Knowing, acknowledging and accounting for one's own biases is just good science.
You wouldn't use a thermometer that was always 10C too high to measure and reports temperatures, without pointing out that the thermometer has a 10C bias, would you? Why would you oppose introspection about oneself and one's own potential biases in knowledge production?
Maybe I am missing the part where is says there is a particular ideological project beyond better science?
You act like bias isn't actually a problem in science, but when I think back to the number of studies recruiting on campus at my Highly Selective Undergrad Institution (TM), and cross reference that with the student population, it's really easy to understand the claims that science is WEIRD[1].
You're describing a very legitimate sampling error problem. I'm describing forced ideological conformity. Both exist in academia today.
If, in the spirit of the proposed "bias declaiming section", a social scientist made a point of saying that they're systematically biased against conservative and white/rural viewpoints, how do you think that would go over? Pat on the back for introspection?
Why don’t you think so? "Our own academic perspective limits us e.g. in our survey design and language, making it harder for us to connect with our respondents" is something I heard and learned over and over and over again.
Please don't add disclaimers like "I'm a liberal", it should not matter what your political opinions are. Shoot the message, not the messenger after all?
When all the biases one is asked to acknowledge and account for are biases against one specific political movement and its symbols, this is an isolated demand for rigour (https://slatestarcodex.com/2014/08/14/beware-isolated-demand...) and not necessarily good for science. To adapt your thermometer metaphor, if there were two types of thermometer in circulation, one 10C too high and one 10C too low, would demanding that people constantly remind each other, and where possible correct, for thermometers that output a temperature that is too high (and perhaps labelling any reference to the low-balling ones as dangerous misinformation by people who have a vested interest in high readings) actually improve the quality of scientific output? On the meta-analysis level, the opposite might happen, if the biases used to cancel out on average and now one of them is left standing unopposed.
1. That's not what is happening here. There's no intention to use this to make science better.
2. Even if it was, some people are assumed to be "biased" based on silly things like the color of their skin or what gender they are. The bias-checking process is biased.
You wouldn't use a thermometer that was always 10C too high to measure and reports temperatures, without pointing out that the thermometer has a 10C bias, would you? Why would you oppose introspection about oneself and one's own potential biases in knowledge production?