Hollis, G. (2019). Learning about things that never happened: a critique and refinement to the Rescorla-Wagner update rule when many outcomes are possible, Memory & Cognition, 1-16.
Hollis, G. (2019). The role of number of items per trial in best-worst scaling expriments. Behavior Research Methods, 1-29.
Westbury, C. & Hollis, G. (2019). Conceptualizing syntactic categories as semantic categories: Unifying POS identification and semantics using co-occurrence vector averaging. Behavior Research Methods, 1-28.
Westbury, C.F. & Hollis, G. (2018). Wriggly, squiffy, lummox, and boobs: What makes some words funny? The Journal of Experimental Psychology: General.
Hollis, G. & Westbury, C.F. (2018). When is best-worst best?: A comparison of best-worst scaling, numeric estimation, and rating scales for collection of semantic norms. Behavior Research Methods, 50(1), 115-133.
Westbury, C.F., Hollis, G., Sidhu, D., & Pexman, P. (2018). Weighing up the evidence for sound symbolism: Distributional properties predict cue strength. The Journal of Memory and Language, 99, 122-150.
Hollis, G. (2017). Estimating the average need of semantic knowledge from distributional semantic models. Memory and Cognition, 1-21.
Hollis, G. (2017). Scoring best/worst data in unbalanced, many-item designs, with applications to crowdsourcing semantic judgments. Behavior Research Methods, 1-19.
Hollis, G., & Westbury, C. (2016). The principals of meaning: Extracting semantic dimensions from co-occurrence models of semantics. Psychonomic bulletin & review, 23(6), 1744-1756.
Hollis, G., Westbury, C., & Lefsrud, L. (2016). Extrapolating Human Judgments from Skip-gram Vector Representations of Word Meaning. The Quarterly Journal of Experimental Psychology, 70(8), 1603-1619.
Westbury, C.F., Shaoul, C., Hollis, G., Smithson, L, Briesemeister, B.B., Hofmann, M.J., & Jacobs, A.M. (2013). Now you see it, now you don't: on emotion, context, and the algorithmic prediction of human imageability judgments. Frontiers in Psychology - Language Sciences, 4:991.
Wallot, S., Hollis, G., & van Rooij, M. (2013). Connected text reading and differences in text reading fluency in adult readers. PLOS ONE.
Van Orden, G.C., Hollis, G., & Wallot, S. (2012). The Blue Collar Brain. Frontiers in Physiology, 3, 207.
Hollis, G. (2010). The Role of Task Constraints in Ambiguity Resolution. Unpublished Dissertation, University of Cincinnati, Ohio, USA.
Hollis, G. (2009). Observed Interdependence of Cognition and Action: The Hand Says 'No' to ROWS. Unpublished Master's Thesis, University of Cincinnati, Ohio, USA.
Hollis, G., Kloos, H., & Van Orden, G.C. (2009). Origins of Order in Cognitive Activity. In S. Guastello, M. Koopmans, & D. Pincus (Eds.), Chaos and complexity in psychology: The theory of nonlinear dynamical systems, pp. 206-234. Boston: Cambridge University Press.
Westbury, C.F., & Hollis, G. (2007). Putting Humpty Together Again: Synthetic Approaches to Nonlinear Variable Effects Underlying Lexical Access. In Libben, G., & Jarema, G. The mental lexicon: Core perspectives. p. 7-30. Oxford, UK: Elsevier Press.
Hollis, G., & Westbury, C.F. (2006). NUANCE: Naturalistic University of Alberta Nonlinear Correlation Explorer. Behavioral Research Methods, Instruments, and Computers, 38, 8-23.
Hollis, G., Westbury, C.F., & Peterson, J.B. (2006). NUANCE 3.0: Using Genetic Programming to Model Variable Relationships. Behavioral Research Methods, Instruments, and Computers, 38, 218-228.
Westbury, C.F., Hollis, G., & Shaoul, C. (2006). LINGUA: The Language-Independent Neighbourhood Generator of the University of Alberta. The Mental Lexicon, 2: 271-284.
Westbury, C., & Hollis, G. (2005). In the tiniest house of time: Parametric constraints in language evolution models. Commentary on Steels, L. & Belpaeme, T. "Coordinating perceptually grounded categories through language: A case study in color". Behavioral and Brain Sciences, 28, 213-214.
Hollis, G. (2005). Mapping Out The Relationship Between 15 Variables Involved in Lexical Access. Unpublished Senior Thesis, University of Alberta, Alberta, Canada.