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In exploring the impact of reflective and work applied approaches, the authors are curious how vivid new insights and collective “Eureka” momentums occur. These momentums can be forces for work communities to gain competitive advantages. However, the authors know little of how learning is actively involved in the processing of creating new insights and how such a turning to learning mode (Pässilä and Owens, 2016) can be facilitated. In the light of cultural studies and art education, the purpose of this paper is to explore how the method of dramatising characters (DC) in a specific innovation culture can be facilitated. In this viewpoint, the authors are suggesting one approach for this type of turning to learning which the authors call Beyond Text, outlining its theoretical underpinnings, its co-creative development and its application.

In this Beyond Text context, the authors are introducing the method of DC and the method of iStory both of which are the authors’ own design based on the theory of the four existing categories of a research-based theatre.

The findings of this viewpoint paper are that both iStory as well as DC methods are useful and practical learning facilitation processes and platforms that can be adopted for use in organisations for promoting reflexivity. Especially they can act as a bridge between various forms of knowing and consummate the other knowledge types (experiential, practical and propositional) in a way that advances practice-based innovation.

The originality and value of iStory and DC is that they can be utilised as dialogical evaluation methods when traditional evaluation strategies and pre-determined indicators are unusable.

A policy of surveillance which interferes with the fundamental right to a private life requires credible justification and a supportive evidence base. The authority for such interference should be clearly detailed in law, overseen by a transparent process and not left to the vagaries of administrative discretion. If a state surveils those it governs and claims the interference to be in the public interest, then the evidence base on which that claim stands and the operative conception of public interest should be subject to critical examination. Unfortunately, there is an inconsistency in the regulatory burden associated with access to confidential patient information for non-health-related surveillance purposes and access for health-related surveillance or research purposes. This inconsistency represents a systemic weakness to inform or challenge an evidence-based policy of non-health-related surveillance. This inconsistency is unjustified and undermines the qualities recognised to be necessary to maintain a trustworthy confidential public health service. Taking the withdrawn Memorandum of Understanding (MoU) between NHS Digital and the Home Office as a worked example, this chapter demonstrates how the capacity of the law to constrain the arbitrary or unwarranted exercise of power through judicial review is not sufficient to level the playing field. The authors recommend ‘levelling up’ in procedural oversight, and adopting independent mechanisms equivalent to those adopted for establishing the operative conceptions of public interest in the context of health research to non-health-related surveillance purposes.

The association of work and learning has been well established for many years. However, some of the terms used to describe the various pedagogies related to work and learning have been used interchangeably, with many lacking definitional clarity and scope. These include work-related learning (WRL), work-based learning, workplace learning (WPL) and work-integrated learning (WIL). This agglomerating approach to usage has resulted in pedagogical confusion and what some theorists call a “problematization” for the field, resulting in undermining shared understanding and potential benefit. The purpose of this conceptual paper is an attempt to unpack the meaning and application of some of the key pedagogical terms used in the applied field of work + learning theory and practice.

Conceptual modelling and qualitative descriptions of each pedagogy.

Many of the work + learning pedagogies do overlap and cohere but attempts to create umbrella terms, which apply to all theories and approaches, are misguided; definitional clarity with the different modes of practice is required for sustainable educational outcomes.

A proto-theoretical model, along with a breakdown of distinguishing features of each term as well as their source in the published literature, has been developed to improve clarity and aid the future praxis of educators.

Flexible staffing arrangements have become a permanent feature of employment in many industrial societies. This article examines how employers perceive the consequences of using flexible staffing arrangements. It presents and assesses theoretically informed hypotheses on organisational situations in which negative consequences are more likely to be perceived.

This study uses data (n = 761) from a bespoke employers survey, fielded in the Netherlands in 2019. Structural equation modelling (SEM) is used to measure and explain employers' perception of downsides to flexible staffing arrangements.

Employers report distinct downsides to the use of flexible staffing arrangements in terms of performance, management and employee well-being. Model estimates show that employers using flexible staffing arrangements to acquire specific expertise or to follow other organisations in their sector perceive more downsides.

Empirical research on employers' perception of the disadvantageous consequences of using flexible staffing arrangements is scarce. This article highlights that this practice can discourage investments in human capital and lead to a sense of insecurity among young workers. It draws attention to the relevance of distinguishing between strategic motives when trying to understand organisational behaviour regarding non-standard forms of employment.

Givensocietalcallsfortransformationalleadershipthatwillliftpeopletohigherlevelsof motivation and critical consciousness, this paper critiques existing student leadership education efforts and proposes that leadership educators adopt core tenets of feminism in order to prepare students to be engaged, change-oriented leaders in their communities. Today’s literature on student leadership development places an over-emphasis on positional leadership, technical problems, and leadership competencies. Feminism can serve as a theoretical strategy for addressingtheseproblemsbyconsideringthecomplexitiesofidentity,re-conceptualizingpower, amplifying student voice, and encouraging activism. In particular, we argue that consciousness- raising is essential for leadership development and offer ways in which it can be employed within leadership curriculum, among student leaders, and among leadership educators.

This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.

Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.

Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.

This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.

This paper aims to offer the first known synthesis of peer-reviewed literature on trade-based money laundering (TBML). Given the topic is in its nascent stage yet gaining prominence across scholarship and practice, this foundation is pertinent for future TBML research.

A systematic literature review was undertaken with a formulaic search string. Both qualitative (thematic) and quantitative (meta) analysis methods were used to illustrate the findings.

The systematic literature review, using qualitative and quantitative synthesis, led to a thematic categorization of extant TBML literature into four categories: TBML risk assessment, TBML detection, the role of professionals and understanding of TBML. Due to the limited number of studies, insights that can be drawn from the extant literature on the best way to combat TBML are also limited.

As the first systematic literature review on TBML, this study identified that the existing TBML literature has focused on increasing the understanding of the phenomenon in terms of its definition and mechanisms, detection, linkage with other crimes, such as organized crime and terrorism financing, and risk assessment frameworks. The originality of these findings lies in identifying areas future researchers might explore to broaden the academic literature.

Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.