A relevância prática da pesquisa no setor público: a potencial contribuição da abordagem intervencionista

The practical relevance of accounting research is one of the main issue currently present in the debate. Scholars engagement and impact of accounting research are all the more required nowadays. Interventionist research (IVR) is considered a potential methodology that allows researchers to contribute to the advancement of both practice and theory. The aim of this paper is to present an analysis of the characteristics of IVR, providing guidance on how it can provide a fruitful methodology to bridge academics and practitioners in the context of public sector research.A relevância prática da pesquisa em contabilidade é uma das questões mais presentes atualmente no debate na área. O engajamento dos acadêmicos e o impacto da pesquisa em contabilidade são mais que necessários nos dias atuais. A pesquisa intervencionista (IVR, sigla para Interventionist Research) é considerada uma metodologia que em potencial permitiria pesquisadores contribuírem com o avanço tanto das práticas quando da teoria. O objetivo deste artigo é apresentar uma análise das características da IVR, oferecendo um guia em esta metodologia pode ser útil para construir a ponte entre acadêmicos e praticantes no contexto da pesquisa no setor público

The practical relevance of public sector research: the potential contributions of the interventionist approach

A relevância prática da pesquisa em contabilidade é uma das questões mais presentes atualmente no debate na área. O engajamento dos acadêmicos e o impacto da pesquisa em contabilidade são mais que necessários nos dias atuais. A pesquisa intervencionista (IVR, sigla para Interventionist Research) é considerada uma metodologia que em potencial permitiria pesquisadores contribuírem com o avanço tanto das práticas quando da teoria. O objetivo deste artigo é apresentar uma análise das características da IVR, oferecendo um guia em esta metodologia pode ser útil para construir a ponte entre acadêmicos e praticantes no contexto da pesquisa no setor público

Implementations, interpretative malleability, value-ladenness and the moral significance of agent-based social simulations

The focus of social simulation on representing the social world calls for an investigation of whether its implementations are inherently value-laden. In this article, I investigate what kind of thing implementation is in social simulation and consider the extent to which it has moral significance. When the purpose of a computational artefact is simulating human institutions, designers with different value judgements may have rational reasons for developing different implementations. I provide three arguments to show that different implementations amount to taking moral stands via the artefact. First, the meaning of a social simulation is not homogeneous among its users, which indicates that simulations have high interpretive malleability. I place malleability as the condition of simulation to be a metaphorical vehicle for representing the social world, allowing for different value judgements about the institutional world that the artefact is expected to simulate. Second, simulating the social world involves distinguishing between malfunction of the artefact and representation gaps, which reflect the role of meaning in simulating the social world and how meaning may or not remain coherent among the models that constitute a single implementation. Third, social simulations are akin to Kroes’ (2012) techno-symbolic artefacts, in which the artefact’s effectiveness relative to a purpose hinges not only on the functional effectiveness of the artefact’s structure, but also on the artefact’s meaning. Meaning, not just technical function, makes implementations morally appraisable relative to a purpose. I investigate Schelling’s model of ethnic residential segregation as an example, in which different implementations amount to taking different moral stands via the artefact.info:eu-repo/semantics/acceptedVersio

MUVTIME: a Multivariate time series visualizer for behavioral science

As behavioral science becomes progressively more data driven, the need is increasing for appropriate tools for visual exploration and analysis of large datasets, often formed by multivariate time series. This paper describes MUVTIME, a multimodal time series visualization tool, developed in Matlab that allows a user to load a time series collection (a multivariate time series dataset) and an associated video. The user can plot several time series on MUVTIME and use one of them to do brushing on the displayed data, i.e. select a time range dynamically and have it updated on the display. The tool also features a categorical visualization of two binary time series that works as a high-level descriptor of the coordination between two interacting partners. The paper reports the successful use of MUVTIME under the scope of project TURNTAKE, which was intended to contribute to the improvement of human-robot interaction systems by studying turn- taking dynamics (role interchange) in parent-child dyads during joint action.Marie Curie International Incoming Fellowship PIIF-GA-2011- 301155; Portuguese Foundation for Science and Technology (FCT) project PTDC/PSI- PCO/121494/2010; AFP was also partially funded by the FCT project (IF/00217/2013)This research was supported by: Marie Curie International Incoming Fellowship PIIF-GA-2011301155; Portuguese Foundation for Science and Technology (FCT) Strategic program FCT UID/EEA/00066/2013; FCT project PTDC/PSIPCO/121494/2010. AFP was also partially funded by the FCT project (IF/00217/2013). REFERENCE

