In but not of the education system, moving past “as I say, not as I do”
Have you ever felt like the outsider looking in? Do you hear the words of change fall on the deaf ears around but shrug and do what is needed for your grade anyway? Maybe I do. Parker Palmer’s “A New Professional” struck a chord when he brought up the need for change from within the systems of society brought on by its members that are “in but not of” their systems. It turns out that looking in may not be a bad perspective after all.
We don’t often talk about moral conflicts in our work but I have had an interesting past with such dilemmas. I was working as a small engine mechanic after getting hired out of my class by a fellow student. That turned out to be the better of two bosses in the small business that hired me. The other boss was the salesman. Time and again he would pit my technical proficiency against a customer to support an upsetting agenda that made me look like his stooge. I hated it overtime and began to pick up on when it would likely happen next. My expectation allowed me to step up my professionalism and be better prepared to be an advocate on the side of the customer rather than a witness in the middle of a cross examination. If it weren’t for the other boss, my classmate, I would have just had to go along with the badgering every time. This is also where I found out people do not trust mechanics because of situations like this.
Where do moral conflicts like this arise in research? The answer is everyday. Lets look at how we report our findings. If our experiment yields significant differences in treatments after our analysis then we can use this to explain all kinds of ideas on how what we measured could happen in the real world. If our data are not significantly different then we give one line saying so but rarely do we poke holes in our study design in our publications. This creates a tense edge in research. On one hand our experimental design should help us to gain insight from our results. On the other hand, we commonly turn a blind eye to negative data in favor of more publishable results. Add on the kind of overwhelmed feeling of emerging researchers that is similar to that of the resident from our case study, and we have a recipe for moral compromise that can compound itself. A different example would be research efforts that essentially set out to prove one preconceived conclusion or another in hopes of more funding. Without such funding, PI’s, Labs, and whole programs can fail. Without legitimate scientific enquiry… entire ecosystems can fail. What kind of efforts can be made now to enable the new professionals to be agents of change? Is there enough protection in play that we can call a timeout and stop the game clock when we know that research is suffering because of ethical compromises? Or will we be forced to only blow the whistle after the fact and watch our bridges of networking smolder in ruin as a result?
Nice post, James. I completely agree with you about negative results in research. Sometimes they don’t even get published, which is really frustrating, as you may end up doing a study that was already done and failed, but didn’t know because it wasn’t published. Sometimes knowing that something doesn’t work is just as informative as knowing if it does work. Sometimes, I think this is a Journal decision rather than the scientist’s. How we can get this changed, I do not know. Thanks for sharing.
I’ve run into Palmer’s issue a few times – I agree with your negative results argument as well. If I go into a social science study looking for correlations between two things, and I go in with the presumption that correlation exists, and yet find that it does not, that may be just as significant and deserving of attention/publication. No matter how objective publication or conference reviewers pretend or claim to be, they are judging our work as influenced by their own knowledge, experiences, areas of interest, influences, biases. Inescapable, frustrating.
Hi, James, thanks for pointing out the publication bias in scientific research. Most of the research indicates a significant relation, but there is thousand others unpublished indicating a non-significant relation. But because such result is hard to publish, we end up only see the significant ones. Besides this significant issue, researchers even turned to create the illusion of importance. For example, when the result is small, researchers turned to multiply the number by 100 or 1000, to make the figure appeared in table seems bigger. I don’t know about other major, such tricks is used a lot in my field. As an audience, I have to pay special attention to the footnote to find out the real impact of the result. Right now, in my own research, I am request to do the same. Honestly, I am not sure whether it is for good or bad…
I like your post because I’ve had to think about my research not producing significant contributions before. I think bias in research is here to stay without a comprehensive shake up of our educational system. In my department, I have to publish at least four papers to have my diploma and I’ve been doing experiments for the past two years not knowing whether my results will be publishable or not. I mentioned my fears to my PI and she said, ‘if we end up with nothing then we know what not to do’! Not many students are as lucky as I am though, and at the end of the day many try to bend their experiments to give meaningful results.
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