Hello Catherine Fréchette-Simard

You haven't give enough information on what you want to achieve. That is you objectives, do you have hypothesis and how was it stated? what are your variables and and how was it measured, this will determine the type of statistical tool to be used

There is a technique called 'inverse probability weighting.' By assigning a different weight for male and female participants, your analysis may be (statistically) closer to the perfect world scenario compared to the unweighted samples.

Hello Catherine,

The question is, how representative is a split of 86-14 among elementary school teachers in your target population? If that is typical/representative, then there's nothing special you need to do with respect to the data before carrying on with your analysis.

If that split is _not_ typical or representative, then as D. Eastern Kang Sim 's reply that weighting schemes may be used could apply, especially if your aim was to estimate some parameter for the population of all elementary teachers (disregarding their sex).

If your chief concern is, how to execute comparisons on some attribute by sex, then the one issue that may be pertinent is, how much precision will any estimates you derive for the smaller group have, and is that sample size large enough to give you confidence in those estimates? (Admittedly, 14% of 67 = 9 cases, isn't a large enough N to offer highly precise estimates of any attribute for the male members of your sample.) Unfortunately, there's no post-hoc adjustment that you can make to ameliorate this issue; only a bigger sample size will help (so long as it includes additional males).

Good luck with your work.