Threats to the health of our environment are numerous, ranging from air and water pollution to deforestation, overpopulation, and climate change. Much research in fields such as biology, earth science, and engineering is devoted to documenting, understanding, and attempting to mitigate the harm. The root cause of all such problems, however, is human behavior. As such, changes to human behavior—and the internal processes that drive them—are essential to solutions. Cognitive scientists therefore have a critical role to play in sustainability research and interventions (e.g., Jaipal, 2014; Weir, 2018, 2019).

Is the influence of language on attention previously found in controlled, single-task lab contexts reduced or absent whenother factors (i.e. goals) influence attention, as in everyday life? The current studies examined whether language effects oneye-movements and recall emerge in richer task conditions. Experiment 1 examined English speakers use of agentive/non-agentive language during scene description on memory for the agent, similar to Fausey and Boroditsky (2011) whilealtering scene complexity and adding eye-tracking. Experiment 2 contrasted the standard describe task with one moretypical of everyday scene processing: predicting what happens next. Eye-tracking results from Experiment 1 supportan influence of language on distribution of attention. However, the absence of a significant memory difference in bothexperiments suggests that the language effect is not robust enough to have a meaningful impact on memory in rich taskconditions. Ultimately, the data suggested even the original effects are difficult to obtain.

Semantic categories in the world's languages often reflect a historical process of chaining: A name for one referent is extended to a conceptually related referent, and from there on to other referents, producing a chain of exemplars that all bear the same name. The beginning and end points of such a chain might in principle be rather dissimilar. There is also evidence supporting a contrasting picture: Languages tend to support efficient, informative communication, often through semantic categories in which all exemplars are similar. Here, we explore this tension through computational analyses of existing cross-language naming and sorting data from the domain of household containers. We find (a) formal evidence for historical semantic chaining, and (b) evidence that systems of categories in this domain nonetheless support near-optimally efficient communication. Our results demonstrate that semantic chaining is compatible with efficient communication, and they suggest that chaining may be constrained by the functional need for efficient communication.