Firm Partner, Employment Law & Litigation and Human Resources, Counseling & Compliance specialist Dina M. Mastellone, Esq. will present at the New Jersey State Bar Association's 2023 Annual Meeting & Convention in Atlantic City, NJ on May 18th.
Ms. Mastellone's panel entitled, "State v Scott and What It May Mean to Your Labor and Employment Practice" is cosponsored by the Labor and Employment Law Section and will be an informative discussion about the ramifications of the State v. Scott decision which, for the first time, recognizes the role of implicit bias in police action. The Hon. Ronald Susswein will discuss his opinion as well as touch upon the training directive for New Jersey law enforcement and racial profiling. Ms. Mastellone and her co-panelists from the criminal bar and the employment bar will discuss the implications of State v. Scott in their respective practice areas and the impact it will have on existing and future cases.
For more information on the Annual Meeting & Convention and to register, please click here.
About The Event
The NJSBA Annual Meeting and Convention is "always the premiere annual event of the legal community and this year will be no exception." The NJSBA "looks forward to welcoming judges, lawyers and law clerks" to participate in their "educational seminars, as well as networking events and the annual installation of officers. Programming begins Wednesday, May 17 and continues through Friday, May 19, with the State of the Judiciary addresses that morning." Their "educational programming will cover a wide range of issues and practice areas, and will include bench-bar conferences. A Welcome Reception will kick off the social events on Wednesday" and they will "install the officers and trustees at a ceremony Thursday where they will express their thanks to NJSBA 2022 - 2023 President Jeralyn L. Lawrence and welcome NJSBA 2023 - 2024 President Timothy F. McGoughran."
Tags: Genova Burns LLC • Dina M. Mastellone • NJSBA • Employment Law & Litigation • Labor & Employment Law • Implicit Bias