Breaking the filter bubble: democracy and design

It has been argued that the Internet and social media increase the number of available viewpoints, perspectives, ideas and opinions available, leading to a very diverse pool of information. However, critics have argued that algorithms used by search engines, social networking platforms and other large online intermediaries actually decrease information diversity by forming so-called “filter bubbles”. This may form a serious threat to our democracies. In response to this threat others have developed algorithms and digital tools to combat filter bubbles. This paper first provides examples of different software designs that try to break filter bubbles. Secondly, we show how norms required by two democracy models dominate the tools that are developed to fight the filter bubbles, while norms of other models are completely missing in the tools. The paper in conclusion argues that democracy itself is a contested concept and points to a variety of norms. Designers of diversity enhancing tools must thus be exposed to diverse conceptions of democracy.     

Phonological Processing and Word Reading in Typically Developing and Reading Disabled Children: Severity Matters

In this study word reading (WR) fluency was used to dichotomously classify 1,598 Dutch children at different cutoffs, indicating (very) poor or (very) good reading performance. Analysis of variance and receiver operating characteristics were used to investigate the effects of rapid automatized naming (RAN) and phonemic awareness (PA) in predicting group membership. The highest predictive values were found for the combination of RAN and PA, particularly for the poorest readers. Furthermore, results indicate that with the severity of impairment, WR is more dominated by deficient PA, which is interpreted as an enduring problem with sublexical processing. Another main result is that with the increase of reading skill, the contribution of PA diminishes, whereas the contribution of RAN remains fairly constant for the whole reading fluency continuum. These results warrant the conclusion that whereas PA hallmarks reading disability, RAN appears to be the default predictor for above-average or excellent reading proficiency.     

Parent–adolescent interaction quality and adolescent affect—An experience sampling study on effect heterogeneity

Person–environment interactions might ultimately drive longer term development. This experience sampling study (Data collection: 2019/20 the Netherlands) assessed short-term linkages between parent–adolescent interaction quality and affect during 2281 interactions of 124 adolescents (M_age = 15.80, SD_age = 1.69, 59% girls, 92% Dutch, Education: 25% low, 31% middle, 35% high, 9% other). Adolescents reported on parent–adolescent interaction quality (i.e., warmth and conflict) and momentary positive and negative affect five to six times a day, for 14 days. Preregistered dynamic structural equation models (DSEM) revealed within-family associations between parent–adolescent interaction quality and adolescent affect (concurrently: r = −.22 to .39; lagged effects: ß = −.17 to .15). These effects varied significantly between families. These findings stress the need for more person-specific research on parenting processes.     

Aspiring to include versus implicit ‘othering’: teachers' perceptions of inclusive education in Wales

Wales, one of the four nations of the UK, is currently undergoing major education system-level reform. From the curriculum, through to a new additional learning needs (ALN) system, there is a renewed focus on inclusive education. Research has shown the importance of teachers' attitudes towards inclusion in creating inclusive learning environments. This research study is based on data from a survey of teachers in Wales (n = 253) exploring their perceptions of inclusive education. Thematic analysis of open-text responses revealed that while teachers were able to articulate the ‘ideal’ of inclusion, these positive ideals were often caveated by both implicit othering of learners with ALN and by the explicit limitations of behaviour, training, and finance and resources. This article critically evaluates the implications of teacher perceptions of inclusive education in Wales, suggesting that without a change in teacher attitudes, the vision of an inclusive education system may be compromised.     

Association between prenatal maternal anxiety and/or stress and offspring's cognitive functioning: A meta-analysis

This meta-analysis examined the relationship between prenatal maternal stress and/or anxiety and the outcomes of children aged 3 months to 9 years. Of the 8754 studies published before June 2021 that were synthesized, 17 conducted in Western countries were included in the meta-analysis (N_total = 23,307; M_males 54%; M_ethnicity White 77%, Pacific 15%, African American/Black 10%, Middle Eastern 7%, Eastern 8%). Effect sizes ranged from −0.41 to 0.15. A weak negative association was found between prenatal stress and/or anxiety exposure and children's general intellectual development. Associations varied based on the type of exposure. Findings are limited to developed counties and cannot be generalized to low- and middle-income countries. Directions for maternal prenatal intervention and future studies are discussed.     

Automatic thematic classification of election manifestos

We digitized three years of Dutch election manifestos annotated by the Dutch political scientist Isaac Lipschits. We used these data to train a classifier that can automatically label new, unseen election manifestos with themes. Having the manifestos in a uniform XML format with all paragraphs annotated with their themes has advantages for both electronic publishing of the data and diachronic comparative data analysis. The data that we created will be disclosed to the public through a search interface. This means that it will be possible to query the data and filter them on themes and parties. We optimized the Lipschits classifier on the task of classifying election manifestos using models trained on earlier years. We built a classifier that is suited for classifying election manifestos from 2002 onwards using the data from the 1980s and 1990s. We evaluated the results by having a domain expert manually assess a sample of the classified data. We found that our automatic classifier obtains the same precision as a human classifier on unseen data. Its recall could be improved by extending the set of themes with newly emerged themes. Thus when using old political texts to classify new texts, work is needed to link and expand the set of themes to newer topics.