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The purpose of this paper is to discuss and shed light on the following questions: What is an author? Is it a person who writes? Or, is it, in information, an iconic taxonomic designation (some might say a “classification”) for a group of writings that are recognized by the public in some particular way? What does it mean when a search engine, or catalog, asks a user to enter the name of an author? And how does that accord with the manner in which the data have been entered in association with the names of the entities identified with the concept of authorship?

The authors use several cases as bases of phenomenological discourse analysis, combining as best the authors can components of eidetic bracketing (a Husserlian technique for isolating noetic reduction) with Foucauldian discourse analysis. The two approaches are not sympathetic or together cogent, so the authors present them instead as alternative explanations alongside empirical evidence. In this way the authors are able to isolate components of iconic “authorship” and then subsequently engage them in discourse.

An “author” is an iconic name associated with a class of works. An “author” is a role in public discourse between a set of works and the culture that consumes them. An “author” is a role in cultural sublimation, or a power broker in deabstemiation. An “author” is last, if ever, a person responsible for the intellectual content of a published work. The library catalog’s attribution of “author” is at odds with the Foucauldian discursive comprehension of the role of an “author.”

One of the main assets of this paper is the combination of Foucauldian discourse analysis with phenomenological analysis for the study of the “author.” The authors turned to Foucauldian discourse analysis to discover the loci of power in the interactions of the public with the named authorial entities. The authors also looked to phenomenological analysis to consider the lived experience of users who encounter the same named authorial entities. The study of the “author” in this combined way facilitated the revelation of new aspects of the role of authorship in search engines and library catalogs.

The purpose of this paper is to discuss the literature on concept theory in library and information science (LIS) from an epistemological perspective, ascribing each paper to an epistemological family and discussing their relevance in the context of the knowledge organization (KO) domain.

This paper adopts a hermeneutic approach for the analysis of the texts that compose the corpus of study following contingency and categorical analyses. More specifically, the paper works with Bardin’s contingency analysis and follows Hjørland’s families of epistemologies for the categorization.

The analysis corroborates the observations made for the last ten years about the scarcity of studies on concept theory in LIS and KO. However, the study also reveals an epistemological turn on concept theory since 2009 that could be considered a departure from the rationalist views that dominated the field and a continuation of a broader paradigm shift in LIS and KO. All analyzed papers except two follow pragmatist or historicist approaches.

This paper follows-up and systematizes the contributions to the LIS and KO fields on concept theory mainly during the last decade. The epistemological analysis reveals the dominant views in this paradigm shift and the main authors and trends that are present in the LIS literature on concept theory.

The purpose of this paper is to review the contributions of the special issue papers while presenting four broad research avenues.

The paper is based on a review of current literature on climate change and carbon accounting.

The authors propose four broad avenues for research: climate change as a systemic and social issue, the multi-layered transition apparatus for climate change, climate vulnerability and the future of carbon accounting.

The authors connect this study with the requested institutional changes for climate breakdown, making the paper relevant for practice and policy. The authors notably point to education and professions as institutions that will request bold and urgent makeovers.

The authors urge academics to reconsider climate change as a social issue, requiring to use new theoretical lenses such as emotions, eco-feminism, material politics and “dispositifs” to tackle this grand challenge.

This paper switches the authors’ viewpoint on carbon accounting to look at it from a more systemic and social lens.

The novel coronavirus disease 2019 (COVID-19) pandemic has presented unique challenges in terms of understanding its unique characteristics of transmission and predicting its spread. The purpose of this study is to present a simple, parsimonious and accurate model for forecasting mortality caused by COVID-19.

The presented Bass Model is compared it with several alternative existing models for forecasting the spread of COVID-19. This study calibrates the model for deaths for the period, March 21 to April 30 for the USA as a whole and as the US States of New York, California and West Virginia. The daily data from the COVID-19 Tracking Project has been used, which is a volunteer organization launched from The Atlantic. Every day, data is collected on testing and patient outcomes from all the 50 states, 5 territories and the District of Columbia. This data set is widely used by policymakers and scholars. The fit of the model (F-value and its significance, R-squared value) and the statistical significance of the variables (t-values) for each one of the four estimates are examined. This study also examines the forecast of deaths for a three-day period, May 1 to 3 for each one of the four estimates – US, and States of New York, California and West Virginia. Based on these metrics, the viability of the Bass Model is assessed. The dependent variable is the number of deaths, and the two independent variables are cumulative number of deaths and its squared value.

The findings of this paper show that compared to other forecasting methods, the Bass Model performs remarkably well. In fact, it may even be argued that the Bass Model does better with its forecast. The calibration of models for deaths in the USA, and States of New York, California and West Virginia are all found to be significant. The F values are large and the significance of the F values is low, that is, the probability that the model is wrong is very miniscule. The fit as measured by R-squared is also robust. Further, each of the two independent variables is highly significant in each of the four model calibrations. These forecasts also approximate the actual numbers reasonably well.

This study illustrates the applicability of the Bass Model to estimate the diffusion of COVID-19 with some preliminary but important empirical analyses. This study argues that while the more sophisticated models may produce slightly better estimates, the Bass model produces robust and reasonably accurate estimates given the extreme parsimony of the model. Future research may investigate applications of the Bass Model for pandemic management using additional variables and other theoretical lenses.

The Bass Model offers effective forecasting of mortality resulting from COVID-19 to help understand how the curve can be flattened, how hospital capacity could be overwhelmed and how fatality rates might climb based on time and geography in the upcoming weeks and months.

This paper demonstrates the efficacy of the Bass Model as a parsimonious, accessible and theory-based approach that can predict the mortality rates of COVID-19 with minimal data requirements, simple calibration and accessible decision calculus. For all these reasons, this paper recommends further and continued examination of the Bass Model as an instrument for forecasting COVID-19 (and other epidemic/pandemic) mortality and health resource requirements. As this paper has demonstrated, there is much promise in this model.