a simple algorithm for the lexical classification of comparable adjectives

Abstract Lexical classification is one of the most widely investigated fields in (computational) linguistic and Natural language Processing. Adjectives play a significant role both in classification tasks and in applications as sentiment analysis. In this paper a simple algorithm for lexical classification of comparable adjectives, called MORE (coMparable fORm dEtector), is proposed. The algorithm is efficient in time. The method is a specific unsupervised learning technique. Results are verified against a reference standard built from 80 manually annotated lists of adjective. The algorithm exhibits an accuracy of 76%

Canadian Nurse Leaders\u27 Experiences with and Perceptions of Moral Distress: An Interpretive Descriptive Study

Moral distress in nursing has been studied across many care contexts, yet there is a paucity of research on the experience among health care leaders.The purpose of this study was to understand the experiences and perceptions of moral distress in nurse leaders.This study used an interpretive description approach interviewing 32 Canadian nurse leaders about their experiences and perceptions of moral distress within their role as a leader and nurse.A constant comparative and thematic analysis process revealed three thematic patterns:(a) leaders suffer moral distress in similar and different ways from their employees; (b) relationships matter in the midst of coping and emerging from moral distress; and (c) navigation through moral distress requires institutional, professional, and personal strategies.These patterns were important structural components in identifying the overarching metaphor of an ethical whirlwind that contextualized the experience as a vortex of constantly changing variables in dynamic interplay on a micro (patient/individual), meso (organizational), and macro (community) level.Findings were extracted from the participants’ interpretations of their experiences and from the interpretation of the data that illuminated experiential issues of importance to nurse leaders in relation to moral distress.On the basis of study findings, resiliency, resourcefulness, and self-awareness assisted nursing leaders in navigating and meaning-making of their experiences.Recommendations for leadership practice, policy implications, and future research are suggested to help diminish conditions that produce moral distress.This dissertation is available in open access at AURA:Antioch University Repository and Archive, http://aura.antioch.edu/ and OhioLINK ETD Center, https://etd.ohiolink.edu/et

Canadian Nurse Leaders\u27 Experiences with and Perceptions of Moral Distress: An Interpretive Descriptive Study

Moral distress in nursing has been studied across many care contexts, yet there is a paucity of research on the experience among health care leaders.The purpose of this study was to understand the experiences and perceptions of moral distress in nurse leaders.This study used an interpretive description approach interviewing 32 Canadian nurse leaders about their experiences and perceptions of moral distress within their role as a leader and nurse.A constant comparative and thematic analysis process revealed three thematic patterns:(a) leaders suffer moral distress in similar and different ways from their employees; (b) relationships matter in the midst of coping and emerging from moral distress; and (c) navigation through moral distress requires institutional, professional, and personal strategies.These patterns were important structural components in identifying the overarching metaphor of an ethical whirlwind that contextualized the experience as a vortex of constantly changing variables in dynamic interplay on a micro (patient/individual), meso (organizational), and macro (community) level.Findings were extracted from the participants’ interpretations of their experiences and from the interpretation of the data that illuminated experiential issues of importance to nurse leaders in relation to moral distress.On the basis of study findings, resiliency, resourcefulness, and self-awareness assisted nursing leaders in navigating and meaning-making of their experiences.Recommendations for leadership practice, policy implications, and future research are suggested to help diminish conditions that produce moral distress.This dissertation is available in open access at AURA:Antioch University Repository and Archive, http://aura.antioch.edu/ and OhioLINK ETD Center, https://etd.ohiolink.edu/et

Approximate solutions of moral dilemmas in multiple agent system

Moral dilemmas are one of the major issues of current research in ethical reasoning. In particular, it is well known that admitting moral dilemmas in Standard Deontic Logic generates a family of inconsistencies that are intrinsically unsolvable. Since managing dilemmas means performing preferential reasoning, we argue that one simple approach to both types of problems is by ordering actions. We notice that in general, more than local orderings between two actions, agents have intrinsic preferences based on classification issues, like the action type, and that, once we have discharged the dilemma as it is intrinsically, preferential reasoning is performed by using a second-level choice approach. Decision theory has dealt with the problem of making decisions in presence of conflicting decision criteria, and some researcher has pointed out that this is the case of moral dilemmas as well. In practice, the choice of preferences in presence of conflicting criteria can be seen as a form of preferential-ethical reasoning. Although this is certainly an important topic in multiple agent investigations, it is definitely neglected in the current investigations. It is well known that humans are quite clever in solving moral dilemmas, and the usage they make of preferential reasoning is very complex. In this paper we address the problems of preferential-ethical reasoning in a combinatorial fashion and provide an algorithm for making decisions on moral dilemmas in presence of conflicting decision criteria. We then evaluate the complexity of the algorithm and prove that this approach can be applied in practice