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A new triage method, MBCE (Medical Bio Social Ethics), is presented with social justice, bio, and medical ethics for critical resource distribution during a pandemic. Ethical triage is a complex and challenging process that requires careful consideration of medical, social, cultural, and ethical factors to guide the decision-making process and ensure fair and transparent allocation of resources. When assigning priorities to patients, a clinician would evaluate each patient’s medical condition, age, comorbidities, and prognosis, as well as their cultural and social background and ethical factors.

A statistical analysis shows no interactions among the ethical triage factors. It implies the ethical components have no moderation effect; hence, each is independent. The result also points out that medical and bioethics may have an affinity for interactions. In such cases, there seem to be some ethical factors related to bio and medical ethics that are correlated. Therefore, the triage team should be careful in evaluating patient cases. The algorithm is explained with case histories of the selected patient. A group of triage nurses and general medical practitioners assists with the triage.

The MBCE triage algorithm aims to allocate scarce resources fairly and equitably. Another ethical principle in this triage algorithm is the principle of utility. In a pandemic, the principle of utility may require prioritizing patients with a higher likelihood of survival or requiring less medical care. The research presents a sensitivity analysis of a patient’s triage score to show the algorithm’s robustness. A weighted score of ethical factors combined with an assessment of triage factors combines multiple objectives to assign a fair triage score. These distinctive features of the algorithm are reasonably easy to implement and a new direction for the unbiased triage principle.

The idea is to make decisions about distributing and using scarce medical resources. Triage algorithms raise ethical issues, such as discrimination and justice, guiding medical ethics in treating patients with terminal diseases or comorbidity. One of the main ethical principles in triage algorithms is the principle of distributive justice.

The discontinuous usage behavior of short video social media presents an ongoing challenge to platform development. The purpose of this study is to investigate the antecedents of intentions to short media discontinuous usage.

This study adopts a Cognition–Affection–Conation (CAC) framework to analyze short video social media discontinuous intention on the basis of cognitive dissonance theory (CDT) and self-efficacy theory. The empirical evaluation of the research model was conducted using SmartPLS 2.0 and was based on questionnaire data obtained from participants in China.

The results show information overload and user addiction have a significant positive association with cognitive dissonance, which is, in turn, found to significantly impact discontinuous usage intention. Self-efficacy moderates the relationships between information overload, user addiction, cognitive dissonance and discontinuous usage.

This study contributes to the understanding of the factors that influence short video discontinuous usage intention and it achieves this by engaging from a CDT perspective and by applying Self-Efficacy Theory. Theoretical implications for future short video platform research, as well as practical suggestions for short video platform operators and users, are also discussed.

The aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.

The paper is designed as a review of the labour vs capital conundrum, the differences between industrial automation and artificial intelligence, threat to employment, the difficulty of substituting, role of soft skills and whether technology leads to the deskilling of human workers or favors increasing human capabilities.

Some authors praise the bright future developments of artificial intelligence while others warn about mass unemployment. Therefore, it is paramount to present an up-to-date overview of the problem, compare and contrast its features with what happened in past innovation waves and contribute to academic discussion about the pros/cons of current trends.

The main value of this paper is presenting a balanced view of 100+ different studies, the vast majority from the last five years. Reading this paper will allow to quickly grasp the main issues around the thorny topic of artificial intelligence and unemployment.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0338

This paper investigates the effect of state-society relations on the industrially-related growth paths of developed countries.

It introduces a novel theoretical framework, the state-business-labor relations (SBLR) framework, where four main actors are identified: the state, big businesspersons or tycoons, owners and managers of small and medium enterprises (SMEs) or Entrepreneurs and labor. Different SBLR categories or modes are introduced depending on levels of coordination and power relations between the studied actors. The paper then investigates how these SBLR modes, through adopting various policies targeting the industrial sector, lead to different growth paths. Rather than focusing only on economic growth, this research regards a growth path as a matrix of the performance in long-run growth and equality of distribution.

Using regression analysis and statistical data, the results suggest that the Co-Balanced mode, having higher levels of coordination and lower favoritism, leads to the best growth path among the four introduced modes, especially with its emphasis on high levels of venture capital availability and easiness of starting business. while the Lib-Capture mode, characterized by lower coordination and higher favoritism, seems to have the worst growth path and the best implemented policy for this mode is suggested to be high profit taxes that seem to counter the negative impact of the existing high levels of favoritism.

