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UDORA is the institutional repository of research produced by staff at the University of Derby, and an archive of our completed doctoral theses.
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Communities in DSpace
Celebrity Science Culture: Young people's inspiration or entertainment?This thesis explores the influence of celebrity scientists on the uptake of science by young people, post-GCSE; the phenomenon is based upon media assertions that young people were continuing with science as a result of the increased media presence of scientists: the ‘Brian Cox effect’. Research design is set within a constructivist-interpretivist paradigm and case study framework, employing a narrative, story-telling approach to data collection and presentation. Narratives require ‘actors’, and as such the ‘lead actors’ in this research are: the conceptual framework; a narrative approach to data presentation; and the sociological perspectives of science capital and habitus. Together they guide development of the ‘bricolaged’ methodology, underpin the innovative script-writing approach to data presentation, which are used to illuminate the phenomenon of celebrity science culture. Data collection includes two participant groups: eighteen science students (‘A’ Level, undergraduate, and postgraduate), and five celebrity scientists (Sir David Attenborough, Baroness Susan Greenfield, Professor Steve Jones, Professor Mark Miodownik MBE, and Roma Agrawal MBE). Interviews explore science memories and influences, as well as perceptions of the role of celebrity science and scientists. The rationale and significance of this research lies within two strands: knowledge-based and methodological. It offers new knowledge to the field of celebrity science influence, with the potential to inform science education policy makers, and the methodological bricolage of conceptual framework development and creative narrative practices offer new dimensions to narrative research. An intrinsic, long-standing ‘passion’ for science was found to be the most influential factor. Advanced subject knowledge of teachers and lecturers, alongside opportunities to work within authentic and meaningful contexts, were highlighted as important in raising aspirations, and building science capital. Celebrity scientists were perceived as having the potential to influence young people, with authentic, inspiring contexts, presented in an entertaining format potentially optimising this influence. Science per se, rather than the ‘scientist’ him/herself, was more influential, contrasting with the traditional view of celebrity influence. The perceptions of science students are reflected in the findings from celebrity scientists. Engagement with children and young people was considered part of their role, not only to raise aspirations, but also to increasingly embed science culturally; their own passion for science the impetus for involvement. Partnership with other stakeholders was recognised as key, especially teachers and parents. ‘Personification’ was also recognised as important, acknowledging the responsibility that brings for their work to be truthful and credible. The thesis concludes with recommendations for future policy and practice, offering a theoretical framework and bespoke checklist, derived from the data, to support dialogue between stakeholders. This includes exploring use of the narratives as a tool to engage pupils with their own science journeys, with the intention of enhancing their science capital. The concept of “message to a name” is introduced, in contrast to the “name to a message” phenomenon of celebrity influence.
Determining the factors which positively affect the intra-family chief executive officer succession of UK small and medium-sized companiesA change in Chief Executive Officer (CEO) is a critical event in the life of any business. For family businesses the stakes can be higher, as failure may lead to the dual issues of business collapse and significant family harm. Intra-family business CEO succession is the transfer of leadership to a different member of the family and is a strategic direction family businesses take, even if sacrificing performance across generations to secure long-term control benefits. The research aims to determine the factors which positively affect the intra-family CEO succession of UK Small and Medium companies as gaps were identified in the research of businesses that had been through a succession across a range of areas. This research uses a deductive research design to test the existing theory and combines theoretical conceptualisations developed within the literature review with the aim of providing new theory and insight into the issues. Quantitative data was collected from primary and secondary sources from 230 UK Small and Medium Enterprises (SMEs) which identified as family businesses and had been through a succession. The questionnaires were completed by company directors and the questions consisted of measures relating to the succession event, processes and outcomes. The data collected was tested empirically using process tracing and regression analysis. Findings show that disagreements relating to the initial planning made an intra-family CEO more likely as did a discussion of passing control to a professional manager. It was found that a family business with higher proportions of senior management, higher levels of generational involvement and higher levels of experience led to an increasingly likely succession to an intra-family CEO. This finding took an additional step in the understanding of elements of the Family Influence on Power, Experience and Culture model. The thesis also found, empirically, that satisfaction with the succession process increased with the presence of advisors and that there was a positive relationship between director stability and profit and a negative relationship with management stability and profit. The findings indicated that a degree of externality in the succession contributes to a positive intra-family CEO succession outcome.
The effect of accounting for biarticularity in hip flexor and hip extensor joint torque representationsSubject-specific torque-driven models have ignored biarticular effects at the hip. The aim of this study was to establish the contribution of monoarticular hip flexors and hip extensors to total hip flexor and total hip extensor joint torques for an individual and to investigate whether torque-driven simulation models should consider incorporating biarticular effects at the hip joint. Maximum voluntary isometric and isovelocity hip flexion and hip extension joint torques were measured for a single participant together with surface electromyography. Single-joint and two-joint representations were fitted to the collected torque data and used to determine the maximum voluntary joint torque capacity. When comparing two-joint and single-joint representations, the single-joint representation had the capacity to produce larger maximum voluntary hip flexion torque (larger by around 9% of maximum torque) and smaller maximum voluntary hip extension torque (smaller by around 33% of maximum torque) with the knee extended. Considering the range of kinematics found for jumping movements, the single-joint hip flexors had the capacity to produce around 10% additional torque, while the single joint hip extensors had about 70% of the capacity of the two-joint representation. Two-joint representations may overcome an over-simplification of single-joint representations by accounting for biarticular effects, while building on the strength of determining subject-specific parameters from measurements on the participant.
The effect of visual focus on spatio-temporal and kinematic parameters of treadmill runningThe characteristics of a treadmill and the environment where it is based could influence the user’s gaze and have an effect on their running kinematics and lower limb impacts. The aim of this study was to identify the effect of visual focus on spatio-temporal parameters and lower limb kinematics during treadmill running. Twenty six experienced runners ran at 3.33 m s−1 on a treadmill under two visual conditions, either looking ahead at a wall or looking down at the treadmill visual display. Spatio-temporal parameters, impact accelerations of the head and tibia, and knee and ankle kinematics were measured for the final 15 s of a 90 s bout of running under each condition. At the end of the test, participants reported their preference for the visual conditions assessed. Participants’ stride angle, flight time, knee flexion during the flight phase, and ankle eversion during contact time were increased when runners directed visual focus toward the wall compared to the treadmill display (p < 0.05). Whilst head acceleration was also increased in the wall condition (p < 0.05), the other acceleration parameters were unaffected (p > 0.05). However, the effect size of all biomechanical alterations was small. The Treadmill condition was the preferred condition by the participants (p < 0.001; ESw = 1.0). The results of the current study indicate that runners had a greater mass centre vertical displacement when they ran looking ahead, probably with the aim of compensating for reduced visual feedback, which resulted in larger head accelerations. Greater knee flexion during the flight phase and ankle eversion during the contact time were suggested as compensatory mechanisms for lower limb impacts.
Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analysesAssessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors’ knowledge, this is the first study to optimise the development of a machine learning algorithm.