The “sorry for being me” attitude

Apologies are hard. Really good apologies can seem almost impossible. I suspect many of us who are pandemic-confined with other humans have had a lot of opportunities to think about apologies. Or at the very least, see them go wrong. I am thankful for Brené Brown‘s new podcast Unlocking Us and last week she gave us a long, thoughtful conversation with Harriet Lerner (I’m Sorry: How To Apologize & Why It Matters). I highly recommend it for any human who intends to interact with other humans, and who might make a mistake now and then.

With the words of the podcast still fresh in my head, I was handed a “sorry for being me” apology. It’s a flavor of apology I’m sure most of us have given at one time or another – probably feeling like it was noble of us to admit our serious inherent faults. It can be hard to see the implicit messages it sends to the person it’s addressed to, or the unproductive stories it reinforces. Despite presumably good intentions, it is packaged in a way that can’t really be opened by the other person. It doesn’t acknowledge the recipient’s hurt or feelings, and what options does it leave? Comfort the apologizer? Tell the apologizer they are forgiven for being them? It gets complicated fast. So much is contained in that one phrase.

I hone in on one of the implicit messages that echoes most loudly in my ears: “I am sorry, but there’s nothing to be done about it.” The “things just are as they are” message sends me into a strong, and probably overreactive, negative response mode. It zaps my hope.

Why am I writing about it here, on my blog meant for talking about science and statistical inference? Because… I was recently hit with the realization that I had heard and felt this message repeatedly over years working as a collaborating statistician. I just didn’t see the connection – even though it seems obvious now. It’s so easy to compartmentalize our work lives from our personal lives — and not see how feelings in one might be magnified because of feelings in the other. We need awareness first, before we can use such information in a positive way — and becoming aware is hard.

I am certainly no expert in this area of apologies and analyzing feelings; but I do have the human thing going for me. I suppose my hope in writing this is that people may understand and relate to the personal apology story — and then by seeing the connection will understand the one related to my experiences as a statistician, which then might lead to increased awareness of problems underlying use of statistical methods in science. On the surface it may sound like quite a reach, but at the moment it sure doesn’t feel like it.

Just to be clear – I am well aware that I fall into the trap I’m describing in many areas of my life. But, there’s no rule against writing about things we also suffer from and are trying to understand. We’re all human — in our personal lives and in our professional lives. Yes, even the scientists.

Same underlying message

I’ve never had an explicit “I’m sorry for being me” from a researcher or client (thank goodness). But, I’ve had plenty of comments that I now see come from a very similar place and share a basic underlying message — they still convey the “sorry for being me” attitude, just dressed up in a more professional context. These typical arrive as some sort of apology after the person decides not to adopt my, or another statistician’s, professional advice to change their intended approach to design or analysis or interpretation.

The message takes me straight to frustrations around dogmatic practices based on statistical methods that continue in many fields – despite plenty of cautions and warnings. This post isn’t about specific practices, but about the attitude, or mindset, that reinforces and encourages behaviors despite well documented problems or professional advice from well-meaning statisticians.

Here are a few examples of paraphrased comments I have received repeatedly over the years in response to suggesting a different approach that is more justifiable from a statistical perspective:

• “I agree with you, but I think I need to go with this approach to get my grant [or get my paper published].”
• “I see what you’re saying, but I have to go with what’s accepted in my field.”
• “I think the approach you’re suggesting makes sense, but it will never fly with reviewers. It’s just not how we do things.”
• “For my career, I need to stick with what people are used to, even if it seems wrong to you.”
• “I’m sorry to disagree with you, but I’m going to keep doing what I was originally taught.”

On the surface, these may not sound a lot like “I’m sorry for being me,” but I hear the same underlying message. The message can be further translated into something like “I’m sorry for how I’m going to do things, but I’m not open to change,” or “I’m not proud of my choice, but I can’t change it, even if I wanted to. It’s how I have to operate to survive.”

Just as in my personal life, the underlying message zaps my hope and respect. In the language now common for many elementary and middle school students — it reflects a fixed mindset (as opposed to a growth mindset) [based on work by psychologist Carol Dweck]. Willingness for change doesn’t bubble up from a belief that things are inherently fixed and unchangeable. There is no need to find the effort or put up with the pain of change if it won’t be worth it in the end. The message reflects a mindset that justifies maintaining the status quo – even when we’re well aware of its problems or at least see others trying to get us to hear about the problems. Our brains are so good at ignoring warning signs just to be able to stay the course we’re on.

