability , new york state subminimum wage demonstration project evaluation, about the new york state ilr school.

• Learn more about ILR Outreach and how to contact us.

Cathy Crieghton, Buffalo Co-Lab director; Steve Peraza, Buffalo Co-Lab senior research and policy associate; Russell Weaver, Buffalo Co-Lab research director.

Overview 

Buffalo Co-Lab researchers show that an initial influx of NYS funding helped to stabilize the child care industry during and immediately after the COVID pandemic. Since then, however, there has been little progress in the availability of and accessibility to child care in NYS. Instead, research shows an unevenly changing child care landscape, with minor gains in aggregate capacity over the past 2.5 years, but meaningful losses in many areas across the state, especially in upstate counties and low-income communities, where child care deserts and near-deserts already existed.

In addition to showing the bleak economic status of the child care industry in NYS, this report showcases one of the proposed solutions for the child care crisis: a workforce compensation fund (rather than temporary wage stabilization grants). The compensation fund would raise pay for workers in the industry to attract and retain new child care professionals.

Key Findings 

• Policy changes in the 2021-2022 NYS budget have had uneven results across NYS. 
• Child care workers remain underpaid and undervalued.
• Lack of access to affordable child care takes New York workers out of the economy.
• Child care capacity is ticking up, but industry diversity is in decline.
• A child care compensation fund would raise wages for all child care workers.
• Child care’s economic return on investment is high.

Recommendations

To improve wages among child care workers, the New York State Child Care Compensation Fund will institute a state-provider partnership to ensure that child care workers receive pay commensurate with other early childhood educators in the state. Per the Buffalo Co-Lab’s analysis, if the model called for a minimum wage of $23.55 in the industry, then the total cost of raising wages for all [non-self-employed] child care workers would be nearly $800 million per year (for wage supports only, not including the cost of fringe benefits).

Research Impact

The median annual salary for child care workers in NYS is approximately $33,000 per year for a full-time employee. The median wage for workers in NYS is approximately $54,000. The proposed fund will correct this injustice and properly recognize child care workers as educators who deserve wages at parity with public school teachers, as proposed in the Universal Child Care Act for New York State, Senate Bill S3245. By creating the Child Care Compensation Fund, NYS would ensure a more equitable wage for child care workers and help address the severe child care shortage in Erie County and other regions with similar child care industry needs. 

Read full report

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Updated NYS Digital Equity Portal + Data Brief: Toward Digital Equity

Russell Weaver, ILR Buffalo Co-Lab research director

Recent updates made by the ILR Buffalo Co-Lab to the New York State Digital Equity Portal shows that the number of New York households with high-speed internet access rose from 725,000 to 1.3 million between 2017 and 2022. But, much of that increase comes exclusively from cellular plans, which could mean that as many as 1.5 million households remain “underconnected.” 

Key Findings

Drawing on data from the Digital Equity Portal, this report shows that: 

• Nearly a quarter-million households still lack any type of high-speed internet connection. 
• An additional 810,000 households can only access the internet through cellular data plans, bringing the total number of potentially “underconnected” households to more than 1.5 million.
• There is reason to believe that insufficient affordable access to multiple and diverse types of computing devices is keeping many households “underconnected” to broadband internet.
• Lack of at-home broadband subscriptions is a problem with multiple dimensions – including but not limited to lack of infrastructure, too few providers and unaffordable prices for local populations – that cut across the rural-urban gradient.
• Households headed by Black or African American and Hispanic or Latinx New Yorkers continue to have the lowest rates of broadband take up, and the groups’ take up rates are falling farther behind statewide averages.
• Income still appears to be the ultimate arbiter of whether a household can access a broadband internet subscription.

Based on the data brief, two immediate targets for digital inclusion activities in NYS are to:

• Design and fund programs that make it easier for households to acquire internet-enabled devices that meet their computing needs.
• Design and fund programs that deliver broadband subscriptions to households at no or almost no cost. Continuing to innovate in legal and regulatory spaces, and continuing to move toward a reconceptualization of broadband as a public good that should be universally accessible appear to be critical next phases of the charge toward digital equity in NYS and across the globe.

This research made use of a statewide New York State Digital Equity Portal that has been fully revamped to allow users to produce on-the-fly infographics and fact sheets for various NYS locations, from ZIP codes and the smallest towns and villages to congressional districts and everywhere in between. The resources have been featured in multiple media outlets and the portal is a featured resource on the New York State Library’s digital equity resources guide. In May 2024, stakeholders from government, community-based organizations and academia joined a webinar introducing the new features of the statewide Digital Equity Portal (available on YouTube).

Related Information

• Digital Equity Portal home page
• Cornell Chronicle coverage of the portal and data brief
• Tech Times coverage of the digital equity portal updates
• What’s new in the NYS Wage Atlas and NYS Digital Equity Portal ( 2024 )? 

Assessing the Impact of Prevailing Wage Benefits on Workers, Contractors and the NYC Economy

Russell Weaver, Buffalo Co-Lab director of research; Anne Marie Brady, Worker Rights and Equity, Worker Institute, director of research.

