Minor: I’d say the travel times in ‘Loxbridge’ are somewhat longer than an hour.
Time from (e.g.) Oxford train station to London train station is an hour, but adding on the travel time from ‘somewhere in Oxford/​London to the train station’ would push this up to ~2 hours. Oxford to Cambridge takes 3-4 hours by public transport.
The general topic looks tricky. I’d guess if you did a kernel density map over the bay, you’d get a (reasonably) even gradient over the 3k square miles. If you did the same over ‘Loxbridge’ you’d get very strong foci over the areas that correspond to London/​Oxford/​Cambridge. I’d also guess you’d get reasonable traffic between subareas in the bay area, but in Loxbridge you’d have some Oxford/​London and Cambridge/​London (a lot of professionals make this sort of commute daily) but very little Oxford/​Cambridge traffic.
What criteria one uses to chunk large connurbations into natural language looks necessarily imprecise. I’d guess if you had the ground truth and ran typical clustering algos on it, you’d probably get a ‘bay area’ cluster though. What might be more satisfying is establishing whether the bay acts like a single community: if instead there is a distinguishable (e.g.) East Bay and South Bay community, where people in one or the other group tend to go to (e.g.) events in one or the other and visit the other occasionally (akin to how an Oxford-EA like me may mostly attend Oxford events but occasionally visit London ones), this would justify splitting it up.
Minor: I’d say the travel times in ‘Loxbridge’ are somewhat longer than an hour.
Time from (e.g.) Oxford train station to London train station is an hour, but adding on the travel time from ‘somewhere in Oxford/​London to the train station’ would push this up to ~2 hours. Oxford to Cambridge takes 3-4 hours by public transport.
The general topic looks tricky. I’d guess if you did a kernel density map over the bay, you’d get a (reasonably) even gradient over the 3k square miles. If you did the same over ‘Loxbridge’ you’d get very strong foci over the areas that correspond to London/​Oxford/​Cambridge. I’d also guess you’d get reasonable traffic between subareas in the bay area, but in Loxbridge you’d have some Oxford/​London and Cambridge/​London (a lot of professionals make this sort of commute daily) but very little Oxford/​Cambridge traffic.
What criteria one uses to chunk large connurbations into natural language looks necessarily imprecise. I’d guess if you had the ground truth and ran typical clustering algos on it, you’d probably get a ‘bay area’ cluster though. What might be more satisfying is establishing whether the bay acts like a single community: if instead there is a distinguishable (e.g.) East Bay and South Bay community, where people in one or the other group tend to go to (e.g.) events in one or the other and visit the other occasionally (akin to how an Oxford-EA like me may mostly attend Oxford events but occasionally visit London ones), this would justify splitting it up.