Utilizing spinal cord injury stratification during classification for allocation of para surfing sport classes.

OBJECTIVES: The purpose of this study was to determine which stratification (anatomical versus functional) forms a better construct for classification of para surfers with spinal cord injury; to assess the groupings of these para surfers; and to evaluate the strength of association between manual muscle testing and surfing performance. DESIGN: Cross-sectional. METHODS: Archived data from classification records including demographics, spinal cord injury levels, trunk strength, and limb strength were compared to judged wave scores and competition rankings. RESULTS: Participants (n = 70, male n = 56; female n = 14) met inclusion criteria and were classified into Para Surfing Kneeling (n = 9); Sit (n = 11); Prone 1 (n = 25); and Prone 2 (n = 25) sport classes. Reliability statistics showed that functional grouping (Cronbach's α = 0.759) is better grouped with strength testing and rankings compared to anatomical grouping (Cronbach's α = 0.721). Under exploratory factor analysis with 2 fixed components, based on the factor loadings (rank and strength) functional stratification (0.978) is better aligned compared to anatomical stratification (0.785) for grouping of surfers. Further, the association and impact of strength with functional spinal cord level stratification were confirmed using regression analysis (chi-square of 74.06 with p-value <.0001). CONCLUSIONS: Trunk and limb strengths have been shown to influence wave riding performance in surfers with spinal cord injury. Surfers with spinal cord injury can equitably be classified into one of the four para surfing sport classes. The use of functional stratification of spinal cord injury with trunk and limb strengths should be considered as an integral component in para surfing athlete sport classification.

The Human Side of Artificial Intelligence.

Artificial moral agents raise complex ethical questions both in terms of the potential decisions they may make as well as the inputs that create their cognitive architecture. There are multiple differences between human and artificial cognition which create potential barriers for artificial moral agency, at least as understood anthropocentrically and it is unclear that artificial moral agents should emulate human cognition and decision-making. It is conceptually possible for artificial moral agency to emerge that reflects alternative ethical methodologies without creating ontological challenges or existential crises for human moral agents.