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This methodological paper offers a five-step model for preparing bilingual data for analysis. The article is guided by research in translating bilingual data into qualitative research. A systematic analysis of the research studies was conducted to identify workable options for preparing bilingual data for analysis. The proposed five-step model is comprised of (1) translator’s worldview and professionalism, (2) epistemological, ontological, and methodological considerations, (3) line of translation, (4) responsiveness to cultural terms and (5) eagerness to trustworthiness and reliability of the data. Researcher’s worldviews encompass the visibility of translator’s positionality for reflexivity, avoidance of biasness, and demonstration of professionalism. The bilingual data needs treatment based on epistemological, ontological, and methodological orientations which the translators need to be mindful of. The researcher must be clear on the line of translation in opting for direct translation, back-translation, single translation, or multiple translations. The translated data must be responsive to the cultural contexts to carry on sense and meaning. Depending on the methodological approaches and contextual requirements, the translation work must meet the needs of trustworthiness and validity. The literature is silent on the translations of non-verbal cues. Therefore, this problem should be dealt with separately in future research endeavors. Similarly, future research on linguistic contexts and translation work in diverse research approaches such as quantitative, qualitative, and mixed methods is needed.

The scientific literature has presented evidence of the links between innovation and change and has published excellent methodologies to analyze them. Nowadays, international scientific programs like Horizon Europe prioritize social impact and co-creation; researchers need to develop methodologies to analyze the link of innovation with change and new knowledge and specially with social impact. This paper presents an innovative methodological approach to this endeavor using Social Media Analytics to investigate citizens' participation in paying attention to and differentiating between innovations with social impact and innovations without social impact. The method used to address this aim is Social Media Analytics, specifically through a Twitter sample on innovation and social impact composed of 16,794 tweets obtained during January–June 2021. The result obtained indicates that the definition of methodologies to capture citizens’ participation in paying attention to and differentiating between innovation and social impact is crucial for advancing this innovative methodological approach to analyze innovation with social impact.

This article examines several qualitative methods to capture and analyze processes in therapeutic and clinical interventions. The study of therapeutic processes provides an understanding of what leads to changes in clinical interventions. This is a goal of any therapeutic intervention. This interest should allow us to try to identify what the therapists do and think they are doing, how they do it, how they think about their interventions, and what happens during the session that might explain changes. These types of studies require that researchers provide clarifications about their epistemological and methodological choices. To meet that requirement, we propose to review a range of issues, methodologies, and tools – which come from qualitative research - that guide us in conducting research in the psychotherapeutic and clinical field. The aim of our article is to put forward a methodological framework for researchers to better explore the patient’s or the therapist’s lived-experience and better reveal, moment-to-moment, the clinical practice.

Repowering the Brazilian hydroelectric park is a way to expand the use of energy from hydro sources, even in a scenario where the options to build new projects are increasingly restricted. Several technical and economic aspects must be considered when evaluating the feasibility to carry out a repowering process, where indicators are considered to choose the best option. The repowering suggests the addition of assured energy, however, electromechanical equipment improvement may occur simultaneously with automation systems. Sizing is generally precise for a hydropower plant and there is no need for repowering so that the project can increase its useful life, consequently, rehabilitation is recommended. This paper shows a methodology to evaluate intervention alternatives in a project, as well as a rehabilitation case study for the Marimbondo Hydroelectric Power Plant

Increasingly, qualitative researchers are combining methods, processes, and principles from two or more methodologies over the course of a research study. Critics charge that researchers adopting combined approaches place too little attention on the historical, epistemological, and theoretical aspects of the research design. Rather than discounting eclecticism in qualitative research, we prefer to place it on a continuum of integration whereby at the ideal end of the spectrum, the researcher demonstrates thorough knowledge of the approaches being drawn from and a thoughtful consideration of the rationale for combining methods. However, there is limited reflection in the literature on the combination of methods from specific methodological approaches. To address this gap we examine the extent to which the methods from two distinct qualitative methodologies, grounded theory and narrative inquiry might complement each other within a qualitative study using a framework that encompasses 10 key methodological features of research design. Key Words: Grounded Theory, Combined Methodological Approaches, Narrative Inquiry, Mixed Methods, Qualitative, Multiple Methods.