Prevailing wage laws generate societal benefits through upward pressure on wages and benefits for non-union workers. They also protect local construction industries (workers, workers’ families and employers alike) from wage and benefit erosion, which could happen if external competition from lower-wage geographies enter the local market and persistently undercut local firms. This research report illustrates how, beyond these and related benefits, prevailing wage laws make union construction labor more cost-effective than non-union construction labor for prevailing wage jobs. 

Specifically, we ask whether a non-union firm’s total labor costs under the new New York City prevailing wage law may exceed the total costs of their union counterpart if the former does not provide employees with bona fide fringe benefits packages at the same rate as the latter. This report investigates this possibility through a modeling exercise focused on labor costs for four selected trades (high-rise carpenters, cement and concrete laborers, cement masons and lathers), designed to compute wage, fringe and workers’ compensation costs related to constructing a 10-story, 150,000-square-foot building in New York City.

Although other cost elements such as materials, technology and profits might not be characterized by similar patterns, the results show that union labor cost savings can be substantial. The scenarios analyzed for just four trades working to construct a 10-story building show that savings may lie between $600,000 and $800,000. Factoring in additional trades, those figures could easily climb to more than $1 million.

Through a combination of (1) robust apprenticeship programs, (2) widespread, generous provision of collectively bargained benefits that help defray workers’ compensation costs and (3) advantages in safety and experience, union bidders on prevailing wage projects are likely to face lower labor costs than their non-union competitors.

Prevailing wage laws impacts include: 

• Increasing the supporting union firms’ ability to take on, train and pay new apprentices will pave the way for a future experienced, high-quality workforce.
• Giving those firms more capacity to hire additional qualified workers at journey and provisional levels, thereby putting upward pressure on union density in the industry. 
• Putting pressure on non-union firms to raise wages and benefits to more competitive levels with their union counterparts. 

Insofar as prevailing wage laws contribute to stronger unions and better-compensated workers, they are “high road” policies that can lead to greater shared prosperity not only for individuals and their families, but in local economies more broadly over time.

Cornell ILR Prevailing Wage Calculator

Updated Cornell ILR Wage Atlas + Data Brief

Russel Weaver; ILR Buffalo Co-Lab research director; Ian Greer, Ithaca Co-Lab director, ILR research professor

Released alongside the sweeping updates made to the Cornell ILR Wage Atlas in spring 2024, New York State’s Minimum Wage is not Keeping Pace with the Rising Cost of Living examines the expected impacts of various potential minimum wage targets on aggregate earnings. The brief finds that a productivity-adjusted minimum wage has the potential to substantially increase disposable income, consumer spending, and, consequently, jobs throughout the state’s economy. 

• Analyses from the updated Cornell ILR Wage Atlas estimate that the implementation of a $21.25 minimum wage – the level being proposed by a statewide “Raise the Wage Act” – would help:
• 65.4% of workers in New York earn at or above their respective “living wage,” as determined by the MIT Living Wage Calculator. 
• Additionally, the combined increased earnings – $80.59 billion per year – would result in consumer demand and spending growth that could support the creation of more than 75,500 net jobs throughout the state.

Quantitative evidence from this project suggests that raising the NYS minimum wage to a level that intentionally accounts for the historic devaluation of low-wage work, and indexing that wage with productivity and inflation, is an equitable policy. It is also a practical one that could lead to net increases in earnings, consumer spending, and jobs throughout the economy. By passing something like the Raise the Wage Act, NYS has the potential to become a model “living wage state” to which the rest of the nation can aspire.

This research used a first-of-its-kind, statewide wage atlas that allows users to interactively estimate the number of workers who earn below various user-set “minimum wage” levels. 

The study's results have been cited by multiple media outlets, and the atlas has been referenced in Politico’s New York Playbook, by a NYS legislator as justification for a policy initiative, by investigative reporters covering the state’s agriculture industry and in various op-ed columns. The wage atlas and results also motivated a public webinar (available on YouTube) sponsored by CAROW. 

• Using the Wage Atlas: A Step-by-Step Guide
• Wage Atlas Home Page
• New Minimum Wage Tools for the 2024 Wage Atlas
• “What is the Minimum Wage?”
• “What is a Living Wage?”
• “Living Wage Deep Dive”

Conducted by the Center for Applied Research on Work with authorship and contributions by Anne Marie Brady, Phumthep Bunnak, Anne DeCecco, Avalon Hoek Spaans, Michael Lenmark, Jillian Morley, Megan Thorsfeldt, Russell Weaver, and Zoë West.

Every year, researchers at the ILR School conduct the Empire State Poll to survey NYS residents about how work impacts their lives: Are they employed, do their wages meet their needs, how do costs of daily living impact their ability to work or the number of jobs they need to manage, do they feel like they can speak up at work, are they part of a union? Most importantly, how do these issues together shape what concerns them most about their future? With over 2,500 residents surveyed across the state, this poll provides a window into New Yorkers’ daily lives, needs and concerns related to labor and employment.

In this latest iteration of Cornell ILR’s Empire State Poll, New Yorkers have expressed concern with the cost of living, access to care services such as home-based care or affordable child care and their ability to work with unions to have a voice in their workplace. They also have strong views on how the state should use its power to create sustainable and equitable industries for the future. The lived experiences, views and goals of those who make up our state are critical to creating the successful policies of tomorrow.

