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Contextual Entailment and Containment:A Ternary Approach to Information and Topic Inclusion
No full textThe paper introduces a relevant containment logic according to which the analytic implication φ↠ψ is analyzed as the conjunction of two theses: φ contextually entails ψ and φ contextually contains ψ. By doing so, we are able to extend the ternary semantics of relevant logic to the analysis of topic containment, thus lifting some limitations of Richard Sylvan’s relevant containment logic. We offer a ternary account of topic containment, in that led by the consideration that topic inclusions are evaluated in situ, i.e. with respect to the discursive context fixed by an information state. The main technical result of the paper is a sound and complete axiomatisation of relevant containment logic. Finally, Sylvan’s logic turns out as a special case of our relevant containment logic
When dialects collide:how socioeconomic mixing affects language use
No full textThe socioeconomic background of people and how they use standard forms of language are not independent, as demonstrated in various sociolinguistic studies. However, the extent to which these correlations may be influenced by the mixing of people from different socioeconomic classes remains relatively unexplored from a quantitative perspective. In this work we leverage geotagged tweets and transferable computational methods to map deviations from standard English across eight UK metropolitan areas. We combine these data with high-resolution income maps to assign a proxy socioeconomic indicator to home-located users. Strikingly, we find a consistent pattern suggesting that the more different socioeconomic classes mix, the less interdependent the frequency of their departures from standard grammar and their income become. Further, we propose an agent-based model of linguistic variety adoption that sheds light on the mechanisms that produce the observations seen in the data
Subnational variations in the quality of household survey data in sub-Saharan Africa
No full textNationally representative household surveys collect geocoded data that are vital to tackling health and other development challenges in sub-Saharan Africa. Scholars and practitioners generally assume uniform data quality but subnational variation of errors in household data has never been investigated at high spatial resolution. Here, we explore within-country variation in the quality of most recent household surveys for 35 African countries at 5 × 5 km resolution and district levels. Findings show a striking heterogeneity in the subnational distribution of sampling and measurement errors. Data quality degrades with greater distance from settlements, and missing data as well as imprecision of estimates add to quality problems that can result in vulnerable remote populations receiving less than optimal services and needed resources. Our easy-to-access geospatial estimates of survey data quality highlight the need to invest in better targeting of household surveys in remote areas
