In this youtube video about bootstrap resampling, the creator states that when the number of bootstrap processes is small, the distribution of the parameter being estimated can no longer be thought to have a normal distribution (see from the 8:50 mark).
Since the parameter's distribution is not normal, the standard deviation can't be obtained via the standard formula:
The author thus states that one needs to use the CDF to calculate where the 68% confidence interval values are and obtain from there an estimation of the standard deviation.
My question is: where can I get a source for this workaround for obtaining the standard deviation when the number of times the bootstrap process is repeated is small?
I'm interested in this because I'm using bootstrap with replacement to estimate the uncertainty of a parameter and I can't possibly repeat it thousands of times (not even dozens actually) because it would be impossibly time consuming.