> They're all right, of course: you can't simply infer bias from statistical underrepresentation Technically speaking, if something is statistically under- or

> They're all right, of course: you can't simply infer bias from statistical underrepresentation Technically speaking, if something is statistically under- or over-represented, then there is a source of bias ("an extraneous latent influence on, unrecognized conflated variable in, or selectivity in a sample which influences its distribution and so renders it unable to reflect the desired population parameters"). Whether that bias reflects overt or covert discrimination on the part of those in academia is another question, of course.