I'm not that involved in wikipedia, but I do recall his name. It came up during a discussion on reddit about aljazeera documentary "the lobby"[1]. He was accused of actively censoring any mention of the incident from the "Israel lobby in the United Kingdom"[2] wikipedia page.
I've been Tunisia where they had a hose like this in the hotel, as you can see it has variable pressure, and even without setting it to the maximum it's sufficient.
I feel like this is bullshit. It's very clear that the photo is inspired by the cat, not the photo of the cat. There are many different details between the two images to the point that it is a totally different photo of the cat ( see ear position,left eye ..)
do you believe that the authors falsified their findings?
and also the idea is not to justify sexism, but to provide another possible reason for why a trend seems to perssist after apparent bias is eliminated. This is in response to the idea that oppression is somehow responsible for 100% of the gender-ratio gap.
I don't claim that biological reasons are the only reasons but I stress that they do in fact exist and that a violent response to suggesting that they might exist is not normal.
To use this studies to be sexist, is the wrong idea ,as the memo's author explained, because there is overlap between the populations and while on average one is better (in that respective function) then the other, that does not preclude that someone from the second group is better then someone one the first.
In other words, the result on hiring based on merit alone is better then both:
- hiring only males
- hiring based on prescribed gender quotas.
do you have any proof of this claims? and if they were true how and in what you way would this matter if we were to compare one individual to one individual instead of treating people like herds.
I meant that the amount of points is not a major outlier, and if it is the interviewer should have written an argument why it's different from the old cases if the other members find the argument convincing it should be fine.
>some Applicant Tracking Systems like Greenhouse
that's exaclty the type of feedback I wanted thank you very much
> Claim E
if we are innocent, why wouldn't this be in our favour.
"Women on average show a higher interest in people and men in things
○ We can make software engineering more people-oriented with pair programming
and more collaboration. Unfortunately, there may be limits to how
people-oriented certain roles at Google can be and we shouldn't deceive
ourselves or students into thinking otherwise (some of our programs to get
female students into coding might be doing this).
● Women on average are more cooperative
○ Allow those exhibiting cooperative behavior to thrive. Recent updates to Perf may
be doing this to an extent, but maybe there's more we can do.
○ This doesn't mean that we should remove all competitiveness from Google.
Competitiveness and self reliance can be valuable traits and we shouldn't
necessarily disadvantage those that have them, like what's been done in
education."
mordern feminsts professors hold fringe ideas about human nature that are far too extreme to the point that it contradicts current scientific findings while also being caught using what can only be called authoritarian methods. A group that holds strong ideas, refuses to change them and uses authoritarian policies to shutdown debate is, in my opinion, bigoted. One of the most recent examples in memory is the Laurier university Case you check it out here: https://globalnews.ca/video/3867811/extended-excerpts-from-s...
this is the same university that gave away a pay raise based on gender: http://nationalpost.com/opinion/christie-blatchford-pay-rais... That ended up in some female professors that were hired in the same time as some male professors having a higher pay after the raise even though they were paid the same before it.
Step 2: peer-review
The highest candidate is selected, interviewers exchange notes and are asked to:
* check and discuss if their colleagues reasons’ are valid and reasonable (for example "the hello" reason might be seen as too petty by some, and will be discarded)
check if the point values are reasonable
(Checking old similar data to flag outliers is a possibility)
check if some of the reasons presented by other colleagues apply to their own candidates. For example, if the "hello" reason was not discarded and your candidate didn't say hello you must apply it to him too.
*Interviewers are asked to bring more focus on the current best candidate's reasons.
If after a peer-review round, the best candidate changes, another round is made or shorten the list and re-interview.
If it does not change, the best candidate is offered the position.
Claim D: this helps smooth out harsh or lenient interviewer bias.
Claim E: this process if well documented should be a valid and easy defense against allegations.
Data Analysis on hiring decisions becomes way more interesting. I'm sure there are tons of trends you can seek out.
Claim F: this allows an earlier detection of discrimination. For example if you find that an interviewer or a committee always removes points from a certain group for a subjective reason more than others in the company. It might be an early warning sign that a problem need be addressed.
Claim G: this allows for a higher quality debate on controversial issues like sexism and racism in hiring.
Machine learning can be used to give suggestions to interviewers about the amount of points to give for reasons. (They should be suggestions no decisions to avoid the pitfalls the lost nuance that classic machine based decision might suffer from)
Example: a fairly easy one is that after a high enough number of universities and GPAs is received one can aggregate the point values into scores that take into account the difference of grading and quality between universities. This might help decide if GPA x in Y is better or worse than GPA z in C, a very hard question to answer fairly if we didn't have the data.
I think this method offers a more traceable, open and perhaps fair way of hiring without suffering from the lack of nuance that traditional automatic hiring suffers from.
Problems:
- Money: this process might require more man power.
- Tooling: to be efficient this process requires tooling and automation
I would be happy to hear your ideas, improvements and experiences with similar systems. I think the idea of this system is very similar to that of a neural network.
so you believe that physical difference between sexes in size of the brain, is not due to sex? what would you say this is caused by?
I would like to point out that saying this changes are due to evolution not sex is unvalid because then nothing will be due to sex, not saying that you think that but just getting it out of the way.
The study examined female and male brains, found that males on average had a higher general intelligence score and a higher standard deviation. The study also found that male brains had on average higher surface area and size even if you control for body size. The study found that brain size in both genders on average leads to a higher g.
I don't understand how your criticism "indirect correlational evidence" applies to this study, could you maybe elaborate on how you would improve this study?
Utilizing MRI and cognitive tests data from the Human Connectome project (N = 900), sex differences in general intelligence (g) and molar brain characteristics were examined. Total brain volume, cortical surface area, and white and gray matter correlated 0.1–0.3 with g for both sexes, whereas cortical thickness and gray/white matter ratio showed less consistent associations with g. Males displayed higher scores on most of the brain characteristics, even after correcting for body size, and also scored approximately one fourth of a standard deviation higher on g. Mediation analyses and the Method of Correlated Vectors both indicated that the sex difference in g is mediated by general brain characteristics. Selecting a subsample of males and females who were matched on g further suggest that larger brains, on average, lead to higher g, whereas similar levels of g do not necessarily imply equal brain sizes."
c- people who have a higher level of empathy might be interrested in fields which need a higher level of empathy, or seek to join fields that directly interact with people [ I don't have a source for this one. It seems logical to me, but it is unproven. if you know a study that proves or disproves it. Please link it]
d - higher levels of women interessted in other fields leads to less women interrested in tech
[1] https://www.aljazeera.com/investigations/thelobby/
[2] https://en.wikipedia.org/wiki/Israel_lobby_in_the_United_Kin...