Search results

Based on authentic leadership (AL) theory and research on lesbian, gay, bisexual and transgender (LGBT) workplace experiences, this study proposes that AL explains variance beyond transformational leadership (TL) in attitudinal outcomes for LGBT managers compared to non-LGBT managers. It is further predicted that core self-evaluations (CSEs) bound relationships between AL, LGBT status and outcomes.

A time-lagged survey of 193 LGBT and 218 non-LGBT (i.e. heterosexual and cisgender) managers was conducted. The first survey assessed respondents' evaluations of their leadership behavior and CSEs whereas the second survey, conducted one month later, assessed role engagement and career satisfaction.

Regression and moderation analyses revealed support for the hypotheses. AL seems especially relevant for LGBT leaders, particularly at low levels of CSEs.

Leadership development programmes emphasizing AL could be particularly beneficial for LGBT managers, especially those low in CSEs. Harnessing a leader’s sense of identity could help those who have been marginalized.

The current study proposes, explains and demonstrates that relationships between AL and leader outcomes will likely be different between managers with and without stigmatized identities, in this case those who are (not) LGBT.

Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.

This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.

The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.

LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.

LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.

To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.

Recent research has proposed a specific female phenotype within autism spectrum disorder (ASD). It suggests females exhibit differences in social communication styles with higher levels of camouflaging and compensatory strategies, as well as variance in restrictive repetitive behaviours (RRBs); however, many existing studies have been based on either small, disproportionate or child and adolescent samples, leaving questions about the specific phenotype. This study aims to explore the sex difference and phenotype in a clinic sample of individuals diagnosed with autism.

A service evaluation of sex/ gender differences on 150 historical ASD assessment reports (75 males, 75 females) using a 103-item questionnaire developed from a quantitative review of existing literature was undertaken.

Females camouflaged more significantly than males in five different areas (thinking how to act next, preparing conversation in advance, making lists of prompts/social responses, wearing a mask/acting, less monotone voice); however, these were not maintained in post-analysis correction.

This study points the evidence towards a different phenotype of Autism that is more common in women than men rather than a unique female phenotype.

Moving away from the stories of financial disaster we encountered in Chapter 2, Chapter 3 examines what it means for fans when their club is suddenly awash with more financial muscle than some nation-states due to the generosity of a wealthy benefactor who is seemingly more interested in sporting glory than in financial gain. This chapter engages with the notion of the football club as a billionaire’s plaything. Roman Abramovich’s acquisition of Chelsea in 2003 saw the West London club embark on an eye-watering spending spree and a sustained period of on-field successes, one that was unknown in the club’s history to that point. As a result, we take Chelsea during the Abramovich era as a starting point for considering how this model of ownership affects the relationship between fans and the connection that they have with their club. The evident success that financial muscle can bring shows owners what a happy fanbase is capable of, what they are capable of doing, and what they are capable of ignoring. The success of the financially doped teams of the 2000s created a precedent for winning over a fanbase with a successful football club, but nevertheless sat awkwardly with the normative ideals of how a football club should exist in the world and relate to its supporters.

Flood preparedness and response from the perspective of community engagement mechanisms have been studied in scholarly articles. However, the differences in flood mitigation may expose social and behavioural challenges to learn from. This study aimed to demonstrate how text mining can be applied in prioritising existing contexts in community-based and government flood mitigation and management strategies.

This investigation mined the semantics researchers ascribed to flood disasters and community responses from 2001 to 2022 peer-reviewed publications. Text mining was used to derive frequently used terms from over 15 publications in the Scopus database and Google Scholar search engine after an initial output of 268 peer-reviewed publications. The text-mining process applied the topic modelling analyses on the 15 publications using the R studio application.

Topic modelling applied through text mining clustered four (4) themes. The themes that emerged from the topic modelling process were building adaptation to flooding, climate change and resilient communities, urban infrastructure and community preparedness and research output for flood risk and community response. The themes were supported with geographical flood risk and community mitigation contexts from the USA, India and Nigeria to provide a broader perspective.

This study exposed the deficiency of “communication, teamwork, responsibility and lessons” as focal themes of flood disaster management and response research. The divergence in flood mitigation in developing nations as compared with developed nations can be bridged through improved government policies, technologies and community engagement.