A Participatory Research Approach to Understanding the Experiences of Black, Asian and Minority Ethnic (BAME) Autistic Young People

Autism is no longer considered a rare condition and is thought to affect one in 160 children worldwide (World Health Organisation, 2019), irrespective of culture and ethnic or racial groups (Tincani et al., 2009). While the growth of autism research has been exponential, the majority of existing research exploring the experiences of autistic young people is based on data from largely White ethnic backgrounds (Marks et al., 2000). There is a growing recognition that ‘race’ is more salient for BAME individuals therefore there is a need to study autism in BAME communities (Dovidio et al., 2009). The purpose of this study was to explore the views of BAME autistic young people using a participatory approach. The study aimed to (1) empower a BAME autistic young person as a co-researcher, and (2) explore the lived experiences of four BAME autistic young people. Using Aldridge’s (2017) participation model, this research was planned and delivered alongside a co-researcher. Collaboratively the researcher and co-researcher identified a research topic that was of importance to the co-researcher’s lived experience. Following on from this, research questions and a schedule for a semi-structured interview were developed in collaboration. Interviews were then carried out with four BAME autistic young people with the aim of eliciting their experiences of being autistic and BAME. The researcher and co-researcher analysed the data using Interpretative Phenomenological Analysis. This produced themes at an individual level as well as across-cases. Four superordinate themes emerged at group level based on participants’ experiences. Participants highlighted how The BAME communities’ constructions of autism often resulted in negative perceptions of their diagnosis due to lack of understanding and knowledge of autism. Participants also highlighted Self and Autism and the impact of their diagnosis on their self-concept. Relationships with peers emerged as a key area within the research as friends were found to be both a barrier and an asset to the participants’ sense of belonging. The final theme, The importance of positive relationships at the different levels highlighted friends, family and LSAs as support systems that have positively contributed to the experiences of BAME autistic young people. While there are similarities between the experiences of BAME autistic young people and findings from the literature review, the current study highlights that autistic young people from BAME communities have experiences that are unique to them as result of their cultural and racial identity. The research findings have implication for educational psychologists and school staff supporting BAME autistic young people including providing support that goes beyond autism and that encapsulates the cultural and racial identities of BAME autistic young people. The researcher and co-researcher hope that this study will contribute towards social justice by shifting the nexus of power as well as enabling participation and giving a voice to a marginalised group who have largely been neglected by autism research. Additionally, by describing and documenting how autistic young people can be involved in research successfully, the researcher hopes that it will contribute to increasing the participation of autistic young people in research, bridging the gap between theory and practice

Behavioral Learning of Aircraft Landing Sequencing Using a Society of Probabilistic Finite State Machines

Air Traffic Control (ATC) is a complex safety critical environment. A tower controller would be making many decisions in real-time to sequence aircraft. While some optimization tools exist to help the controller in some airports, even in these situations, the real sequence of the aircraft adopted by the controller is significantly different from the one proposed by the optimization algorithm. This is due to the very dynamic nature of the environment. The objective of this paper is to test the hypothesis that one can learn from the sequence adopted by the controller some strategies that can act as heuristics in decision support tools for aircraft sequencing. This aim is tested in this paper by attempting to learn sequences generated from a well-known sequencing method that is being used in the real world. The approach relies on a genetic algorithm (GA) to learn these sequences using a society Probabilistic Finite-state Machines (PFSMs). Each PFSM learns a different sub-space; thus, decomposing the learning problem into a group of agents that need to work together to learn the overall problem. Three sequence metrics (Levenshtein, Hamming and Position distances) are compared as the fitness functions in GA. As the results suggest, it is possible to learn the behavior of the algorithm/heuristic that generated the original sequence from very limited information

How large is the spreading width of a superdeformed band?

Recent models of the decay out of superdeformed bands can broadly be divided into two categories. One approach is based on the similarity between the tunneling process involved in the decay and that involved in the fusion of heavy ions, and builds on the formalism of nuclear reaction theory. The other arises from an analogy between the superdeformed decay and transport between coupled quantum dots. These models suggest conflicting values for the spreading width of the decaying superdeformed states. In this paper, the decay of superdeformed bands in the five even-even nuclei in which the SD excitation energies have been determined experimentally is considered in the framework of both approaches, and the significance of the difference in the resulting spreading widths is considered. The results of the two models are also compared to tunneling widths estimated from previous barrier height predictions and a parabolic approximation to the barrier shape