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This paper aims to formalize long-term trajectories of human civilization as a scientific and ethical field of study. The long-term trajectory of human civilization can be defined as the path that human civilization takes during the entire future time period in which human civilization could continue to exist.

This paper focuses on four types of trajectories: status quo trajectories, in which human civilization persists in a state broadly similar to its current state into the distant future; catastrophe trajectories, in which one or more events cause significant harm to human civilization; technological transformation trajectories, in which radical technological breakthroughs put human civilization on a fundamentally different course; and astronomical trajectories, in which human civilization expands beyond its home planet and into the accessible portions of the cosmos.

Status quo trajectories appear unlikely to persist into the distant future, especially in light of long-term astronomical processes. Several catastrophe, technological transformation and astronomical trajectories appear possible.

Some current actions may be able to affect the long-term trajectory. Whether these actions should be pursued depends on a mix of empirical and ethical factors. For some ethical frameworks, these actions may be especially important to pursue.

The great filter and an unfriendly artificial general intelligence might pose existential risks to humanity, but these two risks are anti-correlated. The purpose of this paper is to consider the implications of having evidence that mankind is at significant peril from both these risks.

This paper creates Bayesian models under which one might get evidence for being at risk for two perils when we know that we are at risk for at most one of these perils.

Humanity should possibly be more optimistic about its long-term survival if we have convincing evidence for believing that both these risks are real than if we have such evidence for thinking that only one of these perils would likely strike us.

Deriving implications of being greatly concerned about both an unfriendly artificial general intelligence and the great filter.

December 6, 1971 Master and servant — Negligence — Noise — Deafness — Workman subjected to loud noise at work — Ear plugs providing inadequate protection — Ear muffs not supplied — No encouragement or persuasion to wear ear muffs — Whether negligence — Further loss of hearing resulting from continued negligence after statute‐barred period — Whether full damages recoverable.

This study aims to provide a new vision for investigating the different human resources management (HRM) practices in hotels after the COVID-19 pandemic.

A quantitative research approach was adopted using confirmatory factor analysis and structural equation modeling to reveal updated priorities and relations as stated by 504 hospitality employees.

The research approach contributed to highlighting exciting findings, as training and development (T&D) had an insignificant effect on turnover intention (IT) or affective organizational commitment (AOC) following the COVID-19 pandemic; job security (JS) had the highest impact on AOC and compensation had the highest effect on TI.

Individual HRM practices have different strong impacts on employee outcomes. This paper provides human resource directors with realistic and practical implications to boost individuals' AOC and reduces their intention to quit their job in conditions of uncertainty and ambiguity.

This pioneering study reveals the influence of HRM practices in the hospitality HRM systems regarding employee attitudes and behaviors, especially after the COVID-19 pandemic. It provides novel theoretical and practical contributions.

In the last few decades, there has been growing interest in forecasting with computer intelligence, and both fuzzy time series (FTS) and artificial neural networks (ANNs) have gained particular popularity, among others. Rather than the conventional methods (e.g., econometrics), FTS and ANN are usually thought to be immune to fundamental concepts such as stationarity, theoretical causality, post-sample control, among others. On the other hand, a number of studies significantly indicated that these fundamental controls are required in terms of the theory of forecasting, and even application of such essential procedures substantially improves the forecasting accuracy. The aim of this paper is to fill the existing gap on modeling and forecasting in the FTS and ANN methods and figure out the fundamental concepts in a comprehensive work through merits and common failures in the literature. In addition to these merits, this paper may also be a guideline for eliminating unethical empirical settings in the forecasting studies.

The purpose of this paper is to investigate the contextual factors contributing to the sustainability of healthcare quality improvement (QI) initiatives.

Themes from semi-structured interviews with international healthcare leaders are compared with Kaplan and Provost et al.’s (2012) model for understanding success in quality (MUSIQ). Critical success factors within these themes are shown in detail.

The interviews provide a rich source of information on critical success factors. The themes largely correspond with MUSIQ, reinforcing its robustness. An important factor emerging from the interviews was the importance of engagement with patients and families in QI, and this needs consideration in seeking to understand context in QI.

Interview participants represent a limited set of western countries and health systems. Their experiences may not hold true in other settings.

The detail on critical success factors provides QI practitioners with guidance on designing and implementing sustainable initiatives.

Including consideration of contextual factors for engagement with patients and families in frameworks for context in QI appears to be an original idea that will add value to such frameworks. Researchers in patient engagement are starting to address contextual factors and connections should be made with this work.