Drawing the line at infidelity: Negotiating relationship morality in a Swedish context of consensual non-monogamy

Consensual non-monogamy (CNM) involves being in a relationship that allows participants multiple concurrent sexual and/or intimate partners. Previous studies exploring attitudes toward different types of extra-dyadic sexual activity (EDSA) has typically distinguished between, on the one hand, polyamory/open relationships/swinging and, on the other, infidelity. The aim of this article is to develop further these discussions by showing how the distinctions between relationship types are drawn and/or blurred in social interactions, and how this requires moral work and negotiations of what ethical polyamory is. The research questions are as follows: 1. How are different CNM relationship types distinguished from each other, as well as intertwined and negotiated in social interactions? 2. How are ideals of consent, honesty, and communication reproduced and renegotiated in CNM relationships? 3. How does moral work become important for responding to negative attitudes toward CNM? The material consists of interviews with 22 persons practicing polyamory, CNM, or relationship anarchy, analyzed using thematic analysis. Results show that CNM relationship types are not clearly distinguishable but rather negotiated in social interactions both within a relationship and with others. Interviewees express that consent, honesty, and communication are central for their relationships, but also that they are negotiated. For example, honesty can be renegotiated by introducing an option of not telling your partner everything. Consent can also be renegotiated with some conditions, such as not actively searching out potential partners. They describe several different types of moral work: negotiating and reformulating others’ moral opinions, reversing moral hierarchies, and taking responsibility to explain and to soothe situations. These results contribute to existing research on attitudes toward CNM practices pointing out the importance of taking social interactions into account in order to explore the full extent of negative attitudes toward people involved in CNM relationships and how they handle these interactions.

UFO: Unified Foundational Ontology

The Unified Foundational Ontology (UFO) was developed over the last two decades by consistently putting together theories from areas such as formal ontology in philosophy, cognitive science, linguistics, and philosophical logics. It comprises a number of micro-theories addressing fundamental conceptual modeling notions, including entity types and relationship types. The aim of this paper is to summarize the current state of UFO, presenting a formalization of the ontology, along with the analysis of a number of cases to illustrate the application of UFO and facilitate its comparison with other foundational ontologies in this special issue. (The cases originate from the First FOUST Workshop – the Foundational Stance, an international forum dedicated to Foundational Ontology research.)

Neighborhood-Level Predictors of Sexual Violence Across Intimate Partner and Non-Intimate Partner Relationships: A Case–Control Study

Ample research explores individual factors associated with sexual violence, yet individual, dyadic, and environmental influences on intimate partner sexual violence (IPSV) occurring in the larger context of non-intimate partner violence (NIPSV) remain relatively unexplored. The current study aimed to determine the extent to which county-level indicators in combination with individual and dyadic factors are associated with sexual violence across relationship types. Reported IPSV and NIPSV cases were obtained from the Tennessee Bureau of Investigation’s (TBI) online incident-based reporting system. County-level variables indicative of neighborhood physical disorder, violent crime, income inequality, firearm prevalence, and community alcohol use patterns were retrieved from the online resource County Health Rankings and Roadmaps. Using a nested case–control design, we determined significant sexual violence risk within younger cohorts and across relationship types, finding three significant county-level factors: 1) income inequality, 2) rate of firearm fatalities, and 3) percentage of female residents. Suggested prevention and intervention efforts include targeting younger age groups for IPSV and NIPSV education, developing resources for a range of relational partners, improving legal access and law enforcement training for reporting, and continued examination of the role of firearms.

Nonverbal Auditory Cues Allow Relationship Quality to be Inferred During Conversations

The claim that nonverbal cues provide more information than the linguistic content of a conversational exchange (the Mehrabian Conjecture) has been widely cited and equally widely disputed, mainly on methodological grounds. Most studies that have tested the Conjecture have used individual words or short phrases spoken by actors imitating emotions. While cue recognition is certainly important, speech evolved to manage interactions and relationships rather than simple information exchange. In a cross-cultural design, we tested participants’ ability to identify the quality of the interaction (rapport) in naturalistic third party conversations in their own and a less familiar language, using full auditory content versus audio clips whose verbal content has been digitally altered to differing extents. We found that, using nonverbal content alone, people are 75–90% as accurate as they are with full audio cues in identifying positive vs negative relationships, and 45–53% as accurate in identifying eight different relationship types. The results broadly support Mehrabian’s claim that a significant amount of information about others’ social relationships is conveyed in the nonverbal component of speech.

RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine

Background: Biomedical translational science is increasingly leveraging computational reasoning on large repositories of structured knowledge (such as the Unified Medical Language System (UMLS), the Semantic Medline Database (SemMedDB), ChEMBL, DrugBank, and the Small Molecule Pathway Database (SMPDB)) and data in order to facilitate discovery of new therapeutic targets and modalities. Since 2016, the NCATS Biomedical Data Translator project has been working to federate autonomous reasoning agents and knowledge providers within a distributed system for answering translational questions. Within that project and within the field more broadly, there is an urgent need for an open-source framework that can efficiently and reproducibly build an integrated, standards-compliant, and comprehensive biomedical knowledge graph that can be either downloaded in standard serialized form or queried via a public application programming interface (API) that accords with the FAIR data principles. Results: To create a knowledge provider system within the Translator project, we have developed RTX-KG2, an open-source software system for building—and hosting a web API for querying—a biomedical knowledge graph that uses an Extract-Transform-Load (ETL) approach to integrate 70 knowledge sources (including the aforementioned sources) into a single knowledge graph. The semantic layer and schema for RTX-KG2 follow the standard Biolink metamodel to maximize interoperability within Translator. RTX-KG2 is currently being used by multiple Translator reasoning agents, both in its downloadable form and via its SmartAPI-registered web interface. JavaScript Object Notation (JSON) serializations of RTX-KG2 are available for download of RTX-KG2 in both the pre-canonicalized form and in canonicalized form (in which synonym concepts are merged). The current canonicalized version (KG2.7.3) of RTX-KG2 contains 6.4M concept nodes and 39.3M relationship edges with a rich set of 77 relationship types. Conclusion: RTX-KG2 is the first open-source knowledge graph of which we are aware that integrates UMLS, SemMedDB, ChEMBL, DrugBank, SMPDB, and 65 additional knowledge sources within a knowledge graph that conforms to the Biolink standard for its semantic layer and schema at the intersections of these databases. RTX-KG2 is publicly available for querying via its (API) at arax.ncats.io/api/rtxkg2/v1.2/openapi.json. The code to build RTX-KG2 is publicly available at github:RTXteam/RTX-KG2.

Ambiguous Signaling in Regulatory Conversations How Miscommunication and Hierarchy Hamper Voluntary Regulatee Cooperation

This case study investigates interactions between inspectors and regulatee representatives during regulatory conversations. We study how health care inspectors pursue voluntary cooperation from internal supervisors of health care providers to alter organizational management practices. We identify ambiguity as a central characteristic of the regulatory conversations. We observe several discrepancies as inspectors display hierarchical behavior incongruent with the horizontal relationship they aim for—and incongruent with the relationship style that internal supervisors expect. Analyzing these discrepancies in terms of relationship types and associated relational signals helps explain and prevent suboptimal communication and reduced acceptance of regulators’ demands by regulatees.

Mental Health in Affectionate, Antagonistic, and Ambivalent Relationships During the COVID-19 Pandemic: A Latent Profile Analysis

The ongoing coronavirus disease-2019 (COVID-19) pandemic presents an acute stressor affecting mental health. In these stressful times, intimate relationships functioning could serve as a protective or a risk factor to the well-being of partners. Adult Croatian citizens engaged in intimate relationships (N = 727) reported their relationship characteristics and assessed symptoms of depression, anxiety, and stress during the state lockdown in May 2020. Three relationship profiles based on variations in key relationship characteristics were identified using latent profile analysis. Profiles represented distinct relationship types described as affectionate, ambivalent, and antagonistic relationships. These relationship types differed in their levels of love and perception of humility, responsiveness, and behavior of the partner. Relationship type was associated with mental health symptoms such as depression, anxiety, and stress during the COVID-19 pandemic and state lockdown. Being in an affectionate relationship was associated with the lowest levels of depression, anxiety, and stress, while in an antagonistic relationship these are in the highest levels. Ambivalent relationships were characterized by moderate levels on all measured mental health indicators with no difference in anxiety compared with affectionate relationships. The results emphasized the link between relationship functioning and successful coping with mental health hazards such as the fear of disease or restrictive measures put in place to contain the COVID-19 pandemic.

Interpretation of Spatial Relationships by Objects Tracking in a Complex Streaming Video

By interpreting spatial relations among objects, many applications such as video surveillance, robotics, and scene understanding systems can be utilized efficiently for different purposes. The vast majority of known models for spatial relationships are carried out with an image. However, due to the advance in technology, a three-dimensional scene became available. For our knowledge, most of the interpreted spatial relations were defined between silent objects in images. A technique for determining the dynamic spatial relation between a moving object and another silent one in a time varying scene is presented here. The spatial relationships were determined by using motion-based object tracking along with hypergraph object-oriented model. Defining the spatial relationship types between a single silent object and a moving human body has applied based on two strategies; determining each object with a bounding box, then comparing the locations of these boxes by applying certain conditional rules. This study identifies some of the spatial relationships in three dimensions of streaming frames, which has carried out by establishing a highly accurate and efficient proposed algorithm. The following relations have been studied; (“direct in front of”, “in front of on the Right/Left”, “direct behind of”, “behind of on the Right/Left”, “to the Right”, “to the Left”, “On”, “Under”, Besides, and “Besides on to the Right/Left”). The experimental results, which have been obtained based on actual indoor streaming frames, show effectiveness and reliable execution of our system

Neoliberalism and the ideological construction of equity beliefs

Researchers across disciplines, including psychology, have sought to understand how people evaluate the fairness of resource distributions. Equity, defined as proportionality of rewards to merit, has dominated the conceptualization of distributive justice in psychology, with some scholars casting it as the primary basis on which distributive decisions are made. The present paper acts as a corrective to this disproportionate emphasis on equity. Drawing on findings from different subfields, we argue that people possess a range of beliefs about how valued resources should be allocated—beliefs that vary systematically across developmental stages, relationship types, and societies. By reinvigorating notions of distributive justice put forth by the field’s pioneers, we further argue that prescriptive beliefs concerning resource allocation are ideological formations embedded in socioeconomic and historical contexts. Fairness beliefs at the micro-level are thus shaped by those beliefs’ macro-level instantiations. In a novel investigation of this process, we consider neoliberalism, the globally-dominant socioeconomic model of the past forty years. Using data from more than 160 countries, we uncover evidence that neoliberal economic structures shape equity based distributive beliefs at the individual level. We conclude by advocating an integrative approach to the study of distributive justice that bridges microand macro-level analyses.