Poll findings include:

Employment Opportunities Vary by Demographics and Worker Organization Status

• Over 60% of respondents are employed, but disparities exist across race and ethnicity. Of the New Yorkers either employed or unemployed but looking for work, 92% of white respondents reported being employed vs. 86% of Black or African American, 84% of Asian and 78% of Latinx respondents.
• When asked about economic opportunities for making a comfortable family living through good jobs and business development, over 60% of respondents said that there were “some” or “many” such opportunities, as opposed to “few.” More respondents who were part of a union or a worker association reported that they felt there were “some” or “many” such opportunities compared to respondents who were not part of any worker organization or association.

Cost of Living and Wages Impacting Workers

• Over 65% of respondents said cost of living is the most important issue facing their households. 
• More than a third of the 422 respondents who perform app-based gig work said their gig work income did not meet their household expenses. 

New Yorkers Need and Support Access to Child Care

• Over 40% of respondents said they or another adult in their household chose not to work due to child care. Most cited the high cost or lack of accessible, quality care; 23% said it was personal preference. Of the 40% of respondents who indicated that they forewent out-of-home employment due to child care needs: 52.8% identified as cis-women; 41.6% identified as cis-men; 3.3% identified as gender nonconforming or nonbinary; 1.5% did not provide a gender identity; and 0.8% identified as either transgender men or women.
• 74% of respondents support public funding of universal child care. 
• 72% of respondents support state investment in raising home care workers’ pay.

Union Representation

• 36% of employed respondents are members of a union. 
• When asked if their views on labor unions have shifted in the past year, only 14% of ESP respondents (371) said yes. Of those persons whose views have shifted, the majority (57%) were in a positive direction. 43% of such respondents said that their opposition to labor unions somewhat or strongly increased compared to the prior year.

New Yorkers Want Increased Climate Action

• 65% of those polled want increased action from labor, industry and government leaders on climate change. 

NYS faces a myriad of opportunities and challenges related to labor and employment and their impact on the communities in which we live. It is vital for policymakers to understand how New Yorkers experience changes in the cost of living, access to needed caregiving, and their experiences in the workplace to understand the concerns of New Yorkers as they make decisions that have broad implications for our state. The Empire State Poll offers a unique window into the daily lives of New Yorkers that can inform policy and practice. 

Building an Equitable, Diverse and Unionized Clean Energy Economy

Zach Cunningham, training and education associate; Melissa Shetler, senior training and education associate

The Climate Jobs Institute published a report examining apprenticeship readiness programs as a key tool in helping historically underserved communities access high-quality, unionized careers in the construction and clean energy sectors. By studying three exemplary programs in NYS and across the country, the authors provide a series of best practices and recommendations for practitioners, trade unions, employers, policymakers and philanthropic funders on how to expand apprenticeship readiness and build an equitable, diverse and unionized clean energy economy.

• Tackling the climate crisis has enormous job creation potential. 
• Building a robust, equitable clean energy economy requires high-quality jobs that provide pathways into the middle-class and expanded access for disadvantaged communities. Our current political moment creates an opportunity to accomplish these goals.
• Apprenticeship readiness programs explicitly serve underrepresented populations, creating pathways to high-quality, union jobs in clean energy. Because of this, apprenticeship readiness is key to seizing this moment and creating a just, sustainable economy.

Organized Labor

• Advocate for clean energy policies that prioritize ambitious climate action with strong labor and equity standards. 
• Establish direct entry relationships with apprenticeship readiness programs.

Construction Employers

• Work with organized labor to diversify the construction and clean energy workforce. 
• Support community workforce agreements with targeted and local hiring goals and high-quality union career opportunities. 

Community Organizations

• Advocate for ambitious climate action that includes strong labor and equity standards.  
• Partner with labor, employers and others to advance shared goals. 

Policymakers

• Set ambitious policies to drive clean energy investment and create high-quality jobs.
• Provide adequate, flexible funding for apprenticeship readiness programs to broaden impact. 

Private Funders

• Make long-term, flexible commitments to fund apprenticeship readiness programs and to include job quality metrics in funding streams. 
• Support capacity building for apprenticeship readiness programs to broaden impact. 

This research provides a series of best practices that apprenticeship readiness practitioners can use to grow their programs and increase effectiveness. Additionally, it outlines several measures key constituents – from organized labor, community organizations and construction employers to policymakers and private funders – can take to help apprenticeship readiness programs thrive and create high-quality, clean energy career opportunities for women, people of color and other underrepresented communities.

• View the report launch event

Read the report

Exploring the Conditions of the New York Solar Workforce

Avalon Hoek Spaans, assistant research director; Jillian Morley, research support specialist

Cornell ILR’s Climate Jobs Institute concluded a two-year exploratory study of working conditions in the NYS solar industry in April. Unlike much of the existing research on the solar workforce, based on what is known about adjacent industries or draws on employer-side data, this study directly surveyed solar workers, almost all of whom were non-union workers. The data from the survey indicates that NYS solar workers, especially workers of color, are dealing with challenges including piece rate pay, wage theft, lack of benefits, stimulant use and other issues.  

