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Reading requires the assembly of cognitive processes across a wide spectrum from low-level visual perception to high-level discourse comprehension. One approach of unravelling the dynamics associated with these processes is to determine how eye movements are influenced by the characteristics of the text, in particular which features of the words within the perceptual span maximise the information intake due to foveal, spillover, parafoveal, and predictive processing. One way to test the generalisability of current proposals of such distributed processing is to examine them across different languages. For Turkish, an agglutinative language with a shallow orthography-phonology mapping, we replicate the well-known canonical main effects of frequency and predictability of the fixated word as well as effects of incoming saccade amplitude and fixation location within the word on single-fixation durations with data from 35 adults reading 120 nine-word sentences. Evidence for previously reported effects of the characteristics of neighbouring words and interactions was mixed. There was no evidence for the expected Turkish-specific morphological effect of the number of inflectional suffixes on single-fixation durations. To control for word-selection bias associated with single-fixation durations, we also tested effects on word skipping, single-fixation, and multiple-fixation cases with a base-line category logit model, assuming an increase of difficulty for an increase in the number of fixations. With this model, significant effects of word characteristics and number of inflectional suffixes of foveal word on probabilities of the number of fixations were observed, while the effects of the characteristics of neighbouring words and interactions were mixed.
In this paper, we move from the large strand of research that looks at evidence of climate migration to the questions: who are the climate migrants? and where do they go? These questions are crucial to design policies that mitigate welfare losses of migration choices due to climate change. We study the direct and heterogeneous associations between weather extremes and migration in rural India. We combine ERAS reanalysis data with the India Human Development Survey household panel and conduct regression analyses by applying linear probability and multinomial logit models. This enables us to establish a causal relationship between temperature and precipitation anomalies and overall migration as well as migration by destination. We show that adverse weather shocks decrease rural-rural and international migration and push people into cities in different, presumably more prosperous states. A series of positive weather shocks, however, facilitates international migration and migration to cities within the same state. Further, our results indicate that in contrast to other migrants, climate migrants are likely to be from the lower end of the skill distribution and from households strongly dependent on agricultural production. We estimate that approximately 8% of all rural-urban moves between 2005 and 2012 can be attributed to weather. This figure might increase as a consequence of climate change. Thus, a key policy recommendation is to take steps to facilitate integration of less educated migrants into the urban labor market.