scholarly journals Adolescent Technology-use Rules and Sleep in a Large Representative Sample

Author(s):  
Alison Giovanelli ◽  
Emily J. Ozer ◽  
Sally H. Adams ◽  
M. Jane Park ◽  
Elizabeth M. Ozer
2012 ◽  
Vol 56 (2) ◽  
pp. 142-162 ◽  
Author(s):  
Thérèse Shaw ◽  
Donna Cross

Bullying between students at school can seriously affect students' health and academic outcomes. To date, little is known regarding the extent to which bullying behaviour is clustered within certain schools rather than similarly prevalent across all schools. Additionally, studies of bullying behaviour in schools that do not account for clustering of such behaviour by students within the same school are likely to be underpowered and yield imprecise estimates. This article presents intraclass correlation (ICC) values for bullying victimisation and perpetration measures based on a large representative sample of 106 Australian schools. Results show that bullying is not confined to specific schools and school differences contribute little to explaining students' bullying behaviour. Despite this, seemingly negligible ICC values can substantially affect the sample sizes required to attain sufficiently powered studies, when large numbers of students are sampled per school. Sample size calculations are illustrated.


2020 ◽  
Vol 6 (1) ◽  
pp. 205630512090340 ◽  
Author(s):  
Cristian Vaccari ◽  
Andrew Chadwick

Artificial Intelligence (AI) now enables the mass creation of what have become known as “deepfakes”: synthetic videos that closely resemble real videos. Integrating theories about the power of visual communication and the role played by uncertainty in undermining trust in public discourse, we explain the likely contribution of deepfakes to online disinformation. Administering novel experimental treatments to a large representative sample of the United Kingdom population allowed us to compare people’s evaluations of deepfakes. We find that people are more likely to feel uncertain than to be misled by deepfakes, but this resulting uncertainty, in turn, reduces trust in news on social media. We conclude that deepfakes may contribute toward generalized indeterminacy and cynicism, further intensifying recent challenges to online civic culture in democratic societies.


Author(s):  
Erik D. Reichle

This chapter first describes what has been learned about how readers represent the meaning of discourse by integrating the meanings to individual sentences to construct the representations needed to understand larger segments of text. The chapter reviews the key findings related to text processing and how this sparked an ongoing debate about the extent to which the making of inferences during reading is obligatory. The chapter reviews precursor theories and models of discourse representation that attempt to explain how discourse representations are generated via the interaction of language processing and memory. The chapter then reviews a large, representative sample of the models that have been used to simulate and understand aspects of discourse processing. They are reviewed in their order of development to show how the models have evolved to accommodate new empirical findings. The chapter concludes with an explicit comparative analysis of the discourse-processing models and discusses the empirical findings that each model can and cannot explain.


2019 ◽  
Vol 48 (2) ◽  
pp. 252-262 ◽  
Author(s):  
James Gibson ◽  
Christopher Claassen ◽  
Joan Barceló

While scholars have shown strong interest in the role of emotions in politics, questions remain about the connections between emotions and political intolerance. First, it is not clear which emotion (if any) is likely to produce intolerance toward one’s disliked groups, with different studies favoring hatred, anger, or fear. Second, it is unclear whether these effects of emotion are moderated by sophistication, as some conventional political thought argues. Do the less-sophisticated rely on emotions when making judgments, therefore being less tolerant than sophisticates, who rely on reason? Here, we test both hypotheses using a large representative sample Americans. We find that hatred, anger, and fear are significantly but only modestly related to political intolerance. Moreover, the effects of emotions on intolerance are not consistently stronger among the unsophisticated. These findings provide little support for the conventional assumption that the less-sophisticated rely on their emotions in making political judgments.


2016 ◽  
Vol 62 (5) ◽  
pp. 1363-1380 ◽  
Author(s):  
Stephen G. Dimmock ◽  
Roy Kouwenberg ◽  
Peter P. Wakker

Author(s):  
Charlie Halpern-Hamu

Creation of representative sample(s) of a large document collection can be automated using XSLT. Such samples will be useful for analysis, as a preliminary document analysis step in vocabulary redesign or conversion and to guide design of storage, editing, and transformation processing. Design goals are: to work intuitively with default configuration and no schema, produce plausible output, and produce a range of outputs from a large representative set to a short but highly complex sample document. The technique can be conceptualized in passes: annotate structures as original or redundant; keep wrappers to accommodate original markup found lower in the hierarchy; retain required children and attributes; and collapse similar structures. Possible settings include redundancy thresholds, text compression techniques, target length, schema-awareness, schema intuitions, how much context to preserve around kept elements, and whether similar structures should be collapsed (overlaid).


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