diff --git a/posts/zzz_DO_NOT_EDIT_the__tensio.../the__tension_of__high-_performance__computing:__reproducibility_vs.__parallelization.qmd b/posts/zzz_DO_NOT_EDIT_the__tensio.../the__tension_of__high-_performance__computing:__reproducibility_vs.__parallelization.qmd
index 09d7dbc8..ea4540b8 100644
--- a/posts/zzz_DO_NOT_EDIT_the__tensio.../the__tension_of__high-_performance__computing:__reproducibility_vs.__parallelization.qmd
+++ b/posts/zzz_DO_NOT_EDIT_the__tensio.../the__tension_of__high-_performance__computing:__reproducibility_vs.__parallelization.qmd
@@ -302,7 +302,7 @@ trying for maintaining control and reproducibility.
 This blog post has hopefully increased your intuition about the challenges that 
 may arise when incorporating HPC into your work. By understanding these 
 complexities, you’ll be better positioned to make informed decisions about the 
-trade-offs—such as balancing performance and reproducibility — that are most
+trade-offs—such as balancing performance and reproducibility—that are most
 relevant to your specific case. As your computations scale, finding the right
 balance between efficiency, accuracy, and reproducibility will be crucial for 
 the success of your projects.