What is “Qualitative” in Qualitative Research? Why the Answer Does not Matter but the Question is Important

Qualitative Sociology - What is qualitative research? Aspers and Corte (2019) make a case for a definition that they believe captures what many qualitative researchers intuitively know. Although I...     

Contemplative Methods Meet Social Sciences: Back to Human Experience as It Is

The aim of this paper is to trace a pathway connecting contemplative knowledge and practices with the social sciences. Contemplative knowledge and practices offer material for reflection in social science even concerning their very foundation. I'll found an opportunity for meshing our disciplinary tools with this knowledge as I introduced it in a health promotion program. The result will be a transdisciplinary confluence of different lines of inquiry contributing to a new perspective of self and social action. First of all I will give a definition of contemplative knowledge and practices. Then, I will make a bridge between the contemplative approach and the social sciences, showing the contribution that symbolic interactionism can play. I will illustrate the perspective drawing on an action research program called Auriga aimed at smoking cessation and reduction among health professionals. The aim of this paper is focused on the specification of the conceptual background in which such kind of program has been developed. Finally, I outline some implications it could represent for what might be called transformative sociology. I believe that contemplative knowledge could contribute to disentangle some of the unanswered questions and concerns in the social sciences, once they dismiss for a while their scientistic perspective. The secular redefinition of tools mainly belonging to the wisdom traditions represents an innovation that can reshape what we intend by the self and experience, contributing to what is called the “social transformation from within,” a pragmatic and wise approach to change at any level.     

On the reaction time of moving sum detectors

In this paper, we quantify the reaction time of on-line monitoring schemes for changes in the mean based on moving sums. The corresponding sequential test procedure requires a historical sample of size m   as a baseline, while decisions are made based on a window of size h=h(m)$h=h(m)$ containing the h most recent observations. Perhaps surprisingly, the limit distribution (obtained as m tends to infinity) of the associated stopping time crucially depends on the asymptotic relation of these two quantities, posing potential problems in applications. In the empirical part of the paper, we study therefore the finite sample behavior of the monitoring schemes. We provide tables of critical values for the various limit distributions and guidelines for practitioners via a simulation study.     

The past,present and future of policy modeling

We evaluate the past, present, and future of policy modeling from both qualitative and quantitative perspectives. We do this through an extensive review and analysis of papers published in the Journal of Policy Modeling between 1978 and 2018. Over the years the focus of the policy modeling literature (and the Journal) changed. The changes were in research topics, approaches, techniques, theories, methods, and analytical tools as required for the rigorous analysis of complex and dynamic economic phenomena in policy modeling.     

Bringing the “Moral Charge” Home: Fair Trade within the North and within the South*

Abstract Fair trade is typically understood as an alternative market system that aims to right historically inequitable terms of trade between the geopolitical North and South and foster more direct producer/consumer linkages. We suggest that a more expansive application of the term “fair trade” to encompass agro‐food initiatives within the North and South has considerable analytic and practical utility. We profile five such initiatives in the United States and two in Mexico. The U.S. undertakings are best understood as “proto‐” fair trade projects that frame their work principally as an effort to preserve “family farming” rather than as an exercise to achieve fairness in the marketplace. The Mexican initiatives more explicitly embrace the certification‐criteria‐labeling model of international fair trade. Both, we conclude, hold potential to harness fair trade's “moral charge” to improve conditions for small producers and laborers in North and South experiencing most directly the negative effects of economic globalization.     

Multiple-Scale Integrated Analysis of Farming Systems: The Thuong Lo Commune (Vietnamese Uplands) Case Study

This paper presents an application of an innovative methodological tool for the integrated assessment of farming systems (Multi-Objective Multiple-Scale Integrated Representation). It describes the effect of rural development in parallel on economic and ecological reading at different levels: household, village, and the commune comprising 3 villages. Socio-economic and environmental indicators are organized into integrated packages across scales. This is an ex-post facto analysis of a program of rural development implemented in the Central Vietnamese uplands in 1995 by the central government with the collaboration of FAO. We conclude that two classic problems can only be faced by using an integrated analysis across levels: Large scale generalizations can miss important location-specific characteristics, and exclusive focus on location specific issues carries the risk of loosing the big picture.     

Theory-based evaluation of a comprehensive Latino education initiative: an interactive evaluation approach

Latino student access to higher education has received significant national attention in recent years. This article describes a theory-based evaluation approach used with ENLACE of Hillsborough, a 5-year project funded by the W.K. Kellogg Foundation for the purpose of increasing Latino student graduation from high school and college. Theory-based evaluation guided planning, implementation as well as evaluation through the process of developing consensus on the Latino population of focus, adoption of culturally appropriate principles and values to guide the project, and identification of strategies to reach, engage, and impact outcomes for Latino students and their families. The approach included interactive development of logic models that focused the scope of interventions and guided evaluation designs for addressing three stages of the initiative. Challenges and opportunities created by the approach are discussed, as well as ways in which the initiative impacted Latino students and collaborating educational institutions.     

Subjective machines: Probabilistic risk assessment based on deep learning of soft information

For several years machine learning methods have been proposed for risk classification. While machine learning methods have also been used for failure diagnosis and condition monitoring, to the best of our knowledge, these methods have not been used for probabilistic risk assessment. Probabilistic risk assessment is a subjective process. The problem of how well machine learning methods can emulate expert judgments is challenging. Expert judgments are based on mental shortcuts, heuristics, which are susceptible to biases. This paper presents a process for developing natural language-based probabilistic risk assessment models, applying deep learning algorithms to emulate experts’ quantified risk estimates. This allows the risk analyst to obtain an a priori risk assessment when there is limited information in the form of text and numeric data. Universal sentence embedding (USE) with gradient boosting regression (GBR) trees trained over limited structured data presented the most promising results. When we apply these models’ outputs to generate survival distributions for autonomous systems’ likelihood of loss with distance, we observe that for open water and ice shelf operating environments, the differences between the survival distributions generated by the machine learning algorithm and those generated by the experts are not statistically significant.