Despite the important findings that this research has reached, this paper is mainly meant to open a further investigation into this topic and open this dimension that the research on VoC and political economy have under-researched. A deeper investigation of SBLR typologies that could only be possible by having richer datasets with more data on coordination for the whole world, rather than only the advanced economies, would further our understanding of the dynamics that shape the growth paths of different countries of the world.

To realize the best industrial growth path, fighting favoritism should be an important objective. The negative impact of favoritism on innovation could not be disregarded in the eve of the fourth industrial revolution, where innovation is increasingly pivotal to future industrial development. Actively engaging societal groups in the policymaking process is important in addressing their concerns and balancing them at the same time. This should lead to the double benefit of formulating better policies that should foster growth as well as provide better distribution of this growth. High levels of coordination should help in realizing this objective. Yet, this could only be possible if societal groups are free to associate and aggregate their power and when there are means of preventing one actor from gaining more favorite treatment and exclusive influence over policymakers. The presence of both powerful and broadly represented business associations and labor unions and the existence of a government interested in coordinating their efforts-rather than letting itself be controlled by one group at the expense of the others-should help in the realization of the best growth path. Thus, institutional reform that empowers societal groups and enables them to defend their interests as well as fights all forms of corruption should lead to the realization of a more prosperous and equitable industrial development, with the “re-industrialization” of the developed world being no exception. The technological and social challenges of intensive automation and digitalization accompanying the fourth industrial revolution make the envisaged institutional reform more urgent.

This paper is introducing a novel theoretical framework for studying the effect of state-society relations, particularly SBLR, on the industrial growth paths of developed countries. It integrates three important bodies of literature in order to build a more comprehensive understanding of the dynamics of state-society relations and their economic consequences. These are the Varieties of Capitalism (VoC), State-Business Relations (SBR) and Industrial Relations. The SBLR framework differentiates between tycoons and entrepreneurs, an important distinction that often goes unnoticed. Different SBLR categories or modes are introduced, depending on levels of coordination and power relations between the actors. It is proposed in this research that the effect on growth paths goes beyond the simple dichotomy between CMEs and LMEs usually present in the literature of VoC and that power relations provide an essential complementary dimension in explaining this causality.

Charitable giving in China has moved from being subjected to government attention and public skepticism to receiving government encouragement and public support. The role played by political connections in philanthropy is indisputable, although very few studies have explored their association from the perspective of the country’s first Charity Law of 2016. This study aims to contribute to the ongoing debate about the 2016 Charity Law and offers an understanding of the future trends in corporate charitable giving.

Using empirical analysis of data collected from listed companies in China, this study analyzes the impact of political connections on corporate charitable giving before and after the 2016 Charity Law. The study adopts three leading theories from previous research into corporate charitable giving and political connections: corporate social responsibility, resource dependence theory and stakeholder theory. A conceptual framework is outlined, and hypotheses are formulated accordingly.

The results show that political connections have a substantial positive impact on corporate charitable giving, both before and after the implementation of the 2016 Charity Law, which has significantly promoted and increased the amount and proportion of charitable giving. Although the 2016 Charity Law attempted to weaken the political connections of enterprises, the influence of political connections on corporate charitable giving has proved difficult to diminish or eliminate, as charity is dominated by the state.

This study explores the association between political connections and corporate charitable giving from the perspective of China’s Charity Law of 2016.

Language plays a complex role in coaching, facilitating communication, comprehension and meaning construction. Yet, the implications of coaching in a non-native language are uncertain and under-researched. This study explores the role of non-native language (NNL) in dyadic workplace coaching practice. Specifically, it explores how working in a NNL influences the coaching experience from the coach’s perspective.

A qualitative approach was chosen to explore the way coaches view coaching in a NNL. Twenty-three semi-structured interviews were conducted with coaches experienced in coaching in NNL. Reflexive thematic analysis (RTA) was applied for data analysis.

NNL coaching presents a paradoxical mix of negative and positive tensions for the coach and coachee in communication, relationship and insight. NNL coaching is nuanced and may be accommodated using coaching competencies to mitigate the potential for misunderstanding and relationship rupture. It offers alternative perspectives to existing worldviews, eliciting deeper insights. Coaches’ confidence in coaching in a NNL varies from a challenging struggle that perceptually hinders performance, through ambivalence, to a sense of greater resourcefulness.

