I participated as a subject in a research study at Stanford involving race and stereotype threat in the early 2000s. The details are hazy, but the final readout was the distance I put my chair to a group of chairs that students of a particular racial group were supposed to sit. Evidently I put them in a position that was contrary to the effect the researcher was seeking. She intensely asked me a ton of questions about my background and eventually tossed my data point for having lived in a racially diverse area growing up. This wasn't a pre-inclusion criteria, but a possible act of scientific fraud. Huge bummer since there are honest people in every profession, and I imagine a lot of them didn't succeed the way that the fraudsters thrived.
I've had a similar experience in a long running survey. When I gave the "wrong" answers, the interviewer asked a bunch of questions and eventually told me to skip certain questions.
I had an experience like that where an education researcher was attempting to prove that a certain style of teaching was more effective. It involved a test measuring how much students remembered from a conventionally-taught course taken the year before; the researchers hoped to show that these scores were low, and therefore that conventional teaching methods were ineffective. I and another classmate aced the test so the researcher accused us of cheating, even though there was no incentive to cheat (the test wasn't used for any grade, so if anything, the incentive was to save time by leaving answers blank). We denied cheating, explained that the course instruction had been very memorable, and proved it by correctly answering followup questions on the spot. Ultimately our high-scoring test results were discarded as outliers and the hypothesis was successfully validated.
It sounds more like another day in vegas for the psychology field of that era. This was not an exception, and often researchers were not even aware they were doing something wrong. Even nowadays psychology researchers are clueless as to what really p-hacking and bad statistical practices mean. And because they consider themselves honest researchers, while these practices are obviously dishonest, they do not consider themselves actually doing anything like that - but somebody else may! it is always somebody else. Now it is not as bad as that period, and there is more awareness about the most blunt violations of statistical rigour, but the actual understanding is still low for the median researcher so many grey-to-black zones exist still.
Incentives determine outcomes. Most grad students are grad students because they are responding to incentives. It's competitive so cheating is ubiquituous. Reduce competition in academia and problems would lessen.
Usually psychology studies are conducted by field workers or assistants. I don't think the person you interacted with was the actual author of the study.
Comments
I participated as a subject in a research study at Stanford involving race and stereotype threat in the early 2000s. The details are hazy, but the final readout was the distance I put my chair to a group of chairs that students of a particular racial group were supposed to sit. Evidently I put them in a position that was contrary to the effect the researcher was seeking. She intensely asked me a ton of questions about my background and eventually tossed my data point for having lived in a racially diverse area growing up. This wasn't a pre-inclusion criteria, but a possible act of scientific fraud. Huge bummer since there are honest people in every profession, and I imagine a lot of them didn't succeed the way that the fraudsters thrived.
I've had a similar experience in a long running survey. When I gave the "wrong" answers, the interviewer asked a bunch of questions and eventually told me to skip certain questions.
I had an experience like that where an education researcher was attempting to prove that a certain style of teaching was more effective. It involved a test measuring how much students remembered from a conventionally-taught course taken the year before; the researchers hoped to show that these scores were low, and therefore that conventional teaching methods were ineffective. I and another classmate aced the test so the researcher accused us of cheating, even though there was no incentive to cheat (the test wasn't used for any grade, so if anything, the incentive was to save time by leaving answers blank). We denied cheating, explained that the course instruction had been very memorable, and proved it by correctly answering followup questions on the spot. Ultimately our high-scoring test results were discarded as outliers and the hypothesis was successfully validated.
It sounds more like another day in vegas for the psychology field of that era. This was not an exception, and often researchers were not even aware they were doing something wrong. Even nowadays psychology researchers are clueless as to what really p-hacking and bad statistical practices mean. And because they consider themselves honest researchers, while these practices are obviously dishonest, they do not consider themselves actually doing anything like that - but somebody else may! it is always somebody else. Now it is not as bad as that period, and there is more awareness about the most blunt violations of statistical rigour, but the actual understanding is still low for the median researcher so many grey-to-black zones exist still.
Unfortunately true. In other words: "often researchers were too stupid to ever have been let into university as freshmen".
Incentives determine outcomes. Most grad students are grad students because they are responding to incentives. It's competitive so cheating is ubiquituous. Reduce competition in academia and problems would lessen.
Sounds like this study (published in 2008):
"The space between us: stereotype threat and distance in interracial contexts"
It mentions being run at Stanford, and was pretty popular (Claude Steele discussed in his book Whistling Vivaldi).
https://psycnet.apa.org/doiLanding?doi=10.1037%2F0022-3514.9...
Usually psychology studies are conducted by field workers or assistants. I don't think the person you interacted with was the actual author of the study.
Grad students and post-docs are often running studies.
How would you know if they excluded your data?