• About half of the workers surveyed were paid by the number of panels installed. 
• Pay was inequitable, with differences in wages and payment method (hourly versus annual pay) and by race/ethnicity.
• The majority of workers sampled did not receive benefits and for those who did receive benefits, disparities by race/ethnicity were reported.
• Black workers were still less likely to receive benefits when considering certifications/work type.
• The majority of respondents agreed stimulant use on solar worksites was a problem.
• 12% of the sample had been injured while working on a NYS solar site, and two-thirds of injured workers said the injuries were not reported to OSHA.
• Many workers in the sample lived outside of NYS, and 65% indicated that they had moved or relocated in order to work on a NYS solar worksite. This suggests that New York’s solar workers may be coming from out of state. 
• Some reported experiencing wage theft.  
• Additional research on the solar workforce must be conducted, with a particular focus on workers’ experiences.
• Future research should also prioritize building an accurate understanding of the solar workforce’s size, with the understanding that workers may have more than one solar employer.
• To meet NYS’s policy goals to address climate change and create equitable pathways into high-quality clean energy careers, policymakers should ensure that clean energy workers have access to good wages, benefits, health and safety training, equitable conditions and pathways to unionization. 

The study was the first to examine the solar industry and its worksites directly from workers’ perspectives. This is important because 40% of this sample reported working for more than one employer, calling into question the accuracy of industry worker counts and resulting research based on the existing employer-reported data. This report offers a first look at several previously unstudied issues facing solar workers in NYS.

Criminal Justice and Employment Initiative team members Matthew Saleh, research director; Jodi Anderson Jr., technological innovation director; Timothy McNutt, director.

Our research sought to answer two questions: What barriers to hiring people with criminal records exist within traditional HR practice, and how can HR innovation make Fair Chance hiring a reality?

Hundreds of private employers have signed “Fair Chance” hiring pledges expressing a commitment to hiring people with criminal records. Housing the second-highest number of Fortune 500 corporate headquarters nationally, NYS is an ideal locale for innovating private-sector practices that increase employment pathways for justice-impacted people. 

NYS has made strides toward providing legal protections to job seekers with criminal records, but people with criminal records continue to experience difficulty finding work in the state. The Criminal Justice and Employment Initiative surveyed human resources, talent acquisition and DEI personnel across diverse industries and sectors to assess how Fair Chance commitments and legal protections have translated to changes in hiring practices and third-party background checks. 

• 58% of respondents, including nearly all with 50-plus employees, used third-party credit reporting agencies such as Experian, Sterling and Checkr for background checks.
• 25% said they do not take steps to verify the accuracy of the reports.
• Responses highlighted serious issues with individualized assessment practices, even in NYS, where the assessments are legally required. 
• Only 59.8% considered a candidate’s “age at offense” and “time since offense,” despite those being the strongest predictors of successful reentry.
• Only 13.1% considered “rehabilitative factors,” such as counseling, community service, mentoring, microcredientials and hobbies during individualized assessments.
• With so much of the background check process being privatized and outsourced, employers must ensure that third-party agency practices align with Fair Chance commitments.
• Employers should take restorative factors into account because they strongly predict employment success by showing applicants beyond the lens of risk and liability.
• Employers should acknowledge restorative factors that show the progress and contributions of people with criminal records.
• Employers should acknowledge that the widespread use of HR management and applicant tracking software offers opportunities for innovative workflow customization regarding how candidates are screened, interviewed and delivered adverse action notices.

Research Impact 

The Cornell University Division of Human Resources is piloting the “Restorative Record” digital tool developed by the Criminal Justice and Employment Initiative. The tool invites applicants with criminal records to provide context and additional documentation to inform the individualized assessment process performed by HR. This helps ensure that every candidate has the chance to present a comprehensive picture of their capabilities. 

The Restorative Record profiles highlight a candidate’s core competencies, rehabilitative efforts and micro-credentials rather than focusing only on past criminal records. By leveraging evidence-based restorative factors, which are more accurate predictors of employability, the tool enables employers to make informed, equitable hiring decisions. The Criminal Justice and Employment Initiative recently received funding from SUNY’s Innovative Instruction Technology program to expand the Restorative Record into the SUNY system.

• Restorative Record Enters Beta Stage For Second Chance Month Story
• Video : CJEI's Restorative Record Project

Esta R. Bigler, director, Labor and Employment Law Program

In order to redress decades of harm caused by mass incarceration and the war on drugs, the Marijuana Regulation and Taxation Act that legalized adult-use cannabis in NYS established a goal to award 50% of business licenses to social and economic equity applicants. 

While the regulatory focus is on licensing and ownership, developing a new statewide industry offers a unique opportunity to envision a cannabis workforce that reflects these same goals. This industry has the potential to provide up to 60,000 high-quality careers with family-sustaining wages, upward mobility, worker empowerment and fair employment, leading to the building of generational wealth in historically underresourced communities.

With funding from the NYS Legislature, the Cannabis Workforce Initiative, a non-profit collaboration between the ILR School‘s Labor and Employment Law Program and the Workforce Development Institute, provides free and accessible training and educational resources to support pathways to jobs in the industry, prioritizing individuals and communities negatively impacted by cannabis prohibition. 

• Cannabis Workforce Initiative certificate holders, those who completed our 15-hour program, broadly reflect the social equity goals established in the Marijuana Regulation and Taxation Act.
• Statewide, 31% of certificate holders identify as Black or African American, 16% as Hispanic or Latino, 32% as white, 4% as Asian or other Pacific Islander and American Indian or Alaska Native and 9% as two or more races.
• 44% of certificate holders identify as women, 52% as men, and 3% as nonbinary or of another gender.
• In an industry with a wide range of in-demand transferable skills, 73% of certificate holders are over 30 and 18% are over 50.
• 70% of certificate holders do not have a college degree. 

