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This working paper uses urban school district data to investigate whether including track indicators or accounting for classroom characteristics in the value-added model is sufficient to eliminate potential bias resulting from the sorting of students into academic tracks. Accounting for two classroom characteristicsâ[euro]"mean classroom achievement and the standard deviation of classroom achievementâ[euro]"may reduce bias for middle school math teachers, whereas track indicators help for high school reading teachers. However, including both of these measures simultaneously reduces the precision of the value-added estimates in this context. While these different specifications produce substantially different value-added estimates, they produce small changes in the tails of value-added distribution.