Member Webinar: Disparate Outcomes: A closer look at NALP's Class of 2024 - NALP (Live Webinar)
-
Register
- Non-member - $50
- Faculty Member - Free!
Each year, NALP’s Employment Report and Salary Survey provides the most comprehensive picture of the legal employment market for new law graduates. The Class of 2024 data tell a compelling story — one marked by both progress and persistent disparities in outcomes based on law school size, region, race/ethnicity, and gender.
In this member-exclusive webinar, NALP’s research team will unpack the findings and discuss the implications for career services professionals, legal employers, and policymakers. Participants will gain insight into:
-
Employment trends by sector and geography, including shifts in private practice hiring;
-
Salary outcomes and the widening pay gaps across key demographic groups;
-
Public interest and government placement data, and what these trends suggest about access and equity;
-
Actionable strategies to use NALP data in advising, recruiting, and DEI planning.
Speakers:
Members of NALP’s Research Advisory Group and staff from NALP’s Research & Data team
Format: 60-minute live webinar with Q&A
Audience: NALP members, career services professionals, legal employers, and PD staff
Credit: Eligible for NALP Professional Development Credit
Dr Evelyn Dodge
Professor of Biomedical Data Science
Johns Hopkins University School of Medicine
Dr. Evelyn Dodge is a biomedical data scientist with over 20 years of experience applying machine learning and big data analytics to population health. Her research emphasizes ensuring equity and transparency in AI algorithms used for diagnostics and treatment planning. Dr. Dodge has collaborated with the World Health Organization and national health systems on AI ethics frameworks, and she currently leads a multi-institutional consortium examining bias mitigation strategies in medical AI. A passionate educator, she mentors graduate students and clinicians in responsible innovation, bridging technology and patient-centered care.
- No Relevant Financial Relationships
Dr. Dodge has disclosed no relevant financial relationships with ineligible companies.
Advisory/Consulting Disclosure
Dr. Dodge serves as an unpaid advisor on the World Health Organization’s Artificial Intelligence in Health Ethics panel. She has disclosed no relevant financial relationships with ineligible companies.
Dr Amy Smith
Associate Professor of Medicine
Department of Internal Medicine, University of California, San Francisco (UCSF)
Dr. Amy Smith is a physician and researcher specializing in clinical informatics and digital health. Her work focuses on integrating artificial intelligence and predictive analytics into electronic health records to support clinical decision-making and improve patient safety. Dr. Smith has led NIH-funded projects on machine learning models for early detection of sepsis and has published extensively on the ethical use of AI in clinical practice. She is a frequent speaker at international conferences on digital health innovation and serves on advisory panels shaping guidelines for responsible AI adoption in healthcare.
- No Relevant Financial Relationships
Dr. Smith has disclosed no relevant financial relationships with ineligible companies.
Research Funding Disclosure
Dr. Smith receives research funding from the National Institutes of Health (NIH) for studies related to clinical decision support. She has disclosed no relevant financial relationships with ineligible companies.
Key:
Complete
Next
Failed
Available
Locked