Reparative Reasoning

Peter Ochs' notion of ‘pragmatic reading’ and his wider project of articulating a ‘logic of scripture’ are described in the first part of this article. A distinction is made between Ochs' proposals for how to read scripture and his more technical claims about how scripture itself models a ‘logic of repair’. The term ‘thirdness’ is explained in the contexts of the relations and axioms, hypotheses and communities. His readings of Hans Frei and George Lindbeck are rehearsed briefly in the second section. Their attempts to show that there is nothing ‘behind’ scripture or doctrine, to which the latter supposedly refer, are presented by Ochs as ‘pragmatic’ attempts to repair the rules which generate false oppositions in discussions of scripture and doctrine

Assessing statistical reasoning in descriptive statistics: a qualitative meta-analysis

To date, there are abundant studies on statistical reasoning in descriptive statistics and inferential statistics. Nevertheless, the types of statistical reasoning assessments used in those studies are different from each other. Hence, this qualitative meta-analysis is aimed to explore the methods utilized in assessing statistical reasoning among students from all levels in descriptive statistics. A total of 36 studies on reasoning about measures of central tendency, variability and distribution were found and reviewed in this paper. It was noticed that six major types of methods were employed to assess students’ statistical reasoning in descriptive statistics, namely interview, survey or questionnaire, tasks, tests, minute paper, and teaching. This study contributes considerably to the statistical reasoning area as it provides new information on statistical reasoning in descriptive statistics. For future studies, some recommendations are proposed to improve statistical reasoning assessments

Structure of, access to, and uncertainty in reasoning and their dependence on content

It is known that content has an effect on reasoning. In this paper the influence of the content on the structure of reasoning, the access to it, and the ability to handle uncertainty was studied. The participants were presented with reasoning tasks about the weather and about the oscilloscope in which uncertain premises were introduced. Correct reasoning procedures were identified including correct reasoning with wrong answers. In correct reasoning procedures about the weather, three different structures of reasoning were identified. The participants were mostly able to reason with uncertain components. In reasoning about the oscilloscope, less correct reasoning procedures were found. No empirical and theoretical structures were used. The hidden structure differed here from the one in the weather case because the participants were not able to handle all uncertain components in otherwise correct reasoning. The implications of this unique finding for the acquisition of reasoning skills are discusse

Degrees of Belief as Basis for Scientific Reasoning?

Bayesianism is the claim that scientific reasoning is\ud probabilistic, and that probabilities are adequately interpreted\ud as an agent"s actual subjective degrees of belief\ud measured by her betting behaviour.\ud Confirmation is one important aspect of scientific reasoning.\ud The thesis of this paper is the following: Given that\ud scientific reasoning (and thus confirmation) is at all\ud probabilistic, the subjective interpretation of probability has\ud to be given up in order to get right confirmation, and thus\ud scientific reasoning in general

Distributed stream reasoning

Stream Reasoning is the combination of reasoning techniques with data streams. In this paper, we present our approach to enable rule-based reasoning on semantic data streams in a distributed manne

Towards two-stage service representation and reasoning: from lightweight annotations to comprehensive semantics

Semantics are used to mark up a wide variety of data-centric Web resources but are not used to annotate online functionality in significant numbers. That is despite considerable research dedicated to Semantic Web Services (SWS). This has led to the emergence of a new Linked Services approach with simplified and less costly to produce service models, which targets a wider audience and allows even non-SWS developers to annotate services. However, such models merely aim at enabling semantic search by humans or automated service clustering rather than automation of service tasks such as discovery or orchestration. Thus, more expressive solutions are still required to achieve automated discovery and orchestration of services. In this paper, we describe our investigation into combining the strengths of two distinct approaches to modeling semantic Web services – 'lightweight' Linked Services and 'heavyweight' SWS automation - into a coherent SWS framework. In our vision, such integration is achieved by means of model cross-referencing and model transformation and augmentation

Analogical Reasoning

This chapter from our book Legal Writing in Context aims to demystify analogical reasoning for law students