An outside study on gender equity at the University of California Anderson School of Management has found that female faculty members tend to feel bias of various kinds in the hiring and promotion process and in decision making. The bias isn't of the "women can't be promoted" type, but a devaluing of any nonquantitative research, while almost exclusively valuing quantitative research.
The report says women are much more likely than men among business school faculty members to engage in nonquantitative work. Judy D. Olian, dean of the school, attached a letter for the report, calling for a faculty retreat to discuss the findings. She also said she was concerned about the way many female faculty members feel a lack of respect for their work.
Bryan College, in Tennessee, has set new requirements to be met before faculty members can organize faculty meetings, The Times Free Press reported. Now faculty members will need to go through a seven-step process to obtain approval to hold a meeting, and then will be required to have a waiting period of at least a week. Faculty members are noting that the new rules follow a vote of no confidence last year in President Stephen Livesay. College officials said that the new process is designed to give more legitimacy to faculty meetings.
Could blind analysis of data — meaning that an investigator or computer program obscures data values or labels, or both, and that, more generally, as much analysis as possible is done “in the dark” in relation to expected results — help decrease bias towards certain research findings? Robert MacCoun, a professor of law at Stanford University, and Saul Perlmutter, the Franklin W. and Karen Weber Dabby Chair in physics at the University of California at Berkeley, say yes in a new essay in Naturethat’s getting a lot of attention, including on Twitter. The authors say that blind analysis is commonplace in several physics subfields but that it holds lots of potential for the biological, psychological and social sciences, as well — the latter two of which especially have weathered recent data legitimacy scandals.
“Many motivations distort what inferences we draw from data,” say MacCoun and Perlmutter, who is the 2011 Nobel Prize winner in physics. “These include the desire to support one's theory, to refute one's competitors, to be first to report a phenomenon, or simply to avoid publishing 'odd' results. Such biases can be conscious or unconscious. They can occur irrespective of whether choices are motivated by the search for truth, by the good mentor's desire to help their student write a strong Ph.D. thesis, or just by naked self-interest. …Working blind while selecting data and developing and debugging analyses offers an important way to keep scientists from fooling themselves.”
Friends and colleagues of Tomas Lindahl, a professor of microbiology at Sweden’s Linkoping University, rushed to congratulate him on winning the Nobel Prize in chemistry earlier this week, but it was a case of mistaken identity. The real winner was another Tomas Lindahl, also Swedish, who works at the Francis Crick Institute and Clare Hall Laboratory in London. (His prize-winning research centers on how cells repair their DNA.)
The two have been mixed up by fellow scientists for decades, but the confusion reached its peak when friends of the Sweden-based Lindahl deluged him with emails and the local government in Linkoping sent out a congratulatory press release before quickly withdrawing it, the Associated Press reported. The mistaken winner reportedly was in good spirits, telling a local newspaper that “it's sort of fun actually. To be mixed up with a Nobel Prize winner when I'm doing research in chemistry myself.” Referring to December’s Nobel banquet, he added, “But it would be really nice to go to the party.”