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In recent decades, school discipline has become increasingly characterized by zero-tolerance policies that mandate predetermined punitive consequences for specific offenses. Zero-tolerance policies have not been shown to improve student behavioral outcomes or school climate. Further, these disciplinary policies are applied unevenly across schools and student populations. Despite the well-documented research base that demonstrates that these practices are ineffective, they remain commonplace in K-12 school across the United States. Transformative and culturally responsive educational leadership requires school leaders to examine the historical, societal, and institutional factors that contribute to the racial-discipline gap within their particular schools. This process requires committing to leading for racial justice, self-reflexive practice, and having the courage to boldly name and dismantle practices that do not create equitable outcomes for students on the margins. Drawing on tenets of Critical Race Theory and Culturally Responsive School Leadership to situate the history and proliferation of harmful disciplinary practices, this chapter discusses how critically reflexive school leaders can mobilize restorative practices to dismantle the systems, structures, and practices that reproduce inequities in schools. The chapter provides aspiring and practicing school leaders with the knowledge needed to reform existing school discipline policies and implement practices that support racial justice.

Despite the present focus on improving the resilience of homes to flooding in UK flood risk management policy and strategy, a general measurement framework for determining levels of flood resilience in UK homes does not exist. In light of this, the aim of this study was to develop a means to evaluate the levels of resilience in flood-prone homes from the perspective of homeowners'.

A quantitative research methodology was employed, with empirical data obtained through a postal survey of homeowners who had experienced flooding. The responses received were then analysed using a combination of statistical techniques including agreement/reliability tests and multiple regression to develop a model of flood resilience.

A predictive model was developed that allows the resilience of a property to be quantified and measured as perceived by homeowners. The findings indicate that the main factors found to influence the level of flood resilience were: property type (PT), presence of cellar/basement (C/B), property wall type (PWT), property ground floor type (PGFT), kitchen unit type (KU), flood experience (FE), flood source (FS) and flood risk level (FRL).

The resulting model provides unique insights into resilience levels to the benefit of a range of stakeholders including policy makers (such as Defra/Environment Agency), Local Authority flood teams, property professionals, housing associations and homeowners. As a result, homeowners will be in a better position to determine which interventions should be prioritised to ensure better flood protection.

This is the first study of its kind to have rigorously quantified the level of flood resilience for individual homes. This study has quantified the effectiveness of individual resilience measures to derive the first reliable means to measure the overall levels of resilience at the individual property level. This is regarded as a significant contribution to the study of flood risk management through the quantification of resilience within individual UK homes, enabling the prioritisation of interventions and the overall monitoring of resilience.

The rapid advancement of artificial intelligence (AI), particularly within the last decade and the application of ‘deep learning’, has simultaneously accelerated human fears of the changes AI provokes in human behaviour. The question is not any more if the new phenomena, like artificially-induced consciousness, empathy or creation, will be widely used, but whether they will be used in ethically acceptable ways and for ethically acceptable purposes.

Departing from a diagnosis of the state humans have brought themselves to by (ab)use of technology, the present chapter investigates the possibility of a systematic study of adaptations human society will have to consider in order to guarantee the obeyance to the fundamental ethical values and thus its spiritual survival. To that end, a new discipline – epharmology (from the Greek epharmozein = to adapt) is proposed, together with its aims and methodology.

The purpose of this paper was to examine the two-factor theory (Herzberg et al., 1959), determining whether millennials experience similar job satisfaction and dissatisfaction with Herzberg et al.’s motivation/hygiene descriptors as they relate to job enrichment.

This paper analyzed the historical relevancy of Herzberg et al.’s controversial motivation theory to 21st-century workers. Extensive research of scholarly journal articles included historical studies and recent studies from 1919 to 2024.

In the late 1950s, Herzberg, Mausner and Snyderman identified, from two simple reflective questions to participants, 14 work factors, which vary in the degree of motivational effect across two independent continuums of satisfaction and dissatisfaction. Given the seminal work by Herzberg et al. in this area of motivation and hygiene factors, as well as subsequent contributors in the field, the authors of this study explored the role of generational motivational changes as they relate to job enrichment.

The authors offer a reassessment of the Herzberg motivation theory to account for the generational differences that might influence its practice in the current historical context. The authors laid a foundation for further inquiry into how future workplace motivational choices compare with past generations, potentially increasing performance, and higher levels of personal achievement.

The health, well-being and productivity (i.e. WELL) of office building occupants are vulnerable to poor office environments. Therefore, this study aims to identify new features and concepts of office buildings in supporting occupants’ WELL. To achieve that aim, this study: explores new WELL features for office buildings, develops new WELL concepts for office buildings and examines the influence of the newly developed WELL concepts on existing WELL building standard (WELL v2) concepts.

The first phase involved ten experts to assign weightage for health, well-being and productivity. In the second phase, 206 questionnaire survey data were collected from office building occupants throughout Malaysia. Exploratory factor analysis established new WELL concepts for office buildings. Partial least-squares structural equation modelling examined the influence of the newly developed WELL concepts on the existing WELL v2 concepts.

Two new WELL concepts were developed: “space and services”, consisting of sufficient space, workstation privacy, office layouts, building automation systems, cleanliness and information technology (IT) infrastructure, and “building security”, consisting of security systems and safety at parking lots. Here, “space and services” influences all existing WELL v2 concepts, and “building security” influences the water, nourishment, mind and community concepts of WELL v2.

