[1] https://www.aljazeera.com/investigations/thelobby/
[2] https://en.wikipedia.org/wiki/Israel_lobby_in_the_United_Kin...
251 karma · joined September 18, 2017
[1] https://www.aljazeera.com/investigations/thelobby/
[2] https://en.wikipedia.org/wiki/Israel_lobby_in_the_United_Kin...
https://media-cdn.tripadvisor.com/media/photo-s/06/b7/48/74/...
Some of them also have variable temperature.
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.
and by the way, there is studies that indicate that woman are better at empathy ( a sign of emotional intelligence): https://www.ncbi.nlm.nih.gov/pubmed/19476221
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."
more about that incident: http://www.cbc.ca/news/canada/kitchener-waterloo/wilfrid-lau...
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.
when Damore speaks out against politics affecting hiring and promotion, he is wrong
I'm fascinated how one can reconcile both beliefs
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.
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.
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?
"Abstract
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."
b - higher capacity of empathy might be in part to biological: "Testosterone may reduce empathy by reducing brain connectivity" http://www.psypost.org/2016/03/testosterone-may-reduce-empat...
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
"The trial found assigning a male name to a candidate made them 3.2 per cent less likely to get a job interview."
"Adding a woman's name to a CV made the candidate 2.9 per cent more likely to get a foot in the door."
source: http://www.abc.net.au/news/2017-06-30/bilnd-recruitment-tria...
link: http://www.sciencedirect.com/science/article/pii/S0160289616...
Abstract 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.
Highlights • Sex differences in brain morphology and general intelligence were examined.
• MRI and test data of the Human connectome project were used (N = 896)
• Males and females differed in total brain size, gray, and white matter volumes
• The male-female difference in general intelligence, g, was d = 0.25.
• Sex differences in brain morphology mediated the sex difference in g.
I'm pretty sure this is textbook slippery slope fallacy
there is also this study: "Testosterone may reduce empathy by reducing brain connectivity" http://www.psypost.org/2016/03/testosterone-may-reduce-empat...
"Half of the women were given an orally administered dose of testosterone sufficient to increase the levels of the hormone in their blood by a factor of ten, while the other half received a placebo. The women who were given testosterone subsequently took significantly longer to identify the emotions depicted images of eyes, and made significantly more errors while doing so."
No body is arguing against the right of women to become engineers. It's just stating that the assumption that "hidden bias" exists if a field is not at 50/50 is untrue. and by the way, I'm yet to find any proof for that. if you find a study that indicates no discirimination leads to 50/50 in all fields or at least in engineering I will be happy to read it.