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This paper aims to illustrate, by means of a content analysis of 278 weekly School Meeting minutes, the ways in which student voice is actualized in one democratic free school in Germany.

This paper uses a qualitative content analysis methodology of 278 weekly School Meetings minutes.

This paper uses Fielding’s (2012) patterns of partnership typology to illustrate what counts as student voice and participation in a democratic free school.

Limitations included being reliant on translations of German texts, some missing minutes from the entire set, the lack of a single author for the minutes (and thus degree of detail differs) and the fact that the School Meeting minutes make reference to other meetings for various sub-committees for which no minutes exist, and thus, findings on the degree of student voice may be limited. And because this is a study of one school, generalizability may be difficult. Future research into these sub-committee meetings would prove helpful as well as content analyses of other democratic free schools’ meeting minutes.

This study can help people more deeply understand what goes on in democratic free schools and what student voice and participation can mean within this context.

The conflict between institutionalism and neoclassicism in the 20th century has been investigated by scholars over the years. Many of them believe that in the postwar period, neoclassicism triumphed while institutionalism largely disappeared. The present chapter takes a very different view. The late 20th century represents a broad synthesis of neoclassical and institutional themes in a methodology we call pragmatic empiricism. That approach combines the mathematical model building and theoretical formalism of neoclassical economics with the institutional economist’s data-driven statistical analysis and concern for developing institutional forms. We use as a case study the history of American locational economics from the 1930s to the present. The mixing of institutional and neoclassical themes is quite evident in the work of three young scholars at Harvard who effectively initiated American locational economics. In the postwar period, we find a series of outstanding, well-published papers that capture the spirit of the “founders.” These papers do use more modeling, but they also focus on major institutional developments. A broader review of locational works is consistent with the pragmatic empiricism label. The history of locational economics supports the claim that institutionalism, far from disappearing, continues to provide fundamental questions and techniques for modern pragmatic empiricism.

This paper aims to present new evidence from the Cambridge Study in Delinquent Development (CSDD) showing the extent to which obstetric (e.g. abnormal birth weight, confinement at birth, severe abnormality of pregnancy, etc.) and early childhood and family factors (illegitimate child, unwanted conception, family overcrowding, etc.) have predictive effects on psychopathic traits measured later in life at age 48 years.

Data collected in the CSDD are analysed. This is a prospective longitudinal study of 411 London men from age 8 to age 61 years.

The results suggest that none of the obstetric problems were predictive of adult psychopathy. However, some other early childhood factors were significant. Unwanted conception (by the mother) was significantly associated with high psychopathy. The likelihood of being an unwanted child was higher when the mother was younger (19 years or less), and when the child was illegitimate. The poor health of the mother and living in an overcrowded family were also significant in predicting psychopathy in adulthood, as well as both psychopathic personality (F1) and psychopathic behaviour (F2).

These findings suggest the influence of very early emotional tensions and problematic social background in predicting psychopathic traits in adulthood (at age 48 years). They also emphasise the importance of investigating further the very early roots of psychopathic traits.

Being an efficient mechanism for the value of money, public–private partnership (PPP) is one of the most prominent approaches for infrastructure construction. Hence, many controversies about the performance effectiveness of these delivery systems have been debated. This research aims to develop a novel performance management perspective by revealing the causal effect of key performance indicators (KPIs) on PPP infrastructures.

The literature review was used in this study to extract the PPPs KPIs. Experts’ judgment and interviews, as well as questionnaires, were designed to obtain data. Copula Bayesian network (CBN) has been selected to achieve the research purpose. CBN is one of the most potent tools in statistics for analyzing the causal relationship of different elements and considering their quantitive impact on each other. By utilizing this technique and using Python as one of the best programming languages, this research used machine learning methods, SHAP and XGBoost, to optimize the network.

The sensitivity analysis of the KPIs verified the causation importance in PPPs performance management. This study determined the causal structure of KPIs in PPP projects, assessed each indicator’s priority to performance, and found 7 of them as a critical cluster to optimize the network. These KPIs include innovation for financing, feasibility study, macro-environment impact, appropriate financing option, risk identification, allocation, sharing, and transfer, finance infrastructure, and compliance with the legal and regulatory framework.

