I'm a skeptic. Thanks to individuals like James Randi I've learned that it's human nature to often side with beliefs rather than evidence. These beliefs can be so strong that people will take great steps in order to try to convince themselves and others of falsehoods. This is why when people quote studies, I ask for sources because sometimes you'll get something that looks like this.
Seems rather daunting doesn't it? A giant wall of citations and text all intending to support a hypothesis. That hypothesis in this case is that meritocracy is significantly hindering a woman's ability to be treated fairly in the workplace. Narrow attention spans might take a large collection of words and figures at face value but remember, I'm a skeptic. I actually took the time to read the blasted thing. I have to say, it doesn't look good for you if you're a sociologist trying to defend your craft.
I came upon this study after an exchange with Liz Kofman. Her nerd cred definitely eclipses mine by any standards. I asked her if 445 people was a sufficient sample size to represent 150 million, which is the number of individuals in the labour force. See to me, that was the first thing that I found suspect. The problem here though occurs when you look at the three cited studies. The first, uses 229 participants, the second 115 and the third used 101. 100-200 people per method representing 150 million, That's not going to cut it. There are also other problems with the participants.
In the first study it explains that the participants revolved around gathering individuals at a University. Because when I think corporate environment, I think University. To their credit, they used MBA students in order to conduct this experiment. Although 2 somehow mysteriously failed to identify their gender, On average they had about 6 years of work experience. This is another problem. How exactly do you expect to have an accurate portrait of 150 million people when your average worker only has 6 years of work experience? Only 80% of those were in a managerial position and had an average of about 3 years leading. I'm being generous here, I'm rounding up. When you're trying to establish a portrait of a work environment, throwing warm bodies who have limited experience in the very field you're trying to accurately depict is careless. And the numbers are similar for the second and third study. Now let's get to the method.
For the first study, participants took the role of a manager and were given a package with the description of the company and if it favoured a meritocratic or non-meritocratic approach. The only problem is that the employee records were all completely fictitious. There was no real life scenario and no one interacted with these people on a day to day basis. You can't just look at a sheet of paper and determine accurately if someone should be receiving a raise. Presuming that the gender of the employee is the only contributing factor shows what little insight sociologists have into these kind of experiments. Psychologists are still finding fascinating results revolving around first impressions in general. Tone, structure, lack of experience, words with negative or positive connotations could all contribute to the metrics that are demonstrated in this paper. In essence, you're being asked to take a leap of faith regarding gender being the one and only factor in this.
All of this seems like a half-assed approach that masquerades as truth by burying it in verbal diarrhoea and citations. When you deal with science you deal with facts. A scientist would actually go to a corporate environment and study the human factor as well as widen the participants to people who have more than 3 years of managerial experience. Psychology coupled with neuroscience would be taken into account in stead of discarded to try to fit an agenda. Ultimately, that's what makes scientists awesome. They have no agenda. Unlike sociologists.