Men suffer from higher risk (non-consensual alimony, scams, and catfishing (etc) are all too damn common) but lower harm (these are all nasty, but manageable if you look after yourself and follow basic safety).
Women suffer from lower risk (violent men are not as common as the media makes out) but much higher harm (sorry but dead or trapped in physical abuse trumps the lot, not much you can do to protect against these).
Psychology says the women are going to be a lot more cautious (we fear big losses with low odds more than small losses with high odds).
Gents, just take it on the nose that cautious ladies are playing a smart numbers game. Ladies, make sure to make it up to the gents later on in the relationship (we love chocolates too, especially the "sorry I suspected you of murder" kind).
Honestly, I don't think any of those would be deal breakers today. Europe is now tougher on external migration (much more in line with the UK), the pound is no longer much more powerful than the euro, and the privacy legislation of both is equally concerning so no issues there beyond the normal.
We'd certainly prefer the stronger EU ruling against "pay or ok" under GDPR, and a lot of UK citizens would appreciate the greater mobility.
I would like to suggest that the EU also demand that Nigel Farage be formally charged for misleading the public, in a European court.
So, I in no way support what the USA has just done (essentially forced vassilisation of another nation to appease oil magnates), but god damn that comment was funny.
In some fields (e.g. mathematics) old papers hold up well. However, in fields like psychology where the landscape shifts a lot that's probably a good shout!
Honestly, I always poke the stats no matter how good the journal. The best way to read any article is as a skeptic (the onus is on the writer to prove their point), and any small irregularity is something to be queried.
No matter how good the journal, it's only as good as the reviewers, and reviewers are humans too. Odds are a paper in nature is all above board, but I'm somewhat of a pedant when it comes to checking test conditions.
Paper itself above. Need a deeper reading with my notes but on the surface the stats are so-so. They check normality, but don't confirm linearity (use of pmcc will not be valid without - there are also a few other conditions to check for hypothesis testing with PMCC if memory serves), use of a continuous test (PMCC, ANOVA, unpaired t's) for discrete (likert) data is also little controversial, but generally condoned.
As for the conclusion, not a psych phd so I'll assume they know their stuff!
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