Identifying the most scenic indicators helps the private sector to allocate the limited resources more rationally and concentrate on the most influential parts of the project. It also provides the KPIs’ critical cluster that should be controlled and monitored closely by PPP project managers. Additionally, the public sector can evaluate the performance of the private sector more accurately. Finally, this research provides a comprehensive causal insight into the PPPs’ performance management that can be used to develop management systems in future research.

For the first time, this research proposes a model to determine the causal structure of KPIs in PPPs and indicate the importance of this insight. The developed innovative model identifies the KPIs’ behavior and takes a non-linear approach based on CBN and machine learning methods while providing valuable information for construction and performance managers to allocate resources more efficiently.

The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).

In addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.

Results have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.

In this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

The aim of this study is to explore the dual-experiences of AN recovered service providers. Prognoses for anorexia nervosa (AN) and anorexia nervosa-like (AN-like) presenting patients remain poor, and notably, no current treatment approach is reliably successful. Past research into AN has focused on singular experiences, those of either AN patients or those of practitioners providing treatment, but has yet to explore the experiences of recovered AN service users now working as AN service providers.

In this study, four UK-based female participants shared their dual experiences of treatment for AN or AN-like presentations through individual semi-structured interviews. Data collection and analysis were conducted in accordance with an Interpretative Phenomenological Analysis methodology.

Analysis revealed four primary themes, including barriers to accessing services; the impact of treating professionals’ approaches; displacement of responsibility for treating AN; and the value of dual-experience of AN.

This study focuses on AN and AN-like presentations and does not address the other eating disorders. Additionally, only female-identifying individuals volunteered their participation. As such, this study is notably lacking the voices of individuals of other genders.

Participant narratives suggest that improvements in the treatment of AN lie in improving professionals’ understanding of – and compassion towards – this patient group to optimise the power of the therapeutic relationship across all AN-treating professions.

Participants revealed a pervasive misunderstanding of AN among treating professionals that is hindering patients’ treatment and suggested that lived experience can be an asset in a professional context.

Individuals with dual experiences of AN can provide a unique and reflective insight into experiences of treatment through their combined personal and professional expertise and elucidate the experiences that both helped and hindered their own recovery.

Higher education has begun to attend to the importance of collaboration and self-awareness for educating sustainability leaders. However, there has been limited discussion on how to design a pedagogy that supports the development of these competencies, particularly the development of self-awareness. In this chapter, we introduce an experiential pedagogy in which students and faculty work together to develop self-awareness as the basis for sustainability leadership. We present three pedagogical principles that support the emotional learning that is foundational for sustainability leadership: student self-discovery, faculty as co-learners, and a developmentally focused learning environment. We demonstrate how these three principles work together to enable students and faculty to grow their self-awareness, providing the foundation for sustainable leadership. We conclude with a discussion on how management educators can learn from this case to develop sustainability leaders who have the self-awareness and relational competency to lead positive, inclusive organizations that are committed to sustainable business practices.

The market's intense competition, the unpredictability of customer demands and technological advancements are compelling organizations to adopt new approaches, such as agile new product development (ANPD), which enables the introduction of new products to the market in a short span. The existing ANPD literature review articles are lacking in portraying recent developments, potential fields of adoption and the significance of ANPD in organizational development. The primary goal of this article is to investigate emerging aspects, current trends and conduct a meta-analysis using a systematic review of 177 ANPD articles published in peer-reviewed journals between 1998 and 2020.

The articles were categorized based on their year of publication, publishers, journals, authors, countries, universities, most cited articles, etc. The authors attempted to identify top journals, authors, most cited articles, enablers, barriers, performance metrics, etc. in the ANPD domain through the presented study.

The major themes of research articles, gaps and future trends are identified to assist academicians and ANPD practitioners. This study will benefit ANPD professionals by providing them with information on available literature and current ANPD trends.

Through meta-analysis, this study is one of the unique attempt to categorize ANPD articles to identify research gaps and highlight future research trends. A distinguishing feature of the presented study is the identification of active journals, publishers and authors, as well as enablers, barriers and performance metrics.