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People with intellectual disability are reported to encounter many negative life events during their increasingly long lives. In the absence of protective elements, these may cause toxic stress and trauma. Given the reported negative effects of such adverse events on their quality of life (QoL), the perspective of older people with intellectual disability themselves may be of relevance. The paper aims to discuss these issues.

The authors questioned nine participants with mild intellectual disability, aged 61–88 years old, in four 90-min focus group sessions and thematically analysed the data.

Many recent and bygone negative life events still weighed heavily on the participants. Negative interactions, experiences of loss, lack of control and awareness of one’s disability caused stress. Their emotional response contrasted with their contentment, compliance and resilience. Having (had) good relationships, having learnt coping skills, remaining active, talking about past experiences and feeling free of pain, safe, well supported, capable, respected and involved seemed to heighten resilience and protect participants from toxic stress.

Monitoring and preventing adverse (childhood) experiences, supporting active/emotional coping strategies, psychotherapy and life story work may facilitate coping with negative events and enhance QoL of elderly people with intellectual disability.

Elderly people with mild intellectual disability run a higher risk of experiencing (early) adverse events in life. They are very capable of talking about their experiences, QoL, and the support they need. Focus groups were a reliable method to capture their insights.

Quality of life and quality of care have become dominant themes in planning and evaluating services for persons with learning disabilities. There are, however, few conceptual models and assessment instruments that are geared to people with profound and multiple learning disabilities. This article presents an ongoing research project aimed at developing and implementing a valid and reliable procedure for evaluating the quality of life of people with profound and multiple learning disabilities in several European countries. This objective will be realised in three subsequent stages, each of which is divided into several steps. The research project presented has the potential to develop theory as well as good practice in the care of people with profound and multiple learning disabilities.

Researchers in information studies have examined fictional depictions of libraries in various mediums because these images can reflect and influence real-life experiences and attitudes. Video games, despite being relatively overlooked, are increasingly culturally relevant and can indicate library users' real needs and desires. This study investigates the ways in which video games depict characters using libraries to seek and use information.

A qualitative content analysis approach incorporating methods from information studies and game studies was applied. Tancheva's (2005) semiotic analysis of fictional libraries and Carr's (2019) textual approach provided the framing for the unique aspects of video games and their meanings. Carroll (2021)'s character analysis and Chatman (1996)'s theory on insiders–outsiders dynamic underpinned the data collection and analysis. The purposive sample included 15 video games released since 2010.

Video games depict game characters visiting libraries to solve short-term problems, to gain knowledge to improve themselves or to bond with others. Protagonists are often depicted as adventurers or outsiders who must adapt to unfamiliar places and situations to achieve their wider objectives. In these games, libraries provide useful documents, spaces or helpful guides and intellectuals who assist the protagonists. As outsiders, the protagonists seek information in libraries to help them learn about their environments and to immerse themselves in the local histories and cultures in their worlds. Overall, these depictions highlight both short- and long-term benefits of library use.

As with existing studies, the ways in which fictional library use appear in video games can suggest real needs and desires among library users. The findings from this study emphasise the importance of library services and spaces that help users both address short-term problems and immerse themselves in local concerns, with longer-term goals. Applying different research methods or lenses to analysing video games could deepen our understanding of what library users think and feel when they seek and use information in libraries.

Over half of the US states have jettisoned an exclusive focus on profit maximization for shareholders and created new corporate structures, called “benefit corporations”, which give equal standing to the achievement of social and environmental objectives. This paper aims to examine the factors leading to adoption of legislation for the business formation of benefit corporations by the US states.

Event History Analysis (EHA), a time-series technique using panel data of non-repeatable events, is used to identify and understand economic, political and diffusion factors that affect the adoption of benefit corporation enabling legislation in the US states.

The results strongly indicate that politics matters – states in which the Democratic Party or liberal ideology controls governmental functions are more likely to pass these laws. There is also evidence that states that are more innovative in their approach to policy-making are more likely to adopt these laws. Otherwise, unemployment, tax burden, political culture, enacted constituency statutes and geographic diffusion have no discernible relationship with the adoption of benefit corporation laws.

The paper provides warning signs to firms considering expending costly resources on the establishment of or conversion to benefit corporation status and the related investment in developing skills for the preparation, review and assurance of required annual benefit corporation reporting.

The findings suggest future adoption of benefit corporation enabling laws may slow considerably.

