A student essay on climate and economics can contain a dozen numbers in a single page. Some come from reliable agencies, some from a book like Klein's, and some from a video the student half remembers. Teachers outside the sciences often feel unqualified to judge which is which.

The good news is that you do not need to be a climate scientist to grade evidence well. You need a consistent way to check whether a number is sourced, whether it is used fairly, and whether it actually supports the claim. Those are writing skills, not science skills.

The bad news is that the temptation to skim past statistics is strong. A figure with a citation looks credible, even if the citation points to a blog. Building a short checklist keeps you honest without slowing you down.

This guide lays out a practical approach for English, social studies, and interdisciplinary instructors who want to score evidence use with confidence.

A Five-Question Evidence Check

Run through the same short list on every essay. It takes under two minutes per paper and covers the issues that most affect evidence scores. Over time, you will spot problems on first read.

• Is every statistic attached to a named source, not just "studies show" or "experts say"?
• Is the source one a reasonable reader would trust for this kind of claim?
• Does the number appear in the source as the student describes it, including the time frame and geography?
• Does the evidence actually support the specific claim, or only a nearby one?
• Does the student explain what the evidence means instead of leaving it to speak for itself?

Spot-Checking Without Doing It All

You cannot verify every statistic in every paper. Pick one or two per essay, ideally the ones the argument depends on most, and trace them to the source. If those hold up, extend some trust to the rest; if they do not, look more closely.

Tell students you will do this. Announcing a spot-check policy changes behavior more than any lecture on citation. Students who know a number might be checked tend to be more careful about where it came from.

Distinguishing Primary Data From Author Interpretation

Students who read Klein often cite her as if her book were the original source of every figure. In reality, a book like this draws on reports, studies, and interviews, and it layers the author's interpretation on top. A strong essay separates the data from the argument built on it.

Give credit when a student goes back to a cited report or explains that a claim is the author's reading of the evidence. That kind of source awareness is a real skill and worth rewarding explicitly in your rubric.

Making Evidence Feedback Repeatable

Evidence comments follow patterns: missing source, weak source, mismatch between claim and data, no explanation. Save a short comment for each and reuse them. Students respond well to clear, consistent language about what counts.

AI-assisted grading tools can flag places where a statistic appears without a source or where a claim lacks supporting evidence. Treat those flags as a starting point, then apply your own judgment about whether the essay's evidence really holds up.