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In this chapter, I will outline the labels of giftedness and underachievement and present the theoretical debates surrounding these labels. A historicist examination of these labels follows, highlighting how the gifted underachievement (GUA) label emerges through the negation of “giftedness.” Subsequently, I explore the concept of GUA and its negative connotations, stemming from the positive valuation inherent in the term “giftedness” and its implications for what is considered “normal.” This chapter also reviews perspectives on shifting the focus away from the individual within the current paradigm of labeling giftedness and explores insights from systemic thinking and symbolic interactionism (SI). The conclusion underscores the necessity of a symbolic interactionist perspective to address the gaps in research on the labeling of giftedness and underachievement. Finally, I propose a generic definition that can be used in GUA research in the light of SI.

In this paper, the author advocates recognizing, developing, and promoting “critical interactionism” as a legitimate and pragmatically useful scholarly project. The author argues that critical interactionism includes different interactionist traditions, critical approaches, methodological styles, and sensitizing concepts – as long as they tell us something about how power and inequality operate. I review two fundamental elements of this project that constitute its past and likely future: (1) theoretical interventions that excavate critical insights, diversify founders, integrate critical theories, and promote interactionism's usefulness for critical inquiry and (2) empirically grounded conceptual interventions that shed light on generic processes of inequality reproduction. Although the larger discipline of sociology continues to marginalize interactionism yet selectively adopt its principles, critical interactionism has the potential to break through what David Maines called the fault line of consciousness. The promise of critical interactionism is that it can simultaneously make interactionism more relevant to our discipline and make our discipline more relevant to the social world.

This paper aims to study the impact of consumers’ corporate social responsibility (CSR) associations on corporate financial performance and the moderating role of market competition.

The panel data set is analyzed using a random effects regression model. The analyzed data is based on the unique RepZ Responsibility scores published by the global research agency Kantar Millward Brown and contains information about consumer CSR associations.

This study reveals CSR associations' positive, lagged, direct impact on firms’ market value. Market competition moderates this relationship in the way that a company’s market value benefits more from consumers' CSR associations when facing high rather than low market competition.

Consumers' CSR perceptions increase the market value of a company. This effect is intensified when brands are exposed to intense competition, which allows conclusions about CSR as a differentiation strategy to be drawn: To stand out in a competitive market, brands should prioritize improving their CSR associations among consumers to differentiate themselves and increase their market value.

To the best of the authors’ knowledge, this study is the first to test the effect of consumers’ CSR associations on forward-looking financial performance measures. Moreover, by analyzing the moderating effect of market competition on the relationship between CSR associations and firms' market value, this study provides information about the differentiating power of CSR from a brand perspective using a panel-data analysis.

The purpose of this multi-voiced paper is to propose a prosocial paradigm for the field of performance management and management control systems. This new paradigm suggests cultivating prosocial behaviour and prosocial groups in organizations to simultaneously achieve the objectives of economic performance and sustainability.

The authors share a common concern about the future of humanity and nature. They challenge the influential assumption of economic man from neoclassical economic theory and build on evolutionary science and the core design principles of prosocial groups to develop a prosocial paradigm.

Findings are based on the premise of the prosocial paradigm that self-interested behaviour may outperform prosocial behaviour within a group but that prosocial groups outperform groups dominated by self-interest. The authors explore various dimensions of performance management from the prosocial perspective in the private and public sectors.

The authors call for theoretical, conceptual and empirical research that explores the prosocial paradigm. They invite any approach, including positivist, interpretive and critical research, as well as those using qualitative, quantitative and interventionist methods.

This paper offers implications from the prosocial paradigm for practitioners, particularly for executives and managers, policymakers and educators.

Adoption of the prosocial paradigm in research and practice shapes what the authors call the prosocial market economy. This is an aspired cultural evolution that functions with market competition yet systematically strengthens prosociality as a cultural norm in organizations, markets and society at large.

The Third Sector has been receiving increasing attention from society, including academics, due to its importance in the face of the lack of government responses to many of the social problems that affect contemporary societies. Theoretically, the State is supposed to highlight the importance of the services provided by Social Solidarity Institutions, given their proximity to the beneficiaries, the efficiency in the distribution of resources and their innovative attitude towards social problems and needs. As a logical consequence, society is witnessing an increase in the participation of the private sector in social issues and a greater professionalisation of the Third Sector in the search for sustainability. Within the Third Sector, Social Solidarity Institutions play a very important role, acting as social actors. Within the environment of Social Solidarity Institutions, the Misericórdias also play a very important role. ‘Misericórdia’ is a non-profit institution that takes a form of charity, very popular in some countries, such as Italy and especially in Portugal. However, there are few studies on the governance conditions of this type of institution. In addition, it is possible to discuss whether there is any study that focuses specifically on this type of analysis. This study fills the empirical gap in the existing literature, providing an insight into the ways of adopting governance practices and principles within these institutions, which over five centuries of existence have continuously worked towards a more just, inclusive and supportive society.

The authors passively apply a researcher profile pitch (RPP) template tool in accounting and across a range of Business School disciplines.

The authors document a diversity of worked examples of the RPP. Using an auto-ethnographic research design, each showcased researcher reflects on the exercise, highlighting nuanced perspectives drawn from their experience. Collectively, these examples and associated independent narratives allow the authors to identify common themes that provide informative insights to potential users.

First, the RPP tool is helpful for accounting scholars to portray their essential research stream. Moreover, the tool proved universally meaningful and applicable irrespective of research discipline or research experience. Second, it offers a distinct advantage over existing popular research profile platforms, because it demands a focused “less”, that delivers a meaningful “more”. Further, the conciseness of the RPP design makes it readily amenable to iteration and dynamism. Third, the authors have identified specific situations of added value, e.g. initiating research collaborations and academic job market preparation.