To better understand the cannabis workforce makeup, the state Office of Cannabis Management, which has regulatory authority over the NYS adult-use market, should require as a condition of licensure regular reporting of workforce demographic data, including data by gender and race or ethnicity and by job category.

Program Impact

As more cannabis businesses open across the state, there is an increasing need for qualified job applicants ready to step in and help the industry thrive. The Cannabis Workforce Initiative certificate training builds a ready workforce for a new and growing market. 

Our core curriculum is the 15-hour Cannabis Career Exploration and Worker Rights Certificate Program , focused on the rights and responsibilities of employees and employers on topics ranging from wage and hour laws to preventing sexual harassment. The training informs applicants about industry positions, familiarizes them with industry needs, and equips them with workplace rights and the baseline knowledge needed by new employers in this rapidly growing industry. The demographic data of those seeking certificate training reflects the social equity goals of cannabis legalization and suggests NYS can succeed in building a diverse and equitable new industry from the ground up.

Yang-Tang Institute project team members Kaitlyn Jackson, policy associate; Ellice Switzer, Extension associate; Sandra Mosqueria Caminada, research associate; Jennifer Brooks, research associate; Leslie Shaw, research associate.

In 2022, the U.S. Department of Education’s Rehabilitation Services Administration awarded 14 state vocational rehabilitation agencies grants to decrease the use of subminimum wages and increase access to competitive integrated employment for people with disabilities. NYS is one of 14 states to receive this award, and the ILR School’s Yang-Tan Institute on Employment and Disability serves as New York’s program evaluator. 

Yang-Tan Institute evaluators drafted an evaluation plan that employs implementation science frameworks in its convergent mixed methods design. The plan will provide rich information on how implementation efforts impact performance measures. Evaluators will work closely with the national evaluator of the 14-state demonstration projects to ultimately inform federal efforts toward a responsible redesign of vocational supports for people with disabilities so more people with disabilities obtain competitive jobs and earn fair wages.

By examining established “drivers” of effective implementation and establishing rapid cycle inquiry-to-action protocols in demonstration sites, Yang-Tan Institute evaluators will be able to generate detailed locally and nationally significant recommendations for implementation and scale-up of services to reduce the numbers of people with disabilities earning subminimum wage in NYS. Evaluation results from the 14 states awarded demonstration projects could have a transformative impact on the system of disability employment supports in the U.S.

• Subminimum Wage to Competitive Integrated Employment
• Subminimum Wage for People with Disabilities: An Examination of Policies and Systems

About New York State ILR School

Established by the New York State Legislature in 1945, the New York State School of Industrial and Labor Relations at Cornell University is the world’s leading college of the applied social sciences focusing on work, labor and employment. It is guided by a commitment to social and economic justice and to improving the lives of New York’s working people.

With offices in New York City, Buffalo, and Ithaca, Cornell ILR Outreach provides research, reports, education and training for New York’s workers, unions, employers and government. It serves as a valuable resource for New York’s policymakers to advance equitable workplaces and well-informed public policy.

Key ILR Institutes and Programs Impacting New York State:

The Buffalo Co-Lab for Economic Development continues to play a leading role in Buffalo’s resurgence with a more equitable economy. By partnering with Western New York businesses, unions, government, education and community organizations, the Buffalo Co-Lab impacts New Yorkers statewide through workplace health and safety programs, economic development and labor research, immersion experiences for students and many other initiatives.

The Center for Applied Research on Work exists to connect research on work with the practice of putting it to use. We support member institutes and affiliated faculty and students in their efforts to take insights about work, labor and employment and share them broadly. We are uniquely placed to seed innovative research that puts academic study into practice.

The The Climate Jobs Institute is guiding New York and the nation’s transition to a strong, equitable and resilient clean energy economy that tackles the climate crisis, creates high-quality jobs, confronts race and gender inequality, and builds a diverse and inclusive workforce.

The Criminal Justice and Employment Initiative improves employment opportunities for people with criminal records by designing and delivering legal employment training to close information gaps, implement best practices, and integrate job seekers with criminal records into the workforce.

The Ithaca Co-Lab mobilizes students and research to tackle policy challenges in the local region. These include fighting unemployment, winning a living wage, overcoming disadvantage in the job market and organizing for worker voice in the workplace.

The Labor and Employment Law Program  examines the laws and policies that impact the workplace and offer educational programs. We provide labor and employment law education for job seekers, employees, employers, government agencies, community organizations and unions in support of the Cannabis Workforce Initiative.

The Scheinman Institute combines the academic depth of faculty in conflict/dispute resolution, employee relations and labor relations with the practical knowledge of leading practitioners in the field to provide intensive skill development for individuals and best practices for organizations.

The institute trains more students in mediation and arbitration than any other school in the United States.

Risa Lieberwitz Academic Director The Worker Institute [email protected]

The Worker Institute engages in research and education on contemporary labor issues to generate innovative thinking and solutions to problems related to work, economy and society. The institute brings together researchers, educators and students with practitioners in labor, business and policymaking to confront growing economic and social inequalities, in the interests of working people and their families. A core value of the Worker Institute is that collective representation and workers' rights are vital to a fair economy, robust democracy and just society.

