What you think and what I think: Studying intersubjectivity in knowledge artifacts evaluation

Miscalibration, the failure to accurately evaluate one’s own work relative to others' evaluation, is a common concern in social systems of knowledge creation where participants act as both creators and evaluators. Theories of social norming hold that individual’s self-evaluation miscalibration diminishes over multiple iterations of creator-evaluator interactions and shared understanding emerges. This paper explores intersubjectivity and the longitudinal dynamics of miscalibration between creators' and evaluators' assessments in IT-enabled social knowledge creation and refinement systems. Using Latent Growth Modeling, we investigated dynamics of creator’s assessments of their own knowledge artifacts compared to peer evaluators' to determine whether miscalibration attenuates over multiple interactions. Contrary to theory, we found that creator’s self-assessment miscalibration does not attenuate over repeated interactions. Moreover, depending on the degree of difference, we found self-assessment miscalibration to amplify over time with knowledge artifact creators' diverging farther from their peers' collective opinion. Deeper analysis found no significant evidence of the influence of bias and controversy on miscalibration. Therefore, relying on social norming to correct miscalibration in knowledge creation environments (e.g., social media interactions) may not function as expected

A comparative analysis of Channels TV and CNN's coverage of World News

This study did an analysis of the Western and Third world coverage of World News using the broadcast stations (CNN and Channels TV) as case study. In other words, the study sought to examine if the Western and Third World nations are still guilty of imbalance, bias and distortion in their treatment of news. The findings showed that both the North and South nations are guilty of bias and imbalance in their coverage of World News and that each nation seeks to promote their interest rather than a true world interest or the interest of their counterpart nations. The study further revealed that the Third World media still depend heavily on Western media sources for its news albeit their standpoint on the News Flow debate. About 50% of the entire World News stories on Channels TV were sourced 'outside', while about 40% were unidentified. Only 10% were from the in-house personnel. It was also observed that about 55 and 67% of World News coverage by Channels TV and CNN, respectively, were focused on 'bad news'; an age-long controversy that has bedeviled news coverage globally. In view of the foregoing, it has been recommended that there is need for the acceptance of 'imbalance' as a major feature of all media systems as well as a re-evaluation of the standards and values of news evaluation. The rapid industrialization of Third World economies will also go a long way to stop the one-way traffic in international communication which is what encourages media dependence

Labor and women's nutrition : a study of energy expenditure, fertility, and nutritional status in Ghana

Economic approaches to health and nutrition have focused largely on measures of child nutrition and related variables (such as birth weight) as indicators of household production of nutritional outcomes. But when dealing with adult nutrition, economists have to address an issue that has generated tremendous controversy in the clinical nutrition literature. That issue is heterogeneity in an individual's energy expenditures. Preschoolers'energy expenditure also differs, but the differences are small enough to be ignored. Not so for adults, whose waking hours are devoted mostly to labor activities of which the energy costs vary enormously. Variables measuring time allocation to various types of labor tasks were used to proxy differences in energy expenditure. Parity has also been hypothesized to be an important determinant of female nutritional health in high fertility countries - with rapid reproductive cycling contributing to a cumulative nutritional decline. But the"maternal depletion syndrome"remains controversial. Much of the evidence to date has been impressionistic - or the results of studies based on small, nonrandom cohorts. Higgins and Alderman used a two-step instrumental variables technique to get consistent estimates of the structural parameters. Energy expenditure, as embodied in individual time allocations over the previous seven days, was found to be an important determinant of women's nutritional status. Time devoted to agricultural tasks, in particular, had a strong negative effect. The results also appear to confirm the existence of a maternal depletion syndrome. Perhaps more important, evidence was found of a substantial downward bias of the calorie-elasticity estimate when the energy expenditure proxies were excluded.Health Monitoring&Evaluation,Health Economics&Finance,Agricultural Knowledge&Information Systems,Environmental Economics&Policies,Economic Theory&Research

Viewpoint Discovery and Understanding in Social Networks

The Web has evolved to a dominant platform where everyone has the opportunity to express their opinions, to interact with other users, and to debate on emerging events happening around the world. On the one hand, this has enabled the presence of different viewpoints and opinions about a - usually controversial - topic (like Brexit), but at the same time, it has led to phenomena like media bias, echo chambers and filter bubbles, where users are exposed to only one point of view on the same topic. Therefore, there is the need for methods that are able to detect and explain the different viewpoints. In this paper, we propose a graph partitioning method that exploits social interactions to enable the discovery of different communities (representing different viewpoints) discussing about a controversial topic in a social network like Twitter. To explain the discovered viewpoints, we describe a method, called Iterative Rank Difference (IRD), which allows detecting descriptive terms that characterize the different viewpoints as well as understanding how a specific term is related to a viewpoint (by detecting other related descriptive terms). The results of an experimental evaluation showed that our approach outperforms state-of-the-art methods on viewpoint discovery, while a qualitative analysis of the proposed IRD method on three different controversial topics showed that IRD provides comprehensive and deep representations of the different viewpoints

Judging Judges: Securing Judicial Independence by Use of Judicial Performance Evaluations

This Article discusses judicial performance evaluations as a check on judicial independence. It covers numerous performance evaluation options for measuring accountability, such as bar and media polls, state judicial evaluation programs, and the ABA Guidelines for judicial performance. It discusses the pros and cons of these options. It concludes that the information provided by state judicial performance evaluations offers valuable insight into judicial criticisms and can give voters appropriate criteria to consider in judicial elections

Debiasing Community Detection: The Importance of Lowly-Connected Nodes

Community detection is an important task in social network analysis, allowing us to identify and understand the communities within the social structures. However, many community detection approaches either fail to assign low degree (or lowly-connected) users to communities, or assign them to trivially small communities that prevent them from being included in analysis. In this work, we investigate how excluding these users can bias analysis results. We then introduce an approach that is more inclusive for lowly-connected users by incorporating them into larger groups. Experiments show that our approach outperforms the existing state-of-the-art in terms of F1 and Jaccard similarity scores while reducing the bias towards low-degree users