The RPP tool can provide the basis for developing a scalable interactive researcher exchange platform.

The authors argue that the RPP tool potentially adds meaningful incremental value relative to existing popular platforms for gaining researcher visibility. This additional value derives from the systematic RPP format, combined with the benefit of easy familiarity and strong emphasis on succinctness. Additionally, the authors argue that the RPP adds a depth of nuanced novel information often not contained in other platforms, e.g. around the dimensions of “data” and “tools”. Further, the RPP gives the researcher a “personality”, most notably through the dimensions of “contribution” and “other considerations”.

Magnetic polarizability tensors (MPTs) provide an economical characterisation of conducting magnetic metallic objects and their spectral signature can aid in the solution of metal detection inverse problems, such as scrap metal sorting, searching for unexploded ordnance in areas of former conflict and security screening at event venues and transport hubs. In this work, the authors aim to discuss methods for efficiently building large dictionaries for classification approaches.

Previous work has established explicit formulae for MPT coefficients, underpinned by a rigorous mathematical theory. To assist with the efficient computation of MPTs at differing parameters and objects of interest, this work applies new observations about the way the MPT coefficients can be computed. Furthermore, the authors discuss discretisation strategies for hp-finite elements on meshes of unstructured tetrahedra combined with prismatic boundary layer elements for resolving thin skin depths and using an adaptive proper orthogonal decomposition (POD) reduced-order modelling methodology to accelerate computations for varying parameters.

The success of the proposed methodologies is demonstrated using a series of examples. A significant reduction in computational effort is observed across all examples. The authors identify and recommend a simple discretisation strategy and improved accuracy is obtained using adaptive POD.

The authors present novel computations, timings and error certificates of MPT characterisations of realistic objects made of magnetic materials. A novel postprocessing implementation is introduced and an adaptive POD algorithm is demonstrated.

This research investigates the effect of audit report lag on the cost of equity capital. We argue that an extended audit report lag reduces the value of information and raises concerns for investors, resulting in an increased cost of equity capital.

We hypothesize that audit report lag increases the firm cost of equity capital. We conduct ordinary least squares (OLS) regression analyses to examine our hypothesis. Finally, we also perform a range of sensitivity tests to examine the hypothesis and robustness of findings.

Using a sample of the listed US firms from 2003 to 2018, we find that firms with higher audit report lag have a higher cost of equity capital. Our findings are economically significant as one standard deviation increase in audit report lag raises 3.82 basis points of cost of equity capital. Furthermore, our results remain robust to endogeneity concerns and alternative proxies for the cost of equity capital measures. Finally, we confirm that audit report lag increases the firm cost of equity capital through increasing information asymmetry and future financial restatement as a mediating channel.

We contribute to the theoretical discussion about the role of audit report lag and investors' perceptions. Overall, our results suggest that audit report lag affects a firm cost of equity capital.

While the concept of reciprocity has gained traction in qualitative research, especially as the term relates to challenging power dynamics inherent within the research and evaluation process, a gap remains in understanding how a researcher's or elevator's cultural background shapes the way reciprocity is conceptualized and practiced. We explore how Filipino concepts connected to reciprocity (utang na loob, pakikipagkapwa, and alalay) inform the practice of Filipina American researchers and evaluators in academia. We use Sikolohiyang Pilipino and Critical Kapwa in the conceptual framework to guide our study and employ a collaborative autoethnography (CAE) methodology. We present three findings: (1) reciprocity and utang na loob as a nontransactional debt, (2) reciprocity and pakikipagkapwa as seeing the humanity in others, and (3) reciprocity and alalay as carrying the weight together. We discuss this study's implications – regarding theorizing reciprocity, using collaborative autoethnography as methodology, and reclaiming deeper ways of knowing from a critical perspective – for transforming evaluation and research practice. Specifically, through a collaborative autoethnography, we learned the importance of understanding the nuances of language (i.e., Tagalog and other Filipino languages) as a decolonizing approach to arriving at our analysis of pakikipagkapwa through kuwentuhan. Methodologies that attend to a culturally responsive evaluation and research practice – –such as CAE and kuwentuhan– – amplify the voices of silenced communities. Lastly, deeply understanding the cultural context of evaluators' and researchers' experiences and cultural identities as well as studying oneself through a collaborative autoethnography can create practices of reciprocity that have been buried by settler colonialism.

Safety research has focused on drivers, pedestrians and vehicles, with scarce attention given to highway traffic officers (HTOs). This paper develops a robust prediction model which enables highway safety authorities to predict exclusive incidents occurring on the highway such as incursions and environmental hazards, respond effectively to diverse safety risk incident scenarios and aid in timely safety precautions to minimise HTO incidents.

Using data from a highway incident database, a supervised machine learning method that employs three algorithms [namely Support Vector Machine (SVM), Random Forests (RF) and Naïve Bayes (NB)] was applied, and their performances were comparatively analysed. Three data balancing algorithms were also applied to handle the class imbalance challenge. A five-phase sequential method, which includes (1) data collection, (2) data pre-processing, (3) model selection, (4) data balancing and (5) model evaluation, was implemented.

The findings indicate that SVM with a polynomial kernel combined with the Synthetic Minority Over-sampling Technique (SMOTE) algorithm is the best model to predict the various incidents, and the Random Under-sampling (RU) algorithm was the most inefficient in improving model accuracy. Weather/visibility, age range and location were the most significant factors in predicting highway incidents.

This is the first study to develop a prediction model for HTOs and utilise an incident database solely dedicated to HTOs to forecast various incident outcomes in highway operations. The prediction model will provide evidence-based information to safety officers to train HTOs on impending risks predicted by the model thereby equipping workers with resilient shocks such as awareness, anticipation and flexibility.