This study uncovers holistic WELL building concepts to support occupants’ health, well-being and productivity with additional new features and concepts for construction industry policymakers to establish holistic building assessment tools.

Nowadays, the main challenge in the higher education is the daunting task of transforming universities into digital era institutions. Improving HE students' competence to meet the flow of technological innovations through DT has been the focus of many countries. This task has imposed the restraint that HE institutions should implement the most effective strategies of DT. This chapter is focusing on how DT strategies play their role in making the transformation itself become germane and give its fruits. Therefore, this chapter presents the most effective DT strategies that can be implemented by HE institutions in order to prepare their students for the existing professional roles in their societies. A good DT strategy is one that connects the organization's current level of digital maturity with its future ambition. The well-known strategies in the DT field are as follows: the strategy of electronic projects, strategy of smart electronic platforms, integrated training strategy, participatory e-learning strategy, smart learning strategy, pervasive learning strategy, microlearning strategy and e-design thinking strategy, in addition to the strategy in which traditional learning methods are combined with e-learning methods. It is worth noting here that the chapter is not an attempt to favor a strategy over another or compare and contrast them to uncover their differences at any level. On the contrary, the writer will work on displaying how each strategy can be implemented in order to accomplish DT in HE instructional practices. Also, this chapter will show how complementary these strategies can be once they are utilized to reach DT.

This paper aims to discuss the scholarship over the past 30 years on what used to be called Melanesian warfare or “tribal fighting” and is termed in this paper “intergroup conflict” in the Highlands of Papua New Guinea. The paper categorises the drivers of intergroup conflict that make up the landscape for conflict in the Highlands. It starts with cultural factors and the understandings about conflict that have long been used to explain such violence, then adds newer factors. It argues that while the individual existence of each driver is important, far more important is the way in which they interact with each other in reinforcing feedback loops that propel the actors involved towards violence.

The paper is based on a thorough review of the scholarly and grey literature on the topic, drawing from the fields of anthropology, criminology, political science, law, justice and peacebuilding.

The overall finding of the paper is that the nature of intergroup conflict, its scale and dynamics, has changed considerably over the past 30 years, most prominently in the entanglement of the state with local-level conflicts. This has significantly affected the nature of intergroup conflict today, deepening the attractors towards violence and conflict, while weakening the ability of existing state and non-state systems to prevent it. The picture that emerges is one in which the interconnectivity of factors promoting violence has intensified, the rate of change is accelerating and levels of violence are amplified.

This paper is an original work.

Product returns are a major challenge for e-businesses as they involve huge logistical and operational costs. Therefore, it becomes crucial to predict returns in advance. This study aims to evaluate different genres of classifiers for product return chance prediction, and further optimizes the best performing model.

An e-commerce data set having categorical type attributes has been used for this study. Feature selection based on chi-square provides a selective features-set which is used as inputs for model building. Predictive models are attempted using individual classifiers, ensemble models and deep neural networks. For performance evaluation, 75:25 train/test split and 10-fold cross-validation strategies are used. To improve the predictability of the best performing classifier, hyperparameter tuning is performed using different optimization methods such as, random search, grid search, Bayesian approach and evolutionary models (genetic algorithm, differential evolution and particle swarm optimization).

A comparison of F1-scores revealed that the Bayesian approach outperformed all other optimization approaches in terms of accuracy. The predictability of the Bayesian-optimized model is further compared with that of other classifiers using experimental analysis. The Bayesian-optimized XGBoost model possessed superior performance, with accuracies of 77.80% and 70.35% for holdout and 10-fold cross-validation methods, respectively.

Given the anonymized data, the effects of individual attributes on outcomes could not be investigated in detail. The Bayesian-optimized predictive model may be used in decision support systems, enabling real-time prediction of returns and the implementation of preventive measures.

There are very few reported studies on predicting the chance of order return in e-businesses. To the best of the authors’ knowledge, this study is the first to compare different optimization methods and classifiers, demonstrating the superiority of the Bayesian-optimized XGBoost classification model for returns prediction.

Structural mentoring barriers are policies, practices and cultural norms that collectively disadvantage marginalized groups and perpetuate disparities in mentoring. This study aims to better understand structural mentoring barriers at the postdoctoral training stage, which has a direct impact on faculty diversity and national efforts to retain underrepresented groups in research careers.

A diverse sample of postdoctoral scholars (“postdocs”) from across the USA were asked to participate in focus groups to discuss their training experiences. The authors conducted five 90-min focus groups with 32 biomedical postdocs, including 20 (63%) women and 15 (47%) individuals from underrepresented racial/ethnic groups (URG).

A social-ecological framework was used to categorize both the upstream and downstream manifestations of structural mentoring barriers, as well as mentoring barriers, overall. Notable structural barriers included: academic politics and scientific hierarchy; inequalities resulting from mentor prestige; the (over) reliance on one mentor; the lack of formal training for academic and non-academic careers; and the lack of institutional diversity and institutional mentor training. To overcome these barriers, postdocs strongly encouraged developing a network or team of mentors and recommended institutional interventions that create more comprehensive professional development, mentorship and belonging.

For postdoctoral scientists, structural mentoring barriers can permeate down to institutional, interpersonal and individual levels, impeding a successful transition to an independent research career. This work provides strong evidence for promoting mentorship networks and cultivating a “mentoring milieu” that fosters a supportive community and a strong culture of mentorship at all levels.