At the time they occurred, the savings and loan insolvencies were considered the worst financial crisis since the Great Depression. Contrary to what was then believed, and in sharp contrast with 2007–2009, they in fact had little macroeconomic significance. Savings and Loan (S&L) remediation cost between 2 percent and 3 percent of Gross Domestic Product (GDP), whereas the Troubled Asset Relief Program (TARP) and the conservatorships of Fannie and Freddie actually made money for the US Treasury. But the direct cost of government remediation is largely irrelevant in judging macro significance. What matters is the cumulative output loss associated with and plausibly caused by failing financial institutions. I estimate output losses for 1981–1984, 1991–1998, and 2007–2026 (the latter utilizing forecasts and projections along with actual data through 2015) and, for a final comparison, 1929–1941. The losses associated with 2007–2009 have been truly disastrous – in the same order of magnitude as the Great Depression. The S&L failures were, in contrast, inconsequential. Macroeconomists and policy makers should reserve the word crisis for financial disturbances that threaten substantial damage to the real economy, and continue efforts to identify in advance financial institutions which are systemically important (SIFI), and those which are not.

This chapter develops a predictive approach to Granger causality (GC) testing that utilizes k -fold cross-validation and posterior simulation to perform out-of-sample testing. A Monte Carlo study indicates that the cross-validation predictive procedure has improved power in comparison to previously available out-of-sample testing procedures, matching the performance of the in-sample F-test while retaining the credibility of post- sample inference. An empirical application to the Phillips curve is provided evaluating the evidence on GC between inflation and unemployment rates.

The purpose of this paper is first, to provide input to the “through life knowledge and information management” grand challenge and second to provide industry with a tool for assessing the quality of the process(es) by which decisions are reached.

An iterative approach is used with two student‐based case studies, followed by two research institution case studies, and then two industrial case studies. Validation of the tool by managers is undertaken in another case study.

An analytic framework is created which allows managers to categorise and display the characteristics of their decision processes. By assessing the resulting voids and clusters within the framework, the efficacy of the process can be determined. The framework has an associated management process, first to enable managers to see and compare instances of other situations, especially those leading to “disaster”, and second to upgrade the tool itself as assessments are undertaken.

The tool has been developed in a UK manufacturing environment. It has demonstrated its usefulness in the defence industry, but its wider applicability is not yet known. It requires industrialization to make it usable by managers.

Use of the tool has already led to significant changes to the capability development process in a major defence company, and has been used by a board in a civilian company to understand why they have cost overruns and delivery problems.

The paper has not discovered another, simple‐to‐use tool for the same purpose.

Throughout the 21st century, US households have experienced unprecedented levels of leverage. This dynamic has been exacerbated by income shortfalls during the COVID-19 crisis. Leveraging and deleveraging decisions affect household consumption. This study investigates the effect of the dynamics of household leverage and consumption on the stock market.

The authors explore the relation between household leverage and consumption in the context of the consumption capital asset pricing model (CCAPM). The authors test the model's implication that leverage has a negative risk premium by transforming the asset pricing restriction into an unconditional linear factor model and estimate the model using the general method of moments procedure. The authors run time-series regressions to estimate individual stocks' exposures to leverage, and cross-sectional regressions to investigate the leverage risk premium.

The authors show that shocks to household debt have strong and lasting effects on consumption growth. The authors extend the CCAPM to accommodate this effect and find, using various test assets, a negative risk premium associated with household deleveraging. Looking at individual stocks the authors show that the deleveraging risk premium is not explained by well-known risk factors.

This paper contributes to the literature on the role of leverage in economics and finance by establishing a relation between household leverage and spending decisions. The authors provide novel evidence that households' leveraging and deleveraging decisions can be a fundamental and influential force in determining asset prices. Further, this paper argues that household leverage might explain the small, persistent, and predictable component in consumption growth hypothesised in the long-run risk asset pricing literature.

The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and ideology of the FTC’s leaders, developments in the field of economics, and the tenor of the times. The over-riding current role is to provide well considered, unbiased economic advice regarding antitrust and consumer protection law enforcement cases to the legal staff and the Commission. The second role, which long ago was primary, is to provide reports on investigations of various industries to the public and public officials. This role was more recently called research or “policy R&D”. A third role is to advocate for competition and markets both domestically and internationally. As a practical matter, the provision of economic advice to the FTC and to the legal staff has required that the economists wear “two hats,” helping the legal staff investigate cases and provide evidence to support law enforcement cases while also providing advice to the legal bureaus and to the Commission on which cases to pursue (thus providing “a second set of eyes” to evaluate cases). There is sometimes a tension in those functions because building a case is not the same as evaluating a case. Economists and the Bureau of Economics have provided such services to the FTC for over 100 years proving that a sub-organization can survive while playing roles that sometimes conflict. Such a life is not, however, always easy or fun.

The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.