This chapter will focus on the deep evolutionary history of the cognitive capacities underlying linguistic iconicity. The complex capacity for linguistic iconicity has roots in a more general cross-modal ability present throughout the animal kingdom, cross-modal transfer. Cross-modal transfer is the ability to make basic inferences about sensory properties of an object in multiple modalities based on experience from only one. This situates iconicity as a fundamentally cross-modal phenomenon; part of a broader, uniquely human cross-modal cognitive suite which includes relatively rare phenomena like synesthesia, alongside more ubiquitous phenomena like sensory metaphor and cross-modal correspondences. Evidence suggests the evolutionarily deep capacity for cross-modal transfer was honed into more sophisticated capacities underlying iconicity by an evolutionary ratchet of increased prosociality during human self-domestication. This period provided strong selective pressures for increasingly complex cross-sensory communication, and eventually, the predominantly arbitrary symbolic systems that underpin modern human language. This is a peer-reviewed preprint of the work below.Cuskley, Christine and Kees Sommer (forthcoming). The evolution of linguistic iconicity and the cross-modal cognitive suite. To appear in Olga Fisher, Kimi Akita, and Pamela Perniss (eds.), Oxford Handbook of Iconicity in Language. Oxford University Press: Oxford, UK.
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Energy policies are vital tools used by countries to regulate economic and social development as well as guarantee national security. To address the problems of fragmented policy objectives, conflicting tools, and overlapping initiatives, the internal logic and evolutionary trends of energy policies must be explored using the policy content. This study uses 38,277 energy policies as a database and summarizes the four energy policy objectives: clean, low-carbon, safe, and efficient. Using the TextCNN model to classify and deconstruct policies, the LDA + Word2vec theme conceptualization and similarity calculations were compared with the EISMD evolution framework to determine the energy policy theme evolution path. Results indicate that the density of energy policies has increased. Policies have become more comprehensive, barriers between objectives have gradually been broken, and low-carbon objectives have been strengthened. The evolution types are more diversified, evolution paths are more complicated, and the evolution types are often related to technology, industry, and market maturity. Traditional energy themes evolve through inheritance and merger; emerging technology and industry themes evolve through innovation, inheritance, and splitting. Moreover, this study provides a replicable analytical framework for the study of policy evolution in other sectors and evidence for optimizing energy policy design
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This paper links self-domestication and cross-modality, using a task intended to enhance participants’ prosociality and measuring their sensitivity to linguistic cross-modal associations.
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ion of verb agreement by hearing learners of a sign language. During a 2-year period, 14 novel learners of Sign Language of the Netherlands (NGT) with a spoken language background performed an elicitation task 15 times. Seven deaf native signers and NGT teachers performed the same task to serve as a benchmark group. The results obtained show that for some learners, the verb agreement system of NGT was difficult to master, despite numerous examples in the input. As compared to the benchmark group, learners tended to omit agreement markers on verbs that could be modified, did not always correctly use established locations associated with discourse referents, and made characteristic errors with respect to properties that are important in the expression of agreement (movement and orientation). The outcomes of the study are of value to practitioners in the field, as they are informative with regard to the nature of the learning process during the first stages of learning a sign language.
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Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.
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Does policy analysis exist outside the United States, or are the arts and crafts of policy analysis across the Atlantic a weakened and disoriented branch of the real thing, as the citations above seem to suggest? If policy analysis exists outside the United States-and from our point of interest in the Netherlands in particular-did it come about through a mere transplantation of theories, institutions, and methods originally developed in the United States; or has policy analysis outside the United States an autonomous value, contribution, and evolution? The different contributions and evolutions of policy analysis for instance appear in the various and changing connotations of the word “policy analysis” in national languages. In the Netherlands, for instance, the notion beleidsanalyse-the literal translation of policy analysis-is an ambiguous and somewhat problematic concept. It was fi rst introduced in the early 1970s as a deliberate and programmatic effort to rationalize public policy making in all public policy domains. During the early 1980s, the notion attracted a rather negative connotation, due to the failure of a governmental program by that name, the so-called committee for the development of policy analysis (COBA; de Commissie voor de Ontwikkeling van BeleidsAnalyse). Many now prefer to use equivalents such as applied policy research or research based advice instead. But as I shall demonstrate in this paper, the notion beleidsanalyse is making a remarkable comeback since the turn of the century while it is being used for fi nancial and performance accountability in the public sector. Thus, starting from the observation that different countries show different connotations and evolutions of policy analysis, I will analyze in this paper the evolution of policy analysis in the Netherlands on the basis of the following questions: What are the main characteristics (features) of policy analysis in the Netherlands? What changes, if any, have occurred in policy analysis in the Netherlands since the Second World War and what triggered these changes?
