The first paper
suggests that there
might be an issue based on mentions in the Vaccine Adverse Event Reporting System (VAERS) data.
The second takes this more seriously and looks to see if there is an issue by examing a wider set of data and studies, more or less concluding that sufficient evidence is lacking so far but perhaps further trials are worth pursuing.
This isn't a "womens voices are not heard" thing it's more of a "if there's anything there it is barely peaking above the noise" thing.
It's worth reading the conclusions of the second paper, keeping in mind how to read such papers, this:
The primary limitation of this systematic review was a lack of data from randomized clinical trials investigating the effect of COVID-19 vaccines on the menstrual cycle.
Most surveys included in our analysis were performed in the US, UK, and Norway, which are countries belonging to the ‘Global North’ in terms of health access and utilization by women, due to which, their findings cannot be extrapolated to the rest of the world, particularly countries with low healthcare access and resources such as Pakistan and India, where smartphone apps used for collecting and tracking menstrual data by users may not be as prevalent as they are in the countries where the studies were conducted.
With a lack of peer-reviewed evidence from South Asia, which includes population centers such as Pakistan and India, it cannot be stated with certainty whether COVID-19 vaccination would have similar low reported menstrual abnormalities.
highlights that overall, with app based menstrual tracking, there are low reported menstrual abnormalities (largely being that for a few women, cycles run a day late).
Data science wise the issues are; How often does this happen (sans COVID or vaccines), How much does stress play a factor (the stress of being concerned about the vaccine (which is a real thing)).
The conclusions are that "more study is needed to say anything definitive, throw money our way", which is a reasonable request and one common to many such papers - bear in mind there is no obvious smoking gun here so no immediate need to panic.
As a note about VAERS - consider routine haircuts, now scare the pants off of everybody about haircuts and open a Haircut Adverse Event Reporting System database for anybody to add theor stories to.
The reports of eveybody who died, injured themselves, got the runs, had cramps, etc. within a week after their haircut will mostly be real .. the data science challenge is to pick out how many of these events are related to the haircut and how many are statistically "as expected".