Wendy Strobel Gower Thomas P. Golden Executive Director [email protected]

The Yang-Tan Institute works to advance the inclusion and full participation of people with disabilities in the workplace and community. Our research, training and technical resources expand knowledge about disability inclusion, leading to positive change.

Analyst/ Associate - US Credit Research, Consumer Retail

Job Description:

The Global Credit Research organization supports BofA Securities’ institutional sales and trading teams and their clients by providing insightful, objective, action-oriented analysis and recommendations designed to enable more informed investment decisions. Research Analysts are responsible for financial modeling/analysis, conducting primary research, writing detailed company & industry outlooks, engaging with corporate management teams and capital markets personnel, and servicing institutional clients. We are looking for a motivated and hardworking analyst/associate with strong attention to detail and writing skills to support the Consumer & Retail team covering investment grade and crossover credits (corporate bonds and credit default swaps).

Sample responsibilities include:

• Assembling historical financial models using SEC filings, press releases, and company conference calls
• Conducting financial & qualitative analysis on companies and their industry to support the investment thesis
• Learning fundamentals of industries and covered companies, staying on top of news flow and researching sector trends that may impact company/sector recommendations
• Writing short notes and lengthy reports on industries, company events & earnings, and/or trading and capital markets activity; written component may be as frequent as daily
• Initiating and building relationships with internal and external clients, communicating frequently with trading counterparts, and developing a network of contacts among companies and industries covered

Qualifications:

• Bachelor's degree OR equivalent years of experience. Progress toward or CFA charter holder a plus
• Finance, accounting and valuation coursework and/or work experience
• Strong financial modeling skills - ability to create and maintain financial models
• Strong attention to detail and organization skills; ability to exercise strong quality control over their own and the team's deliverables
• Ability to work in a fast-paced, time-sensitive environment and to prioritize competing demands
• Candidates must demonstrate a combination of academic aptitude, quantitative skills, professionalism, strategic and creative thinking, and distinguished written and verbal communications skills
• Client service-oriented; outgoing with strong personal presence
• Strong team and collaboration skills; able to operate effectively remotely when necessary
• A passion and interest in the capital markets, and ability to learn and use a wide range of market data sources
• Intellectual curiosity required for success in research
• Highly motivated with a drive to succeed
• Good judgment, common and business sense

Hours Per Week:

Weekly Schedule:

Referral Bonus Amount:

Hours Per Week: 

Learn more about this role

JR-24034984

Manages People: No

New York pay range:

$110,000 - $175,000 annualized salary, offers to be determined based on experience, education and skill set.

Discretionary incentive eligible

This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors, the performance and contributions of their line of business and/or group; and the overall success of the Company.

This role is currently benefits eligible . We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.

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Key things to know about U.S. election polling in 2024

Confidence in U.S. public opinion polling was shaken by errors in 2016 and 2020. In both years’ general elections, many polls underestimated the strength of Republican candidates, including Donald Trump. These errors laid bare some real limitations of polling.

In the midterms that followed those elections, polling performed better . But many Americans remain skeptical that it can paint an accurate portrait of the public’s political preferences.

Restoring people’s confidence in polling is an important goal, because robust and independent public polling has a critical role to play in a democratic society. It gathers and publishes information about the well-being of the public and about citizens’ views on major issues. And it provides an important counterweight to people in power, or those seeking power, when they make claims about “what the people want.”

The challenges facing polling are undeniable. In addition to the longstanding issues of rising nonresponse and cost, summer 2024 brought extraordinary events that transformed the presidential race . The good news is that people with deep knowledge of polling are working hard to fix the problems exposed in 2016 and 2020, experimenting with more data sources and interview approaches than ever before. Still, polls are more useful to the public if people have realistic expectations about what surveys can do well – and what they cannot.

With that in mind, here are some key points to know about polling heading into this year’s presidential election.

Probability sampling (or “random sampling”). This refers to a polling method in which survey participants are recruited using random sampling from a database or list that includes nearly everyone in the population. The pollster selects the sample. The survey is not open for anyone who wants to sign up.

Online opt-in polling (or “nonprobability sampling”). These polls are recruited using a variety of methods that are sometimes referred to as “convenience sampling.” Respondents come from a variety of online sources such as ads on social media or search engines, websites offering rewards in exchange for survey participation, or self-enrollment. Unlike surveys with probability samples, people can volunteer to participate in opt-in surveys.

Nonresponse and nonresponse bias. Nonresponse is when someone sampled for a survey does not participate. Nonresponse bias occurs when the pattern of nonresponse leads to error in a poll estimate. For example, college graduates are more likely than those without a degree to participate in surveys, leading to the potential that the share of college graduates in the resulting sample will be too high.

Mode of interview. This refers to the format in which respondents are presented with and respond to survey questions. The most common modes are online, live telephone, text message and paper. Some polls use more than one mode.

Weighting. This is a statistical procedure pollsters perform to make their survey align with the broader population on key characteristics like age, race, etc. For example, if a survey has too many college graduates compared with their share in the population, people without a college degree are “weighted up” to match the proper share.

