“…More recently, norms have become easier to collect and score, and a number of factors have driven the need for norms on larger sets of items, in particular the use of techniques such as EEG and functional magnetic resonance imaging (fMRI) that require large sets of items if effects are to stand out from a background of noise, and the replication crisis, which suggests the use of larger sets of items (and participants) in all studies. For example, an event-related potential (ERP) study by Misersky, Majid, and Snijders (2019) used the large set of 400+ gender stereotype norms collected by Misersky et al (2014), which have also been used in a range of other studies (e.g., Lewis & Lupyan, 2020;Richy & Burnett, 2020;Mueller-Feldmeth, Ahnefeld, & Hanulikova, 2019;Gygax et al, 2019). Studies of the effect of emotional valence on word recognition times (Citron, Weekes, & Ferstl, 2012) and on ERP components during word recognition (Citron, Weekes, & Ferstl, 2013) used the Sussex Affective Word List (SAWL) with ratings on 525 words, and a more recent study by Chen et al (2015) used the alterative ANEW corpus (Affective Norms for English Words, Bradley & Lang, 1999), which has an even larger set of ratings, in this case for American English.…”