I really appreciate the thoughtfulness that went into the reanalysis of the original Harthorne et al. 2018 data on second language acquisition and a potential critical/sensitive period. What struck me (more on this below) was the subtlety of the distinction that van der Slik et al. 2021 were really looking at: I think it’s not really a “critical period” vs. not, but rather a sensitive period where some language ability is equal before a certain point vs. not. In particular, both the discontinuous (=sensitive period) and continuous (=no sensitive period) approaches assume a dropoff at some point, and that dropoff is steeper at some points than others (hence, the S-shaped curve). So the fact that there is in fact a dropoff isn’t really in dispute. Instead, the question is whether before that dropoff point, are abilities equal (and in fact, equal to native = sensitive period) or not? To me, this is certainly interesting, but the big picture remains that there’s a steeper dropoff after some point that’s predictable, and it’s useful to know when that point is.
Specific thoughts:
(1) A bit more on the discontinuous vs. continuous models, and sensitive periods vs. not: I totally sympathize with the idea that a continuous sigmoidal function is the more parsimonious explanation for the available data, especially given the plausibility of external factors (i.e., non-biological factors like schooling) for the non-immersion learners. So, turning back to the idea of a critical/sensitive period, we still get a big dropoff in rate of learning, and if the slope is steep enough at the initial onset of the S-curve, it probably looks pretty stark. Is the big difference between that and a canonical sensitive period simply that the time before the dropoff isn’t all the same? That is, for a canonical sensitive period, all ages before the cutoff are the same. In contrast, for the continuous sigmoidal curve, all ages before the point of accelerated dropoff are mostly the same, but there may in fact be small differences the older you are. If that’s the takeaway, then great — we just have to be more nuanced in how we define what happens before the “cutoff” point. But the fact that a younger brain is better (broadly speaking) is true in either case.
(2) L1 vs. L2 sensitive periods: It’s a good point that these may in fact be different (missing the L1 cutoff seems more catastrophic). This difference seems to call into question how much we can infer about a critical/sensitive period for L1 acquisition on the basis of L2 acquisition. Later results from this paper suggest qualitative similarities in early immersion (<10 years old), bilinguals, and monolinguals (L1) vs. later immersion, in terms of whether a continuous model with sigmoidal dropoff (early immersion) vs. a discontinuous model with constant rate followed by sigmoidal dropoff (later immersion) is the best fit. So maybe we can extrapolate from L2 to L1, provided we look at the right set of L2 learners (i.e., early immersion learners). And certainly we can learn useful things about L2 critical/sensitive periods.
(3) AIC score interpretation: I think I need more of a primer on this, as I was pretty confused on how to interpret these scores. I had thought that a negative score closer to 0 is better because the measure is based on log likelihood, and closer to 0 means a “smaller” negative, which is a higher probability. Various googling suggests absolute lowest score is better, but I don’t understand how you get a negative number in the first place if you’re subtracting the ln of the log likelihood. That is, you’re subtracting a negative number (because likelihoods are small probabilities often much less than 1), which is equivalent to adding a positive number. So, I would have expected these scores to be positive numbers.
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