United States v. Tabitha Gann
United States v. Tabitha Gann
Opinion
Affirmed by unpublished PER CURIAM opinion.
Unpublished opinions are not binding precedent in this circuit.
Tabitha Lynn Gann appeals her 11-month sentence imposed upon revocation of her supervised release. On appeal, Gann asserts that her sentence is plainly unreasonable because the district court, in imposing a sentence at the top of the Sentencing Guidelines’ policy statement *250 range, unduly emphasized her attitude while on supervised release. We affirm.
“A .district court has broad discretion when imposing a sentence upon revocation of supervised release.” United States v. Webb, 738 F.3d 638, 640 (4th Cir. 2013). We will affirm a revocation sentence if it is within the applicable statutory maximum and not plainly unreasonable. United States v. Padgett, 788 F.3d 370, 373 (4th Cir. 2015). “Only if a revocation sentence is unreasonable must we assess whether it is plainly so.” Id.
Gann raises no procedural challenge to her sentence, and the record reveals no substantive error by the district court. A revocation sentence is substantively reasonable if the district court states a proper basis for concluding that the defendant should receive the sentence imposed, up to the statutory maximum. United States v. Crudup, 461 F.3d 433, 440 (4th Cir. 2006). Here, when considering the applicable sentencing factors and imposing sentence, the court fairly weighed Gann’s prior supervised release violations, history of substance abuse, and poor attitude on supervision, all of which relate to Gann’s history and characteristics. See 18 U.S.C. §§ 3563(a)(1), 3583(e) (2012). We conclude that Gann’s sentence is not unreasonable and therefore not plainly so.
Accordingly, we affirm the district court’s judgment. We dispense with oral argument because the facts and legal contentions are adequately presented in the materials before this court and argument would not aid the decisional process.
AFFIRMED.
Case-law data current through December 31, 2025. Source: CourtListener bulk data.