People v. Benoit
Opinion of the Court
Judgments, Supreme Court, New York County (Budd G. Goodman, J), rendered December 12, 2005, convicting defendants, after a jury trial, of robbery in the second degree, and sentencing defendant Benoit to a term of 6V2 years, and sentencing defendant Wilkinson to a term of four years, unanimously affirmed.
The court properly denied defendant Wilkinson’s motion to suppress identification testimony. The record supports the court’s finding that the lineup was not unduly suggestive. The police took effective measures to minimize any differences in appearances between Wilkinson and the lineup fillers, and Wilkinson was not singled out for identification (see People v Chipp, 75 NY2d 327, 336 [1990], cert denied 498 US 833 [1990]).
Both defendants’ ineffective assistance of counsel claims are unreviewable on direct appeal because they involve matters outside the record concerning matters of trial strategy (see People v Rivera, 71 NY2d 705, 709 [1988]; People v Love, 57 NY2d 998 [1982]). On the existing record, to the extent it permits review, we find that both Wilkinson and Benoit received effective assistance of counsel under the state and federal standards (see People v Benevento, 91 NY2d 708, 713-714 [1998]; see also Strickland v Washington, 466 US 668 [1984]). With respect to each defendant, the actions of counsel challenged on appeal constituted reasonable strategic decisions that did not prejudice their respective clients.
Both defendants’ challenges to the court’s jury instructions and its responses to inquiries from the deliberating jury are unpreserved (see People v Whalen, 59 NY2d 273, 280 [1983]; People v Williams, 297 AD2d 565 [2002], lv denied 99 NY2d 566 [2002]), and we decline to review them in the interest of justice. Were we to review these claims, we would find no basis for reversal.
We perceive no basis for reducing Benoit’s sentence. Concur— Tom, J.P., Mazzarelli, Friedman, Williams and Sweeny, JJ.
Case-law data current through December 31, 2025. Source: CourtListener bulk data.