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tokens: can lead to an almost infinite amount of parameter space to consider (Bate, Clarke McCaughrean 1998 ; Parker Meyer 2012 ; Jaffa, Whitworth Lomax 2017 ). We therefore restrict our comparison to either box fractals as defined by Goodwin Whitworth ( 2004 ); Cartwright Whitworth ( 2004 ) or centrally concentrated clusters with different radial density profiles (Cartwright Whitworth 2004 ; Cartwright 2009 ). 3.2 The mass segregation ratio, Λ<sub>MSR</sub> MSTs are often used to quantify the relative spatial distribution of the most massive stars in a star-forming region (Allison et al. 2009 ; Parker Goodwin 2015 ), but the method can be applied to any distribution of points with assigned masses (or indeed any other scalar property), and we will apply it to the dense cores in Orion B. For the data set we use in this paper, the ‘mass segregation ratio’ (Λ MSR ) is defined as the ratio between the average MST pathlength of 10 randomly chosen cores in a star-forming region and that of the 10 most massive cores: As described in Allison et al. ( 2009 ) and Parker et al. ( 2011a ), we define the lower (upper) uncertainty as the MST length, which lies 1/6 (5/6) of the way through an ordered list of all the random lengths (corresponding to a 66 per cent deviation from the median value, 〈 l average 〉). This determination prevents a single outlying object from heavily influencing the uncertainty, which could be an issue if using the Gaussian dispersion as the uncertainty estimator. If Λ MSR > 1, then the most massive cores are more spatially concentrated than the average cores, and we designate this as significant if the lower error bar also exceeds unity (see also Alfaro González 2016 ; González Alfaro 2017 ). Parker Goodwin ( 2015 ) show that Λ MSR can sometimes be too sensitive in that it sometimes finds that random fluctuations in low-number distributions lead to mass segregation according to our definition. Therefore, if Λ MSR is calculated to be less than 2, then we also do not consider this to be a significant deviation from a random distribution. 3.3 The local surface density ratio, Σ<sub>LDR</sub> We calculate the relative local surface density of the most massive cores compared to lower mass cores using the local surface density ratio, Σ LDR (Maschberger Clarke 2011 ; Küpper et al. 2011 ; Parker et al. 2014 ). We first determine the local surface density around each core, Σ, as where r N is the distance to the N th nearest neighbour, N (Casertano Hut 1985 ). We adopt N = 10 throughout this work. We divide the median Σ for the 10 most massive cores, , by the median value for all the cores to define a ‘local density ratio’, Σ LDR (Parker et al. 2014 ): If Σ LDR > 1, then the most massive cores are in areas of higher local surface density than the average core, the significance of which is quantified by a Kolmogorov–Smirnov (KS) test on the cumulative distribution of the cores, ranked by their local surface densities Σ. We reject the hypothesis that