How are election polls being conducted?

Pollsters are making changes in response to the problems in previous elections. As a result, polling is different today than in 2016. Most U.S. polling organizations that conducted and publicly released national surveys in both 2016 and 2022 (61%) used methods in 2022 that differed from what they used in 2016 . And change has continued since 2022.

One change is that the number of active polling organizations has grown significantly, indicating that there are fewer barriers to entry into the polling field. The number of organizations that conduct national election polls more than doubled between 2000 and 2022.

This growth has been driven largely by pollsters using inexpensive opt-in sampling methods. But previous Pew Research Center analyses have demonstrated how surveys that use nonprobability sampling may have errors twice as large , on average, as those that use probability sampling.

The second change is that many of the more prominent polling organizations that use probability sampling – including Pew Research Center – have shifted from conducting polls primarily by telephone to using online methods, or some combination of online, mail and telephone. The result is that polling methodologies are far more diverse now than in the past.

(For more about how public opinion polling works, including a chapter on election polls, read our short online course on public opinion polling basics .)

All good polling relies on statistical adjustment called “weighting,” which makes sure that the survey sample aligns with the broader population on key characteristics. Historically, public opinion researchers have adjusted their data using a core set of demographic variables to correct imbalances between the survey sample and the population.

But there is a growing realization among survey researchers that weighting a poll on just a few variables like age, race and gender is insufficient for getting accurate results. Some groups of people – such as older adults and college graduates – are more likely to take surveys, which can lead to errors that are too sizable for a simple three- or four-variable adjustment to work well. Adjusting on more variables produces more accurate results, according to Center studies in 2016 and 2018 .

A number of pollsters have taken this lesson to heart. For example, recent high-quality polls by Gallup and The New York Times/Siena College adjusted on eight and 12 variables, respectively. Our own polls typically adjust on 12 variables . In a perfect world, it wouldn’t be necessary to have that much intervention by the pollster. But the real world of survey research is not perfect.

Predicting who will vote is critical – and difficult. Preelection polls face one crucial challenge that routine opinion polls do not: determining who of the people surveyed will actually cast a ballot.

Roughly a third of eligible Americans do not vote in presidential elections , despite the enormous attention paid to these contests. Determining who will abstain is difficult because people can’t perfectly predict their future behavior – and because many people feel social pressure to say they’ll vote even if it’s unlikely.

No one knows the profile of voters ahead of Election Day. We can’t know for sure whether young people will turn out in greater numbers than usual, or whether key racial or ethnic groups will do so. This means pollsters are left to make educated guesses about turnout, often using a mix of historical data and current measures of voting enthusiasm. This is very different from routine opinion polls, which mostly do not ask about people’s future intentions.

When major news breaks, a poll’s timing can matter. Public opinion on most issues is remarkably stable, so you don’t necessarily need a recent poll about an issue to get a sense of what people think about it. But dramatic events can and do change public opinion , especially when people are first learning about a new topic. For example, polls this summer saw notable changes in voter attitudes following Joe Biden’s withdrawal from the presidential race. Polls taken immediately after a major event may pick up a shift in public opinion, but those shifts are sometimes short-lived. Polls fielded weeks or months later are what allow us to see whether an event has had a long-term impact on the public’s psyche.

How accurate are polls?

The answer to this question depends on what you want polls to do. Polls are used for all kinds of purposes in addition to showing who’s ahead and who’s behind in a campaign. Fair or not, however, the accuracy of election polling is usually judged by how closely the polls matched the outcome of the election.

By this standard, polling in 2016 and 2020 performed poorly. In both years, state polling was characterized by serious errors. National polling did reasonably well in 2016 but faltered in 2020.

In 2020, a post-election review of polling by the American Association for Public Opinion Research (AAPOR) found that “the 2020 polls featured polling error of an unusual magnitude: It was the highest in 40 years for the national popular vote and the highest in at least 20 years for state-level estimates of the vote in presidential, senatorial, and gubernatorial contests.”

How big were the errors? Polls conducted in the last two weeks before the election suggested that Biden’s margin over Trump was nearly twice as large as it ended up being in the final national vote tally.

Errors of this size make it difficult to be confident about who is leading if the election is closely contested, as many U.S. elections are .

Pollsters are rightly working to improve the accuracy of their polls. But even an error of 4 or 5 percentage points isn’t too concerning if the purpose of the poll is to describe whether the public has favorable or unfavorable opinions about candidates , or to show which issues matter to which voters. And on questions that gauge where people stand on issues, we usually want to know broadly where the public stands. We don’t necessarily need to know the precise share of Americans who say, for example, that climate change is mostly caused by human activity. Even judged by its performance in recent elections, polling can still provide a faithful picture of public sentiment on the important issues of the day.

The 2022 midterms saw generally accurate polling, despite a wave of partisan polls predicting a broad Republican victory. In fact, FiveThirtyEight found that “polls were more accurate in 2022 than in any cycle since at least 1998, with almost no bias toward either party.” Moreover, a handful of contrarian polls that predicted a 2022 “red wave” largely washed out when the votes were tallied. In sum, if we focus on polling in the most recent national election, there’s plenty of reason to be encouraged.

