Advancing the Discipline: Guidelines from the Experience of Colleagues

Introduces articles from the issue about the disciplinary advancement of the communication departments of various colleges and universities

Job Insecurity and Youth Emancipation: A Theoretical Approach

In this paper, we propose a theoretical model to study the effect of income insecurity of parents and offspring on the child's residential choice. Parents are partially altruistic toward their children and will provide financial help to an independent child when her income is low relative to the parents'. We show that first-order stochastic dominance (FOSD) shifts in the distribution of the child's future income (or her parents') will have ambiguous effects on the child's residential choice. The analysis identifies altruism as the source of ambiguity in the results. If parents are selfish or the joint income distribution of parents and child places no mass on the region where transfers are provided, a FOSD shift in the distribution of the child's (parents') future income will reduce (raise) the child's current income threshold for independenceAltruism; Emancipation; Job security; Option value

Job Insecurity and Children's Emancipation

The age at which children leave the parental home differs considerably across countries. We present a theoretical model predicting that higher job security of parents and lower job security of children may delay emancipation. We then provide aggregate evidence which supports this hypothesis for 12 European countries. We also give microeconometric evidence for Italy, the single country for which we have access to household-specific information on job security and coresidence. It is a very interesting case to study since, in the late 1990s, approximately 75 per cent of young Italians aged 18 to 35 were living at home and they had only a 4 per cent probability of emancipation in the subsequent 3 years. We show that this probability would have increased by 4 to 10 percentage points if their fathers had gone from having a fully secure job to becoming unemployed for sure.emancipation, job security, option value

A new statistical solution to the generality problem

The Generality Problem is widely recognized to be a serious problem for reliabilist theories of justification. James R. Beebe's Statistical Solution is one of only a handful of attempted solutions that has garnered serious attention in the literature. In their recent response to Beebe, Julien Dutant and Erik J. Olsson successfully refute Beebe's Statistical Solution. This paper presents a New Statistical Solution that countenances Dutant and Olsson's objections, dodges the serious problems that trouble rival solutions, and retains the theoretical virtues that made Beebe's solution so attractive in the first place. There indeed exists a principled, rigorous, conceptually sparse, and plausible solution to the Generality Problem: it is the New Statistical Solution

Probabilistic Social Learning Improves the Public's Detection of Misinformation

The digital spread of misinformation is one of the leading threats to democracy, public health, and the global economy. Popular strategies for mitigating misinformation include crowdsourcing, machine learning, and media literacy programs that require social media users to classify news in binary terms as either true or false. However, research on peer influence suggests that framing decisions in binary terms can amplify judgment errors and limit social learning, whereas framing decisions in probabilistic terms can reliably improve judgments. In this preregistered experiment, we compare online peer networks that collaboratively evaluate the veracity of news by communicating either binary or probabilistic judgments. Exchanging probabilistic estimates of news veracity substantially improved individual and group judgments, with the effect of eliminating polarization in news evaluation. By contrast, exchanging binary classifications reduced social learning and entrenched polarization. The benefits of probabilistic social learning are robust to participants' education, gender, race, income, religion, and partisanship.Comment: 11 pages, 4 figure

Vegetation diversity in East African wetlands : Cocktail algorithms supported by a vegetation-plot database

Aims: Wetlands in East Africa are important ecosystems for biodiversity conservation and ecosystem service provisioning, yet threatened by degradation and conversion into croplands. Conservation and land use management require data on vegetation structure and dynamics. The presented work is a response to a lacking consistent classification of East African wetland vegetation. Location: Namulonge valley in Uganda and Kilombero floodplain in Tanzania. Methods: We sampled 431 4 m²-plots along land use intensity and flooding duration gradients. A floristic classification using the cocktail method was performed in a two-step approach. We developed definitions for vegetation units, using plot observations from the study sites in a first step and revised them in a second step by adding data from a vegetation-plot database and complied the definitions to an expert system for classification. Resulting vegetation units were analyzed regarding their life form composition, for which we implemented a classification based on life span and growth form. Following a literature review, the identified vegetation units were assigned either to existing phytosociological associations or proposals. Results: We recognize eight units of marsh and reed vegetation (class Phragmito-Magno-Caricetea) and five units of weed and pioneer vegetation under semi-aquatic conditions (class Oryzetea sativae). Five of these associations were previously described in the bibliographic references. The remaining eight are newly described in this work. The associations contrast in their life form composition with the five Oryzetea sativae associations dominated by obligate annuals and the Phragmito-Magno-Caricetea associations dominated by either reed plants or lacking a dominating life form. Conclusions: The developed expert system enables a comparison of wetland vegetation in the East African region and will support vegetation science and informed decision making about land use management and conservation. The two-step approach of revising a classification developed for single wetlands with a database is promising for data-scarce regions. Nomenclature: Haines & Lye (1983); CJBG & SANBI (2012); The Plant List (2013); TNRS (2018). Abbreviations: DCA = Detrended Correspondence Analysis; DRC = Democratic Republic of the Congo; MRPP = Multiple Response Permutation Procedure