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First-generation college students in the United States are a unique demographic that is often characterized by the institutions that serve them with a risk-laden and deficit-based model. However, our analysis of the transcripts of open-ended, semi-structured interviews with 22 “first-gen” respondents suggests they are actively deft, agentic, self-determining parties to processes of identity construction that are both externally imposed and potentially stigmatizing, as well as exemplars of survivance and determination. We deploy a grounded theory approach to an open-coding process, modeled after the extended case method, while viewing our data through a novel synthesis of the dual theoretical lenses of structural and radical/structural symbolic interactionism and intersectional/standpoint feminist traditions, in order to reveal the complex, unfolding, active strategies students used to make sense of their obstacles, successes, co-created identities, and distinctive institutional encounters. We find that contrary to the dictates of prevailing paradigms, identity-building among first-gens is an incremental and bidirectional process through which students actively perceive and engage existing power structures to persist and even thrive amid incredibly trying, challenging, distressing, and even traumatic circumstances. Our findings suggest that successful institutional interventional strategies designed to serve this functionally unique student population (and particularly those tailored to the COVID-moment) would do well to listen deeply to their voices, consider the secondary consequences of “protectionary” policies as potentially more harmful than helpful, and fundamentally, to reexamine the presumption that such students present just institutional risk and vulnerability, but also present a valuable addition to university environments, due to the unique perspective and broader scale of vision their experiences afford them.

This chapter aims to critically analyse the implications that the national protectionist policies have on the global supply and value chains and the relocation of production. The analysis is based on the assumptions that the global economy is facing the possibility of decoupling of many trade connections, and this trend favours de-globalisation processes that have long been promoted by populism, nationalism and economic protectionism. It is concluded that global supply, production and value chains although being economically efficient are no longer any more secure under national protectionist policies, and therefore, the relocation of production processes is mainly due to the increase in the level of income and wages of the developing countries that are the destination and which reduce the advantages to relocate.

In February 2018, Jerome Powell had taken over as chair of the FOMC. At first glance, the macroeconomic conditions inherited by Powell appeared favorable for continued stability: unemployment and inflation were low, and the economy had been steadily growing for nearly a decade. Yet despite the appearance of stability, the economy faced significant risks that required the Federal Reserve's attention. Was an uptick in inflation imminent, and if so, should Powell raise rates to limit any inflationary pressure? Or was the economy still operating below capacity, and if so, should the Federal Reserve take a more accommodative stance? To gain perspective, Powell needed to look back at the past fifty years of monetary policy in the United States.

Homelessness has many causes and also is stigmatized in the United States, leading to much misunderstanding of its causes and what policy solutions may ameliorate the problem. The problem is of course getting worse and impacting many communities far removed from the West Coast cities the authors examine in this study. This analysis examines the socioeconomic variables influencing homelessness on the West Coast in recent years. The authors utilize a panel fixed effects model that explicitly includes measures of healthcare access and availability to account for the additional health risks faced by individuals who lack shelter. The authors estimate a spatial error model (SEM) in order to better understand the impacts that systemic shocks, such as the COVID-19 pandemic, have on a variety of factors that directly influence productivity and other measures of welfare such as income inequality, housing supply, healthcare investment, and homelessness.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.