📚 What Was Compared:

This study complements Dion, Sumner, and Mitchell (2018) by shifting focus from whether articles cite female-authored work to how often articles written by women are cited. The analysis examines citation counts for articles in the Dion et al. dataset, conditional on an article having at least one female author.

🔎 How the Analysis Was Done:

• Citation counts for articles in the Dion, Sumner, and Mitchell (2018) dataset were modeled as the outcome.
• Key controls included the publishing journal and the number of authors on an article.
• The approach isolates the relationship between having at least one female author and subsequent citation frequency while accounting for journal-level and coauthorship factors.

📈 Key Findings:

• Articles with at least one female author are cited no more or less often than articles without female authors once controls for publishing journal and author count are included.
• The number of authors is an important predictor: failing to control for author count can produce spurious correlations.
• The role of author count also raises the possibility that self-citation or compositional differences across author teams may explain at least part of the gender differences reported by Dion, Sumner, and Mitchell (2018).

💡 Why It Matters:

These results caution against interpreting raw gender differences in citation patterns as evidence of citation bias without adjusting for journal placement and team composition. Measuring gender disparities in scholarly impact requires careful controls for coauthorship and publication venue to avoid misleading conclusions.