Most triathlons are probably won by men and global exploratory voyages were first accomplished by men...
Not saying your wrong I'm asking what I'm missing?
This assumption seems strange. How do you think polynesians spread without both men and women?
If you're referring to the european age of exploration, they weren't rowing much at that point, rendering sex mostly irrelevant.
> The boat was paddled by a mixed team consisting of four men (paddlers) and one woman (steerer), without replacement by other paddlers on the way. The inclusion of both men and women is essential because our focus is ancient migration, not men’s adventure. An unstable, round-bottomed dugout required skilled paddlers to control it on the open sea. Furthermore, because this type of boat does not travel in a straight direction but instead snakes its way, the skill of the steerer is crucial for optimizing its performance. Considering these factors, we invited professional and semi-professional sea kayakers as the paddlers and steerer.
And ... this wasn't a race? Perhaps 5 women could have gotten there faster, but speed wasn't the primary goal.
I don't know anything about paddle sports specifically, but I have seen a discussion about sex differences in performance in other endurance sports, and one important distinction is that women as a group can have average pace times that are faster than men as a group, even when most of the outright winners are men.
https://www.theguardian.com/lifeandstyle/2024/dec/30/the-lon...
> While men still hold the edge, women’s rapid progress suggests a future where they may outperform men in extreme endurance events.
https://www.bbc.co.uk/sounds/play/p0hg2764 (9 minute episode).
Why is that important? Unless the runners are conscripted into the race, it's not telling you anything about women or men.
Your second link notes this explicitly:
>> What the data actually means is that after 195 miles the average pace of all women competing is better than the average pace of all the men competing. Why is this the case? Math and demographics (not physiology and toughness). In any athletic user group, the early adopters are also higher performers. Take the people who pioneered skateboarding, or adventure racing as an example. Those early adopters were good at the sport they were trying to push the boundaries. As a sport becomes more and more popular, the number of non-elites grows much faster than the number of elites. Therefore, even though the best times and performances improve (by way of a course or world record) the average times get worse. Ultrarunning is no different.
It's not saying something about _all_ men or women. If you did try to work with a random sample wouldn't you mainly find that almost all people of both sexes can't run an ultra marathon?
But in making comparative statements even about people who choose to participate in such races, I think a critical distinction made in that article is that there's a difference between "E(Pace_W) < E(Pace_M)" vs "Min(TotalTime_W) <? Min(TotalTime_M)".
The earlier anecdote was making a statement about who won a canoe race and using it as evidence of a group level difference ... But race winners are the extreme end of the distribution and are poor information about the overall behavior.
Compare http://www.lagriffedulion.f2s.com/dogrun.htm :
>> How, for example, do we determine a distribution of running ability within an entire population? Can we find a representative sample of tribesmen, provide each with motivation and training, and finally measure their times for some event? Not very likely. There is, however, a way out. In Aggressiveness, Criminality and Sex Drive by Race, Gender and Ethnicity, we introduced the method of thresholds. It applies nicely to this problem. The proportion of each tribe meeting or exceeding some threshold of performance is the only input it requires. When all is said and done, the precise definition of "ability" will still be fuzzy, a characteristic of the method of thresholds. That aside, we will have established running ability distributions in tribes relative to one another.
>> Some of the data we need are available from chroniclers of track and field. All-time-best lists are particularly useful. For a given event, such a list might contain 100, 500, 1500 or any number of the best times ever run. The slowest time on a list serves as the threshold of performance required by the method of thresholds.
> If you did try to work with a random sample wouldn't you mainly find that almost all people of both sexes can't run an ultra marathon?
No, you'd find that people managed to go different distances before failing. You would have to be intentionally avoiding the result you expected to find to binarize your outcome data like that. The data you're appealing to right now isn't binarized.
> But in making comparative statements even about people who choose to participate in such races, I think a critical distinction made in that article is that there's a difference between "E(Pace_W) < E(Pace_M)" vs "Min(TotalTime_W) <? Min(TotalTime_M)".
The article itself provides the explanation: there are very, very few women running. What lesson do you feel we should draw? To me it looks like the lesson is "men are a lot more interested in distance running than women are".
> Dr. Kaifu noted that the islands could be spied from the top of one of Taiwan’s coastal mountains, indicating intentional travel
Image?
http://english.ryukyushimpo.jp/wp-content/uploads/2011/09/Yo...
raincom•5h ago