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Syosset Recognizes Three Regeneron Science Talent Search Semifinalists
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Summary
Syosset High School presented three Regeneron Science Talent Search semifinalists—Elaine Liu, Grace Liu and Nikhil Shah—each summarizing their research on apology strategies, gender gaps in entrepreneurship, and racial disparities in federal sentencing.
The board opened the meeting by recognizing three Syosset High School students who are semifinalists in the Regeneron Science Talent Search.
Heather Miller, the high school's lead research facilitator, said the district submitted 34 projects this year and introduced the students to the board. "This year, we submitted 34 projects to the Regeneron Science Talent Search competition... this represents over 3,000 pages and hundreds of hours of work by our students and staff," she said.
Elaine Liu summarized her linguistic analysis of online apology strategies and reported that apologies that combined explanation and acknowledgement showed lower average comment growth on social platforms, a finding she said supports a role for specific apology strategies in limiting the spread of online condemnation.
Grace Liu presented a behavioral‑economics model and panel‑data analysis that identified aversion to uncertainty as a significant barrier to women becoming entrepreneurs; she noted low venture‑capital funding for female‑led startups and argued policy changes could reduce systemic uncertainty.
Nikhil Shah described a review of roughly 26,000 federal drug‑trafficking cases (U.S. Sentencing Commission data) and reported no meaningful relationship between judges' application of federal sentencing guidelines and racial‑disparity outcomes from 2015–2024, suggesting the guidelines have not reduced disparity in his sample.
Dr. Rogers congratulated the students and invited the public to a research symposium on June 4 where the district will showcase more student work.
Why it matters: student research recognition highlights district academic programs and showcases independent student inquiry at national competitions.
