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This is just not right in this day and age!

Originally shared by Jon Hiller

This is just not right in this day and age!


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  1. I disagree with this study and what it stands for. If there are less women in a given field, they will not have the same opportunities to succeed simply because they make up less of the pot. How do you win a raffle? Buy more raffle tickets. So there are less women in these fields which therefore decreases their chances of being a team lead and thereby decreasing their chances of applying for research grants and there is something wrong with this? No. If women don’t enjoy the field, they’re not going to go into it. There is no need to try and start some affirmative action type thing to give women a better chance if succeeding than a man which will eventually turn into everyone but a white man benefits. It’s bullcrap in my book. If you don’t earn it, you don’t deserve it.


  2. Rhett Rhemann  If your odds of winning aren’t the same as someone else with the same number of tickets, then the raffle is rigged. Your rant does not reflect what the article actually says – they found that among those who had become independent academic researchers, men got more resources than women.


  3. No what I’m saying is that if I want to win, I buy more tickets than others. So let’s say DARPA wants some research done in one area and there are 10 people who write the research proposals identifying the way they want to go about solving the problem for the government. However, 9 out of those 10 research proposals are headed up by men and 1 a woman. The odds of a woman winning is far fewer and thereby women getting less representation in total monies given to research.

    This research does not show a comparison of the percentage women in X field and their comparable percentage of research monies available. Secondly, if after reading all proposals, it is decided by a committee generally on who gets the money by what is identified as the best solution to a problem or the best way to find that solution. I could care less who has the idea as long as what I’m trying to do gets done. And I’m sure many of the entities doling out this money feel the same way. There doesn’t need to be any BS regulation guaranteeing women a certain percentage of the monies available. Because THEN you would be missing out on the best scientific research and THAT would be a travesty!


  4. From the actual paper itself:

    “Since historically female faculty members have received less institutional support and have had less access to research resources [17]–[22], these considerations prompt a question with significant policy implications: Could the differences in resource requirements lead to distinct gender-specific publication patterns across disciplines?”

    the answer was yes.

    This paper (and the article about the paper) never suggests that funding rates should be equalized to gender. The research makes within-field comparisons; women researchers who are in the field have already selected it and are succeeding (i.e. publishing) despite the biases they face. To assume they didn’t earn their success despite institutional bias is as insulting to them as assuming that their white male colleagues earned their success because they are white and male (even when it is true.)


  5. Racism and sexism is a double edged sword. If a woman fails it’s primarily because the playing field is tilted against her? If a Caucasian Male is successful its only because of race and gender? To be honest this study only SUGGESTS it does not prove anything. While it doesn’t specifically mention affirmative action, that is typically where this type of argument ends up.


  6. When a woman fails, it may simply be that a woman has failed. When women are failing generally compared to men, this is an indication that there might be a problem. When women’s failure appears to be linked to the amount of resources needed to succeed, this is a stronger indication that there is a  problem.

    Observational studies can only ever suggest, they can’t prove. I would hope most scientists know that. However, the obvious explanation for women failing more frequently than men is that discrimination is at work.

    Direct experiments, such as the now-famous job-application study published earlier this year, have proven that there is a problem with discrimination against women in the tested circumstances.

    Putting the tested fact of known discrimination together with the observational fact that women are more likely to fail than men leads to the obvious conclusion that discrimination is behind the higher failure rate. That’s science.


  7. I do not understand how or why discrimination would happen in this situation. What benefit is it to try and exclude a group of people? Science is not a field where being perceived as attractive matters like in advertising etc. Verifiable results matter so it shouldn’t matter if a woman, man or a transgendered person were to come up with those results. Could it be that they are not securing a very limited amount of research funds because they have less experience, less successful studies, or a poor pitch on their idea for that matter?


  8. Robert Minchin When you say there is an obvious conclusion… without proof that is not science… That is what is known as “cum hoc ergo propter hoc.” It is a logical fallacy and anything but scientific. I’m not sure if you ever heard the phrase “correlation does not imply causation” in elementary Science class but this it what that means.


  9. E.E. Chenoweth I am fully aware that “correlation does not imply causation”. Observation + theoretical explanation + agreement of theory with previously proven results does, however, strongly imply causation.

    Let’s go through the facts:

    1) We have an observation that women are (as a group) succeeding less than men in science.

    2) We have experiments that prove that women are discriminated against in science.

    3) Discrimination would explain why women are less successful than men in science.

    Once you have a theory, supported by experiment, that explains an observation, the logical conclusion is that that theory is indeed the explanation for the observation. That’s the way observational science works.

    An obvious example where people cry “correlation does not imply causation”, ignoring the fact of the theoretical framework that explains why the correlation exists, is in climate change. Here global temperatures correlate with CO2 levels, along with explanations of why rising CO2 levels should lead to rising temperatures.

    When you have a theory saying two variables should be linked and you test for the correlation and find it, then the logical conclusion is that they are indeed linked. There is always the possibility that the theory is incomplete and there is a third variable present, and in observational science one always has to be very aware of selection effects, but until there is some evidence for a third variable or an uncorrected selection effect then these should not be introduced into the hypothesis.


  10. Rhett Rhemann There is no need for there to be any conscious discrimination, so no need for there to be any benefit that would give a motive for discrimination.

    In the ‘job application’ experiment, the discrimination can be was caused subconsciously by referees having a lower assessment of the abilities of a candidate with a female name. Interestingly, both men and women shared this bias, so it’s not a case of trying to keep women out.


  11. Strongly imply perhaps but that it is certainly not a “Obvious conclusion.” Using your line of reasoning one could argue that

    1. the number of atheists and agnostics has recently grown.

    2. We have recently experienced a significant increase in natural and man made disasters.

    3. Our abandonment of Christ would explain why there has been a increase of disasters.

    While yes it would explain it, that doesn’t mean it is the explanation…


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