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Bank celebrates its discrimination against male employees

The second part:working fewer hours does not negate the first part: paying women less than men for the same work.

Paying women less for the same work DOES contribute to them working fewer hours. So does limiting their opportunities for career advancement and development. Most partners make rational choices about which person should cut back on working to deal with (whatever family issue). Usually, it is the person who earns less will work less because a loss of their income has a smaller impact on the overall family budget.

In America we have found it reported as "same work" when it was less hours and less years of experience. I see no reason to assume the Australian data is any more honest.

Fewer.

Less is for un-countable quantities. Hours and years are countable.

Less water; but fewer glasses of water. Less sand; but fewer grains of sand. Less money; but fewer coins.

It's not that difficult.

/grammarnazi
 

Note that the message I am replying to has a bad URL unless the mods have fixed it. I have corrected it in this quote.

This report looks like more of the disparate result means discrimination crap. While there isn't enough here to prove there's no discrimination going on we can clearly see the pattern.

Teenagers: .3% discrepancy. That's about 1% of the total effect they are reporting, the rest of it appears to be due to mommy-track.

When 99% of something is bad data I see no reason to figure the remaining 1% isn't just less obvious bad data.
 

Note that the message I am replying to has a bad URL unless the mods have fixed it. I have corrected it in this quote.

This report looks like more of the disparate result means discrimination crap. While there isn't enough here to prove there's no discrimination going on we can clearly see the pattern.

Teenagers: .3% discrepancy. That's about 1% of the total effect they are reporting, the rest of it appears to be due to mommy-track.

When 99% of something is bad data I see no reason to figure the remaining 1% isn't just less obvious bad data.

You also see no reason to back up your claims with links.

Frankly, you have no idea whether the data is good or bad. You may find the analysis lacking in qualities that justify your position but you do not know enough about the data itself to determine whether it is 'good' or 'bad.'
 
Note that the message I am replying to has a bad URL unless the mods have fixed it. I have corrected it in this quote.

This report looks like more of the disparate result means discrimination crap. While there isn't enough here to prove there's no discrimination going on we can clearly see the pattern.

Teenagers: .3% discrepancy. That's about 1% of the total effect they are reporting, the rest of it appears to be due to mommy-track.

When 99% of something is bad data I see no reason to figure the remaining 1% isn't just less obvious bad data.

You also see no reason to back up your claims with links.

Frankly, you have no idea whether the data is good or bad. You may find the analysis lacking in qualities that justify your position but you do not know enough about the data itself to determine whether it is 'good' or 'bad.'

I'm pointing out problems with the link that was provided, what links should I be providing?!?!?!
 
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