In and out of home care decisions: The influence of confirmation bias in developing decision supportive reasoning

The aims of this study were to identify the themes Social Workers regard as important in supporting decisions to remove children from, or return them to, the care of their parents. To further elicit underlying hypotheses that are discernible in interpretation of evidence. A case study, comprising a two-part vignette with a questionnaire, recorded demographic information, child welfare attitudes and risk assessments, using scales derived from standardised instruments, was completed by 202 Social Workers in Northern Ireland. There were two manipulated variables, mother’s attitude to removal and child’s attitude to reunification2 years later. In this paper we use data derived from respondents’ qualitative comments explaining their reasoning for in and out of home care decisions. Some 60.9% of respondent’s chose the parental care option at part one, with 94% choosing to have the child remain in foster care at part two. The manipulated variables were found to have no significant statistical effect. However, three underlying hypotheses were found to underpin decisions; (a)child rescue, (b) kinship defence and (c) a hedged position on calculation of risk subject to further assessment. Reasoning strategies utilised by social workers to support their decision making suggest that they tend to selectively interpret information either positively or negatively to support pre-existing underlying hypotheses. This finding is in keeping with the literature on ‘confirmation bias.’ The research further draws attention to the need to incorporate open questions in quantitative studies, to help guard against surface reading of data, which often does not ‘speak for itself.’

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

Reasoning Rights: Comparative judicial engagement

This edited book is about comparative reasoning in human rights cases, exploring the questions: How is it that notionally universal norms are reasoned by courts in such dramatically different ways? What is the shape of this reasoning? What techniques are common across the transnational jurisprudence? What techniques are diverse? With contributions by a team of world-leading human rights scholars, the book moves beyond simply addressing the institutional questions concerning courts and human rights, which too often dominate discussions of this kind. Instead, it seeks a deeper examination of the similarities and divergence in the content of reasons being developed by different courts when addressing comparable human rights questions. These differences, while partly influenced by institutional issues, cannot be attributable to them alone. The book explores the diverse and rich underlying spectrum of human rights reasoning, as a distinctive and particular form of legal reasoning, evident in the case studies across the selected jurisdictions. It is a fascinating study for all those interested in human rights law and legal reasoning.

Using Comparative Reasoning in Human Rights Adjudication:The Court of Justice of the European Union and the European Court of Human Rights Compared

This article examines the relationship between the methods that the European Court of Human Rights (ECtHR) and the Court of Justice of the European Union (CJEU) use to decide disputes that involve ‘human’ or ‘fundamental’ rights claims, and the substantive outcomes that result from the use of these particular methods. It has a limited aim: in attempting to understand the interrelationship between human rights methodology and human rights outcomes, it considers primarily the use of ‘comparative reasoning’ in ‘human’ and ‘fundamental’ rights claims by these courts. It is not primarily concerned with examining the extent to which the use of comparative reasoning is based on an appropriate methodology or whether there is a persuasive normative theory underpinning the use of comparative reasoning. The issues considered in this chapter do some of the groundwork, however, that is necessary in order to address these methodological and normative questions.

Kinect and Episodic Reasoning for Human Action Recognition

This paper presents a method for rational behaviour recognition that combines vision-based pose estimation with knowledge modeling and reasoning. The proposed method consists of two stages. First, RGB-D images are used in the estimation of the body postures. Then, estimated actions are evaluated to verify that they make sense. This method requires rational behaviour to be exhibited. To comply with this requirement, this work proposes a rational RGB-D dataset with two types of sequences, some for training and some for testing. Preliminary results show the addition of knowledge modeling and reasoning leads to a significant increase of recognition accuracy when compared to a system based only on computer vision.