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After the initial life (which coincides with the origins of social research in the 1850s, and lasts until 1940s), mixed methods revive at the beginning of 1970s. However, this second life (or renaissance) receives the deleterious imprinting of quantitative methods. In fact, some of the old positivist assumptions are still reproduced and active in most of mixed methods research. This imprinting is traceable in the ambiguity (and purposive semantic stretching) of the term “qualitative”: from the 1990s, it encompasses almost everything (even approaches considered positivistic in the 1950s!). Whereby the semantical extension of the term “qualitative” has become a sort of Trojan horse for a new legitimation of many quantitative and positivist researchers: a great swindle. Today “qualitative” is nonsense and acts as a bug, which muddies the qualitative-quantitative debate. For this reason, it would be better to remove the bug (i.e. to discharge the term “qualitative” from the language of social research and methodology), reset and start over from the level of specific research methods, considering carefully and balancing their diversity before mixing them. The purpose of this paper is to outline two (complementary) ways of integration of methods (“mixed” and “merged”), arguing that “merged” methods realize a higher integration than “mixed” methods, because the former overcome some weaknesses of the latter.

A semantic and pragmatic analysis of the term “qualitative.”

In social and behavioral sciences, the second life of mixed methods has been heavily affected by old positivist and quantitative assumptions.

The term “qualitative” should be discharged from the language of social research and methodology.

The coveted integration in “mixed” methods, could be better pursed through “merged” methods.

Disentangling the strands of a debate (the qualitative-quantitative one) become muddy.

An alternative framework, to interpret the mixed methods history and their recent developments, has been proposed.

Artificial intelligence (AI) and automation are currently changing human life with a great implication in the communication field. This research focusses on understanding the current and growing impact of AI and automation in the role of communication professionals to identify what skills and training are needed to face its impacts leading to a recommendation.

The research involves methodological triangulation, analysing and comparing data gathered from consulting with experts using the Delphi method, focus group with communication students, and literature review.

Findings show that the likely impacts are on the one hand the enhancing of efficiency and productivity, as well as freeing communication professionals to focus on the creative side, strategy and analytical thinking, on the other hand, repetitive and low-level jobs could be lost, being higher position jobs or those involving creativity and decision making harder to automate. Two types of training are needed: to gather experience with the current AI and automated tools, and to focus on developing human qualities that AI cannot replicate.

The outcomes of this research are valuable to help current and future communication practitioners, as well as organisations, to be one step ahead and survive the age AI and automation, being aware of its current and near-future impacts. The paper offers a list of recommended soft and technical skills, as well as training needed, categorizing them in low, medium and high priority.

The equation of unified knowledge says that S = f (A,P) which means that the practical solution to a given problem is a function of the existing, empirical, actual realities and the future, potential, best possible conditions of general stable equilibrium which both pure and practical reason, exhaustive in the Kantian sense, show as being within the realm of potential realities beyond any doubt. The first classical revolution in economic thinking, included in factor “P” of the equation, conceived the economic and financial problems in terms of a model of ideal conditions of stable equilibrium but neglected the full consideration of the existing, actual conditions. That is the main reason why, in the end, it failed. The second modern revolution, included in factor “A” of the equation, conceived the economic and financial problems in terms of the existing, actual conditions, usually in disequilibrium or unstable equilibrium (in case of stagnation) and neglected the sense of right direction expressed in factor “P” or the realization of general, stable equilibrium. That is the main reason why the modern revolution failed in the past and is failing in front of our eyes in the present. The equation of unified knowledge, perceived as a sui generis synthesis between classical and modern thinking has been applied rigorously and systematically in writing the enclosed American‐British economic, monetary, financial and social stabilization plans. In the final analysis, a new economic philosophy, based on a synthesis between classical and modern thinking, called here the new economics of unified knowledge, is applied to solve the malaise of the twentieth century which resulted from a confusion between thinking in terms of stable equilibrium on the one hand and disequilibrium or unstable equilibrium on the other.

Organizations facing issues related to growth, innovation, and strategy are embracing design thinking, a problem-solving process. This study explores 40 design thinking initiatives and identifies operational practices emerge and empirical categories across various contexts. Quantitative analyses of the initiatives and qualitative interview data are used to distinguish four configurations of action analogous to races: training, emphasizing learning-by-doing; marathons, capturing personal reflection over a long project; relays, highlighting team collaboration; and sprints, reflecting fast-paced product innovation. The initiatives are differentiated as designer-led versus team-driven and, low-urgency versus high-urgency. Implications of practicing design thinking in Organization Development and Change are discussed.

Gilles Deleuze and Alain Badiou are two very different philosophers, and yet they touch upon many similar themes. Perhaps most noticeable is their respective concerns for developing philosophical systems free of the concerns of so-called post-modernism. In this paper I look at some of the themes in their work, and consider what might thereby be enabled within thinking about law. In so doing the paper argues that Deleuze’s work is particularly useful, as it allows for a polymorphous practice of thought, appropriately named as “jurisprudence.”

Argues preliminarily that quantitative‐mathematical social science, including economics, is not possible because it applies a method useful in other areas to a field to which it cannot be applied and because the truth claim of science so conceived is self‐referential to begin with. The argument is primarily based on the classic Gadamerian hermeneutic critique of the natural sciences and on the conception of the social sciences as related to phronésis.