Toward a Neuroscientific Understanding of Play: A Dimensional Coding Framework for Analyzing Infant-Adult Play Patterns.

Play during early life is a ubiquitous activity, and an individual's propensity for play is positively related to cognitive development and emotional well-being. Play behavior (which may be solitary or shared with a social partner) is diverse and multi-faceted. A challenge for current research is to converge on a common definition and measurement system for play - whether examined at a behavioral, cognitive or neurological level. Combining these different approaches in a multimodal analysis could yield significant advances in understanding the neurocognitive mechanisms of play, and provide the basis for developing biologically grounded play models. However, there is currently no integrated framework for conducting a multimodal analysis of play that spans brain, cognition and behavior. The proposed coding framework uses grounded and observable behaviors along three dimensions (sensorimotor, cognitive and socio-emotional), to compute inferences about playful behavior in a social context, and related social interactional states. Here, we illustrate the sensitivity and utility of the proposed coding framework using two contrasting dyadic corpora (N = 5) of mother-infant object-oriented interactions during experimental conditions that were either non-conducive (Condition 1) or conducive (Condition 2) to the emergence of playful behavior. We find that the framework accurately identifies the modal form of social interaction as being either non-playful (Condition 1) or playful (Condition 2), and further provides useful insights about differences in the quality of social interaction and temporal synchronicity within the dyad. It is intended that this fine-grained coding of play behavior will be easily assimilated with, and inform, future analysis of neural data that is also collected during adult-infant play. In conclusion, here, we present a novel framework for analyzing the continuous time-evolution of adult-infant play patterns, underpinned by biologically informed state coding along sensorimotor, cognitive and socio-emotional dimensions. We expect that the proposed framework will have wide utility amongst researchers wishing to employ an integrated, multimodal approach to the study of play, and lead toward a greater understanding of the neuroscientific basis of play. It may also yield insights into a new biologically grounded taxonomy of play interactions

Time to go wild: How to conceptualize and measure process dynamics in real teams with high-resolution

Team processes are interdependent activities among team members that transform inputs into outputs, vary over time, and are critical for team effectiveness. Understanding the temporal dynamics of team processes and related team phenomena with a high-resolution lens (i.e., methods with high sampling rates) is particularly challenging when going “into the wild” (i.e., studying teams operating in their full situated context). We review quantitative field studies using high-resolution methods (e.g., video, chat/text data, archival, wearables) and map out the various temporal lenses for studying team dynamics. We synthesize these different lenses and present an integrated temporal framework that is of help in theorizing about team dynamics. We also provide readers with a “how to” guide that summarizes four essential steps along with analytical methods (e.g., sequential and pattern analyses, mixed-methods research, abductive reasoning) that are applicable to the broad scope of high-resolution methods

Third Space, Social Media and Everyday Political Talk

Theoretical and empirical research into online politics to date has primarily focused on what might be called formal politics or on how activists and social movements utilize social media to pursue their goals. However, in this chapter, we argue that there is much to be gained by investigating how political talk and engagement emerges in everyday, online, lifestyle communities: i.e. third spaces. Such spaces are not intended for political purposes, but rather – during the course of everyday talk – become political through the connections people make between their everyday lives and the political/social issues of the day. In this chapter, we develop a theoretically informed argument for research that focuses on everyday informal political talk in online third spaces