In large literature courses, the professor rarely grades every paper. Teaching assistants take sections of thirty or forty students, and each reads Their Eyes Were Watching God papers with their own instincts. Students in the same course can end up with quite different results for similar work.

The differences are not always about generosity. One TA may reward original arguments, another may prioritize clean structure, and a third may focus on grammar. Each is defensible, and together they create a grading system that feels arbitrary to students.

Consistency is a design problem more than a personnel problem. When graders share a rubric, examples, and regular check-ins, differences shrink. Without them, even excellent TAs drift.

The practices below help keep standards uniform without micromanaging. They take a few hours at the start of the term and pay off in fewer grade disputes. They also make the TA experience less stressful.

Start with a norming session

Before the first stack of papers arrives, ask every grader to score the same three or four essays, ranging from strong to weak. Compare results and discuss the gaps. The conversation exposes assumptions and gives the group a shared sense of what each level looks like.

• Share the rubric and prompt at least a week before grading begins
• Select anchor papers that illustrate each score level
• Have graders score independently, then discuss disagreements
• Revise rubric wording wherever graders interpreted a row differently
• Repeat with a fresh paper midway through the term

Spot checks during grading

Ask each TA to send a few graded papers to you or to a peer for review. Look at whether the scores match the comments and whether the feedback is specific. Early correction prevents a semester of uneven grading.

Track average scores by section. A large difference may be a sign of a calibration issue, though it can also reflect real differences in the students. Use it as a prompt for conversation, not a verdict.

Shared feedback tools

A comment bank helps TAs give consistent feedback on common issues. Compile the most frequent problems in Hurston papers, such as weak theses, unexplained quotations, and summary in place of analysis, and provide model comments for each. TAs can adapt them to the paper in front of them.

Encourage TAs to add to the bank. They often see patterns you miss. The resource improves each term.

Using AI as a second reader

AI grading tools can serve as a consistency check. A platform like GraideMind applies the same rubric to every paper, so comparing its output with a TA's scores can reveal where interpretations diverge. Human graders still make the final call.

Treat the comparison as a coaching opportunity, not an audit. When a TA's score differs from the tool's, talk through the paper together and decide which reading better reflects the rubric. Those conversations sharpen the whole team's judgment.