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Background Children with developmental language disorders (DLD) face ongoing challenges in language and communication, impacting their learning, literacy, social interactions, and emotional well-being. Speech and language therapy interventions have been shown to positively influence the language abilities and communication skills of children with DLD. However, these interventions are often not described in full detail, hindering effective implementation, replication, and the advancement of knowledge. Method We used the Template for Intervention Description and Replication (TIDieR) checklist and guide to describe the ENGAGE tool, which supports shared decision-making between parents and SLTs about communicative participation goals for children with DLD. The description was based on the development process, the ENGAGE user manual, and an interview study on its impact on SLT practice. Results We provided a detailed description of the ENGAGE intervention using the 12 items from the TIDieR checklist and guide, facilitating easier implementation and replication. Discussion Reflecting on our findings, we discussed the evolution of shared decision-making models, comparing Elwyn et al.'s (2012) model with the updated goal-based model by Elwyn & Vermunt (2020). The new model highlights the importance of collaborative goal setting in speech and language therapy. Our findings suggest that the ENGAGE tool aligns well with the latest theoretical advancements in shared decision-making.
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Abstract van prestentatie. According to Roy and Napier (2015), the earliest research on sign language interpreting dates to the mid-1970s. More recently we have acknowledged the need for research to be part of sign language interpreter (SLI) education programs (Winston, 2013). At present, educators feel an urgent need to embed research in their SLI programs with two goals: first, to firmly base their teaching in evidencebased practice, and second, to teach future interpreters how to continuously improve their practice
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OBJECTIVE: Ever since Engel's Biopsychosocial Model (1977) emotions, thoughts, beliefs and behaviors are accepted as important factors of health. The Brief Illness Perception Questionnaire (Brief IPQ) assesses these beliefs. Aim of this study was to cross-culturally adapt the Brief IPQ into the Brief IPQ Dutch Language Version (Brief IPQ-DLV), and to assess its face validity, content validity, reproducibility, and concurrent validity. METHODS: Beaton's guideline was used for cross-culturally adaptation. Face and content validity were assessed in 25 patients, 15 physiotherapists and 24 first-grade students. Reproducibility was established in 27 individuals with chronic obstructive pulmonary disease using Cohen's kappa coefficient (K(w)) and the Smallest Detectable Change (SDC). Concurrent validity was assessed in 163 patients visiting 11 different physical therapists. RESULTS: The Brief IPQ-DLV is well understood by patients, health care professionals and first-grade students. Reliability at 1 week for the dimensions Consequences, Concern and Emotional response K(w)>0.70, for the dimensions Personal control, Treatment control, Identity, K(w)<0.70. A time interval of 3 weeks, reliability coefficients were lower for almost all dimensions. SDC was between 2.45 and 3.37 points for individual measurement purposes and between 0.47 and 0.57 points for group evaluative measurement purposes. Concurrent validity showed significant correlations (P<.05) for four out of eight illness perceptions (IPs) dimensions. CONCLUSION: The face and content properties were found to be acceptable. The reproducibility and concurrent validity needs further investigated
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This study explores how households interact with smart systems for energy usage, providing insights into the field's trends, themes and evolution through a bibliometric analysis of 547 relevant literature from 2015 to 2025. Our findings discover: (1) Research activity has grown over the past decade, with leading journals recognizing several productive authors. Increased collaboration and interdisciplinary work are expected to expand; (2) Key research hotspots, identified through keyword co-occurrence, with two (exploration and development) stages, highlighting the interplay between technological, economic, environmental, and behavioral factors within the field; (3) Future research should place greater emphasis on understanding how emerging technologies interact with human, with a deeper understanding of users. Beyond the individual perspective, social dimensions also demand investigation. Finally, research should also aim to support policy development. To conclude, this study contributes to a broader perspective of this topic and highlights directions for future research development.
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