The study contributes to the stream of literature on language in international business, sociolinguistic research and how meaning is constructed in a coaching process. First, the work develops a distinction between coaching in a native language (NL) and a NNL. Second, study results indicate that the context of NNL creates challenges as well as opportunities in a dyadic coaching process, particularly regarding aspects of the coach–coachee relationship and insight elicitation via alternative perspectives. Moreover, several practical implications of the study for the coaching practice are discussed.

This study aims to investigate whether social investment (SI) policies improve employment among single mothers.

This paper analyzes the potential effects of SI policies on vulnerable individuals and workers at the macro level by using the employment position of single mothers as a dependent variable. Time-series cross-national data from 18 OECD countries between 1998 and 2017 are analyzed. Multilevel model analysis is also used for robustness check.

I find that public spending on education and family support is positively associated with the employment rates of single mothers. In contrast, active labor market policy (ALMP) spending is negatively associated. ALMP’s negative effects stand out particularly with public spending on job training. Of all family support policies, family allowances are positively associated with single mothers’ employment, which runs counter to the conventional argument that family allowances are a disincentive for women’s or mothers’ employment. Paid leave (length and generosity) is also associated with higher employment for single mothers. There is also some tentative evidence that public spending on maternity leave benefits (spending level) may raise the odds of single mothers being employed, when individual-level factors are controlled for in multilevel analysis we implement for robustness check.

This paper does not analyze the effects of the qualitative properties of SI policies. Future research is necessary in this respect.

The effects of SI policies on employment among single mothers have not yet been examined in the literature. This paper seeks to be a first cut at measuring the effects.

The aim of this paper is to empirically investigate whether social contacts can mediate the way in which current unemployment impacts future unemployment.

We use 2006–2017 data from the Household Income and Labour Dynamics in Australia (HILDA) survey and a dynamic random-effects model to describe the evolution of individual unemployment status over time.

Once controlled for the local context where individuals live and create friendships, we find that above-average social contacts reduce unemployment persistence. However, social contacts seem to be slightly less effective in deprived neighborhoods. These findings are consistent with the idea that individuals obtain information about job opportunities through a network of social contacts, and unemployment may lead to a decay of social capital, making it more difficult to find employment in future periods. Our results also show that neighborhood deprivation increases individual unemployment risk, while above-average neighborhood cohesion reduces the probability of unemployment in deprived neighborhoods.

Although many studies have been published on unemployment persistence, to the best of the author's knowledge, this is the first study quantifying the impact of social contacts on unemployment persistence. The study also offers fresh empirical evidence on the impact of neighborhood characteristics on unemployment risk.

This study longitudinally investigated the predictors and mediators of adolescent smartphone addiction by examining the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3, as well as the separate and sequential role of adolescent self-esteem and depression at T2 as mediating factors.

This study used a hierarchical regression and the PROCESS macro (Model 6) to investigate research model by collecting 3,904 parent-adolescent pairs. Panel data were collected from three waves of the Korean Children and Youth Panel Survey (KCYPS).

First, the result showed that parental smartphone addiction at T1 significantly and positively predicted adolescent smartphone addiction at T3. Second, the serial mediation analysis revealed that the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3 was mediated by adolescent self-esteem and depression at T2 independently and serially.

The findings enhance our comprehension of the impact of parental smartphone addiction, adolescent self-esteem and depression, on adolescent smartphone addiction.

Gender and geographical imbalance in production and impact levels is a pressing issue in global knowledge production. Within Health Sciences, while some studies found stark gender and geographical biases and inequalities, others found little empirical evidence of this marginalization. The purpose of the study is to clear the ambiguity concerning the topic.

Based on a comprehensive and systematic analysis of Health Sciences research data downloaded from the Scival (Scopus/Scimago) database from 2017 to 2020 (n = 7,990), this study first compares gender representation in research productivity, as well as differences in terms of citation per document, citations per document view and view per document scores according to geographical location. Additionally, the study clarifies whether there is a geographic bias in productivity and impact measures (i.e. citation per document, citations per document view and view per document) moderated by gender.

Results indicate that gender inequalities in productivity are systematic at the overall disciplinary, as well as the subfield levels. Findings also suggest statistically significant geographical differences in citation per document, citations per document view, and view per document scores, and interaction effect of gender over the relation between geography and (1) the number of citations per view and (2) the number of views per document.

This study contributes to scientometric studies in health sciences by providing insightful findings about the geographical and gender bias in productivity and impact across world regions.