di Gerlando v. Second Avenue Railroad
Opinion of the Court
Defendant moves to set aside as excessive a verdict of $10,000. Its counsel’s memorandum says: “The proposition before the court is the dollar value of a married woman of the social class of the plaintiff for the injuries and the pain and suffering incidental thereto.”
This court cannot subscribe to this. While courts in the past have held that a person’s social position had something to do with the amount of recoveries, this court refuses to follow any such illogical reasoning. Courts are established so that a respectable scrubwoman may receive just as large a verdict as any
This thirty-year old married woman, living with her husband, had been employed in a dress shop. She sustained a compound fracture of both the larger and the smaller of the two bones below the knee of the right leg, which necessitated two operations. The first was an open operation to try to get the bones together. For this there were two cuts, each three inches long, from which there are still permanent scars some four inches long by half an inch wide. About three square inches of muscle and tissue were cut out. The ends of the bones slipped and over-rode, which caused a shrinkage in the leg of plaintiff. The bones became bowed. She was in Bellevue Hospital fifty-three days, during which time the pieces of bone had not united. Blood and pus came from the heel, which caused an infection of the heel. Five months later the bones had not knit, and with a brace made necessary by the accident she had to go to the hospital to give birth to a child. After the birth of the child plaintiff was confined to her home for some months. At the end of three years from the accident there was still .a shortening of one inch in the right leg. For years after the accident the shortening was three-quarters of an inch. There was evidence of permanent injury and deformity.
The motion to set aside the verdict and for a new trial is denied.
Case-law data current through December 31, 2025. Source: CourtListener bulk data.