The literature on resilience and posttraumatic growth has been instrumental in highlighting the human capacity to overcome adversity by illuminating that there are different pathways individuals may follow. Although the theme of strength from adversity is attractive and central to many disciplines and certain cultural narratives, this claim lacks robust empirical evidence. Specific issues include methodological approaches of using growth-mixture modeling in resilience research and retrospective assessments of growth. Conceptually, limitations exist in the examination of which outcomes are most appropriate for studying resilience and growth. We discuss new research intended to overcome these limitations, with a focus on prospective longitudinal designs and the value of integrating these disciplines for furthering our understanding of the human capacity to overcome adversity.

Management journals are currently responding to challenges raised by the “replication crisis” in experimental social psychology, leading to new standards for transparency. These approaches are spilling over to qualitative research in unhelpful and potentially even dangerous ways. Advocates for transparency in qualitative research mistakenly couple it with replication. Tying transparency tightly to replication is deeply troublesome for qualitative research, where replication misses the point of what the work seeks to accomplish. We suggest that transparency advocates conflate replication with trustworthiness. We challenge this conflation on both ontological and methodological grounds, and we offer alternatives for how to (and how not to) think about trustworthiness in qualitative research. Management journals need to tackle the core issues raised by this tumult over transparency by identifying solutions for enhanced trustworthiness that recognize the unique strengths and considerations of different methodological approaches in our field.

The present paper illustrates the results of a diagnostic investigation performed on the oil on canvas painting “The Glory of St. Barbara” (1680–1688) by Mattia Preti. The painting is located inside the St. Barbara Church in Taverna (Catanzaro, Italy), the city that gave birth to the artist. In situ, non-invasive studies, by applying X-ray fluorescence (XRF) spectroscopy, along with laboratory micro-destructive analytical investigations, by employing electron probe microanalyses (EPMA) coupled with energy-dispersive spectrometry (EDS) and micro-Raman (µ-Raman) spectroscopy, were combined to retrieve the color palette and identify the painting technique and style of the famous master. As a result of this multi-scale characterization, an extraordinary pictorial technique was revealed, enriching knowledge about one of the oldest pictorial traditions outlined by Mattia Preti, and solving doubts still existing about many of his investigated artworks. Moreover, the achieved results represent useful and essential tools to address management issues of the artwork, by providing valuable information for planning and monitoring future restoration interventions of the canvas.

A common theme in social science studies of algorithms is that they are profoundly opaque and function as “black boxes.” Scholars have developed several methodological approaches in order to address algorithmic opacity. Here I argue that we can explicitly enroll algorithms in ethnographic research, which can shed light on unexpected aspects of algorithmic systems—including their opacity. I delineate three meso-level strategies for algorithmic ethnography. The first, algorithmic refraction , examines the reconfigurations that take place when computational software, people, and institutions interact. The second strategy, algorithmic comparison , relies on a similarity-and-difference approach to identify the instruments’ unique features. The third strategy, algorithmic triangulation , enrolls algorithms to help gather rich qualitative data. I conclude by discussing the implications of this toolkit for the study of algorithms and future of ethnographic fieldwork.

The assessment and identification of risk/vulnerable groups and risk factors are vital elements that can help quantify the pandemic potential of the SARS‐CoV‐2 virus in order to plan prevention and treatment measures. The aim of the study is to identify a methodological approach of population vulnerability to the SARS‐CoV‐2 virus infection. The study identifies reliable data sources and sets up a unitary database with statistical variables, quantitative and qualitative indicators with potential for being updated and improved. The analysis takes into account a number of variables/indicators (e.g., elderly persons, population without physician care, number of people suffering from cardiovascular diseases, number of people suffering from respiratory diseases, dwellings not connected to the public water supply network, no. of medical staff, number of COVID‐19 hospitals, PCR testing laboratories, number of vaccinated persons) grouped into the key vulnerability components: exposure, sensitivity, coping capacity and adaptive capacity. They allowed the computation of the final Index of Population Vulnerability to the SARS‐CoV‐2 virus infection and the mapping of different dimensions of vulnerability. The study was performed using the statistical data available at NUTS3/County level provided by different institutions (e.g., the Ministry of Health, the National Institute of Public Health, the Strategic Communication Group, and the National Institute of Statistics). The mapping of the different degrees of vulnerability could solve a problem of visibility for possible areas with vulnerable population, but also a problem of communication between different institutional health and administrative levels, as well as between all of them and the local communities and/or professionals. Key Points Risk/vulnerable groups and risk factors are vital elements that can help quantify the pandemic potential of the SARS‐CoV‐2 virus The mapping of the different degrees of vulnerability could solve a problem of visibility of possible areas with vulnerable population The results could lead to a rethinking of the interventions of the decision‐makers