Compared with other elections in the past 20 years, polls have been less accurate when Donald Trump is on the ballot. Preelection surveys suffered from large errors – especially at the state level – in 2016 and 2020, when Trump was standing for election. But they performed reasonably well in the 2018 and 2022 midterms, when he was not.

During the 2016 campaign, observers speculated about the possibility that Trump supporters might be less willing to express their support to a pollster – a phenomenon sometimes described as the “shy Trump effect.” But a committee of polling experts evaluated five different tests of the “shy Trump” theory and turned up little to no evidence for each one . Later, Pew Research Center and, in a separate test, a researcher from Yale also found little to no evidence in support of the claim.

Instead, two other explanations are more likely. One is about the difficulty of estimating who will turn out to vote. Research has found that Trump is popular among people who tend to sit out midterms but turn out for him in presidential election years. Since pollsters often use past turnout to predict who will vote, it can be difficult to anticipate when irregular voters will actually show up.

The other explanation is that Republicans in the Trump era have become a little less likely than Democrats to participate in polls . Pollsters call this “partisan nonresponse bias.” Surprisingly, polls historically have not shown any particular pattern of favoring one side or the other. The errors that favored Democratic candidates in the past eight years may be a result of the growth of political polarization, along with declining trust among conservatives in news organizations and other institutions that conduct polls.

Whatever the cause, the fact that Trump is again the nominee of the Republican Party means that pollsters must be especially careful to make sure all segments of the population are properly represented in surveys.

The real margin of error is often about double the one reported. A typical election poll sample of about 1,000 people has a margin of sampling error that’s about plus or minus 3 percentage points. That number expresses the uncertainty that results from taking a sample of the population rather than interviewing everyone . Random samples are likely to differ a little from the population just by chance, in the same way that the quality of your hand in a card game varies from one deal to the next.

The problem is that sampling error is not the only kind of error that affects a poll. Those other kinds of error, in fact, can be as large or larger than sampling error. Consequently, the reported margin of error can lead people to think that polls are more accurate than they really are.

There are three other, equally important sources of error in polling: noncoverage error , where not all the target population has a chance of being sampled; nonresponse error, where certain groups of people may be less likely to participate; and measurement error, where people may not properly understand the questions or misreport their opinions. Not only does the margin of error fail to account for those other sources of potential error, putting a number only on sampling error implies to the public that other kinds of error do not exist.

Several recent studies show that the average total error in a poll estimate may be closer to twice as large as that implied by a typical margin of sampling error. This hidden error underscores the fact that polls may not be precise enough to call the winner in a close election.

Other important things to remember

Transparency in how a poll was conducted is associated with better accuracy . The polling industry has several platforms and initiatives aimed at promoting transparency in survey methodology. These include AAPOR’s transparency initiative and the Roper Center archive . Polling organizations that participate in these organizations have less error, on average, than those that don’t participate, an analysis by FiveThirtyEight found .

Participation in these transparency efforts does not guarantee that a poll is rigorous, but it is undoubtedly a positive signal. Transparency in polling means disclosing essential information, including the poll’s sponsor, the data collection firm, where and how participants were selected, modes of interview, field dates, sample size, question wording, and weighting procedures.

There is evidence that when the public is told that a candidate is extremely likely to win, some people may be less likely to vote . Following the 2016 election, many people wondered whether the pervasive forecasts that seemed to all but guarantee a Hillary Clinton victory – two modelers put her chances at 99% – led some would-be voters to conclude that the race was effectively over and that their vote would not make a difference. There is scientific research to back up that claim: A team of researchers found experimental evidence that when people have high confidence that one candidate will win, they are less likely to vote. This helps explain why some polling analysts say elections should be covered using traditional polling estimates and margins of error rather than speculative win probabilities (also known as “probabilistic forecasts”).

National polls tell us what the entire public thinks about the presidential candidates, but the outcome of the election is determined state by state in the Electoral College . The 2000 and 2016 presidential elections demonstrated a difficult truth: The candidate with the largest share of support among all voters in the United States sometimes loses the election. In those two elections, the national popular vote winners (Al Gore and Hillary Clinton) lost the election in the Electoral College (to George W. Bush and Donald Trump). In recent years, analysts have shown that Republican candidates do somewhat better in the Electoral College than in the popular vote because every state gets three electoral votes regardless of population – and many less-populated states are rural and more Republican.

For some, this raises the question: What is the use of national polls if they don’t tell us who is likely to win the presidency? In fact, national polls try to gauge the opinions of all Americans, regardless of whether they live in a battleground state like Pennsylvania, a reliably red state like Idaho or a reliably blue state like Rhode Island. In short, national polls tell us what the entire citizenry is thinking. Polls that focus only on the competitive states run the risk of giving too little attention to the needs and views of the vast majority of Americans who live in uncompetitive states – about 80%.

Fortunately, this is not how most pollsters view the world . As the noted political scientist Sidney Verba explained, “Surveys produce just what democracy is supposed to produce – equal representation of all citizens.”

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Scott Keeter is a senior survey advisor at Pew Research Center .

Courtney Kennedy is Vice President of Methods and Innovation at Pew Research Center .

How do people in the U.S. take Pew Research Center surveys, anyway?

How public polling has changed in the 21st century, what 2020’s election poll errors tell us about the accuracy of issue polling, a field guide to polling: election 2020 edition, methods 101: how is polling done around the world, most popular.

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