Shared understanding of color among sighted and blind adults

Empiricist philosophers such as Locke famously argued that people born blind might learn arbitrary color facts (e.g., marigolds are yellow) but would lack color understanding. Contrary to this intuition, we find that blind and sighted adults share causal understanding of color, despite not always agreeing about arbitrary color facts. Relative to sighted people, blind individuals are less likely to generate “yellow” for banana and “red” for stop sign but make similar generative inferences about real and novel objects’ colors, and provide similar causal explanations. For example, people infer that two natural kinds (e.g., bananas) and two artifacts with functional colors (e.g., stop signs) are more likely to have the same color than two artifacts with nonfunctional colors (e.g., cars). People develop intuitive and inferentially rich “theories” of color regardless of visual experience. Linguistic communication is more effective at aligning intuitive theories than knowledge of arbitrary facts.

Influence of causal language on causal understanding: A comparison between Swiss-German and Turkish

Young children have difficulties understanding untypical causal relations. While we know that hearing a causal description facilitates this understanding, less is known about what particular features of causal language are responsible for this facilitation. Here, we asked: (1) Do syntactic and morphological cues in the grammatical structure of sentences facilitate the extraction of causal meaning, and (2) do these different cues influence this facilitation to a different degree. We studied children learning either Swiss-German or Turkish, two languages which differ in their expression of causality. Swiss-German predominantly uses lexical causatives (e.g., schniidä (cut)), which lack a formal marker to denote causality. Turkish, alongside lexical causatives, uses morphological causatives, which formally mark causation (e.g., ye (eat) vs. yeDIr (feed)). We assessed 2.5- to 3.5-year-old children’s understanding of untypical cause-effect relations described with either non-causal language (e.g., Here is a cube and a car) or causal language using a pseudo-verb (e.g., lexical: The cube gorps the car). We tested n = 135 Turkish-learning (non-causal, lexical, and morphological conditions) and n = 90 Swiss-German-learning children (non-causal and lexical conditions). Children in both language groups performed better in the causal language condition(s) than the non-causal language condition. Further, Turkish-learning children’s performance in both the lexical and morphological conditions was similar to Swiss-German-learning children in the lexical condition, and did not differ from each other. These findings suggest that the structural cues of causal language support children’s understanding of untypical causal relations, regardless of the type of construction.

Towards ending the animal cognition war: a three-dimensional model of causal cognition

Debates in animal cognition are frequently polarized between the romantic view that some species have human-like causal understanding and the killjoy view that human causal reasoning is unique. These apparently endless debates are often characterized by conceptual confusions and accusations of straw-men positions. What is needed is an account of causal understanding that enables researchers to investigate both similarities and differences in cognitive abilities in an incremental evolutionary framework. Here we outline the ways in which a three-dimensional model of causal understanding fulfills these criteria. We describe how this approach clarifies what is at stake, illuminates recent experiments on both physical and social cognition, and plots a path for productive future research that avoids the romantic/killjoy dichotomy.

Monitoring social–ecological networks for biodiversity and ecosystem services in human-dominated landscapes

The demand the human population is placing on the environment has triggered accelerated rates of biodiversity change and created trade-offs among the ecosystem services we depend upon. Decisions designed to reverse these trends require the best possible information obtained by monitoring ecological and social dimensions of change. Here, we conceptualize a network framework to monitor change in social–ecological systems. We contextualize our framework within Ostrom’s social–ecological system framework and use it to discuss the challenges of monitoring biodiversity and ecosystem services across spatial and temporal scales. We propose that spatially explicit multilayer and multiscale monitoring can help estimate the range of variability seen in social–ecological systems with varying levels of human modification across the landscape. We illustrate our framework using a conceptual case study on the ecosystem service of maple syrup production. We argue for the use of analytical tools capable of integrating qualitative and quantitative knowledge of social–ecological systems to provide a causal understanding of change across a network. Altogether, our conceptual framework provides a foundation for establishing monitoring systems. Operationalizing our framework will allow for the detection of ecosystem service change and assessment of its drivers across several scales, informing the long-term sustainability of biodiversity and ecosystem services.

From the field into the lab: Causal approaches to the evolution of spatial language

There is striking variation in preferences for specific spatial linguistic strategies among different speech communities. Increasing evidence now suggests that this might not simply be a result of neutral drift, but rather a form of linguistic adaptation to the local social, cultural, or physical environment. Recent studies indicate that different factors like, e.g., topography, subsistence style, or bilingualism successfully predict the choice of spatial Frames of Reference (FoR) on linguistic and non-linguistic tasks. However, the exact causal relationships between these variables and the cultural evolutionary mechanisms that lead to selection of one FoR strategy over another are still not fully understood. In this paper, we argue that in order to arrive at a more mechanistic and causal understanding of the cultural evolution of spatial language, observations from descriptive fieldwork should be combined with experimental and computational methods. In such a framework, causal relationships between linguistic and non-linguistic variables (such as topography and FoR choice) can be isolated and empirically tested in order to shed light on how sociotopographic factors motivate the variation in spatial language we observe cross-linguistically.

The Chicken or the Egg? Causal Inference in Entrepreneurial Orientation–Performance Research

While entrepreneurial orientation (EO) correlates with many organizational phenomena, we lack convincing evidence of causal relationships within EO’s nomological network. We explore the challenges to establishing causal relationships with a systematic review of EO–performance research. We then use a simulation to illustrate how popular research designs in EO research limit our ability to make causal claims. We conclude by outlining the research design considerations to move from associational to causal EO–performance research. Our message is that while experiments may not be practical or feasible in many areas of organizational research, including EO, scholars can nevertheless move towards causal understanding.