In doing science, it’s easier to continue to operate as you’re used to operating, and probably as your advisors, and their advisors, also operated. It may have already led you to a successful career, or it may look like the only way to end up with success. The dangers of changing course, of trying something different, and putting in the additional effort and fight to justify it, are real. They are real because the dogmatic approaches get so embedded in the system of doing business and in the surrounding culture. The culture is generally unforgiving when it comes to change. Those with the most power in the system generally got that power using the approaches. Recognizing the problems and allowing others to change requires (or at least encourages) some pretty deep and uncomfortable reflection on previous work.

There are so many forces acting against change. It is easy to get overwhelmed or simply choose to ignore the problems. Maybe seeing the connections to struggles we tend to place only in our personal life compartment is a way to glimpse things from different perspective and gain a different type of awareness? It may be worth a try, as it’s hard to see how it could hurt.

Statistician’s perspective

I want to go into a little more detail related to use of statistical inference in scientific practice. Let’s take the statement:  “I’m sorry, but I have to continue using statistics as I was originally taught.” What am I to do with this as a statistician? It’s quite likely they were “originally taught” by someone with little formal background in statistical inference, but we don’t know what we don’t know. Does the person want me to forgive them for their decision, even if it goes against my own professional opinion? To me, that feels like condoning practices I disagree with – not something I can do and still preserve my integrity. While I might not be able to forgive, I can understand and sympathize with the pressures and forces against change. I do get it. I understand how the system operates. But, that doesn’t mean I have to accept and feel okay with the decision to choose status quo over greater rigor.

I also can’t ignore how the collection of many, many of those decisions may work against progress in science. I think statisticians get a relatively unique perspective through our work with many different individuals across disciplines. We get a birds eye view of the accumulation of these decisions that isn’t obvious from the ground within the very specific niche of a single person’s work. We see the heaping mound of debris resulting from decisions made by a whole culture reinforcing itself to produce more of the same.

Statements like those mentioned above, send the message that it is more important to cling to “the way things are” than to be open to looking at why things are as they are and how they can be improved (because things can always be improved). For you scientists, what is the evidence that change will be that bad? Do you know you won’t get your grant? Do you know you won’t get your paper published? Or, are you proceeding as if that’s the case, without decent evidence or justification?

What do we do about it?

I don’t have the secret to pushing our brains outside their default way of operating, but I do know humans manage to do it all the time. Something happens — some awareness is gained, some level of motivation is reached — that pushes a person to reach outside their comfort zone or suddenly see the harm in their usual way of thinking and operating. We expect this in the context of tending to meaningful relationships with other people, so why not set expectations for something similar in the practice of science?

Finding motivation has to first come from a willingness to search for greater understanding and an openness to awareness. Maybe it can be captured with a renewed or deeper sense of curiosity about why and how we tend to do the things we do. We’re human — in our relationships and in our work. There is no easy magical fix. But, it is clear that staying confined within a fixed mindset is not helpful. It continues the pain, contributes to systemic problems in systems, and makes widespread positive change seem nearly impossible.

The “I’m sorry for being me” attitude pops up all areas of our lives. Even when delivered with the best intentions, it’s worth realizing that it’s likely serving as poor justification for an excuse to not change. It does not move us forward in doing science or living our lives — as if there is really much of a difference between the two most of the time.

I have a lot of hope for those growing up with awareness of the power of mindsets, and even the language to talk about it. Maybe they will be able to better shed the fixedness that hurts relationships and hinders scientific rigor and progress. We’re all stuck somewhere and not doing the world any favors by it. Why does it seem easier to make our mistakes by sticking with the status quo than risk making our mistakes through change? The latter artificially feels like we’re more accountable, whereas the first leaves us somehow absolved because we didn’t really “do” anything. We can so easily trick ourselves into believing that acting in the way we usually do (not changing) is not acting. But, both involve making a decision about how to act. Deciding to do nothing is making a decision to act in a certain way, as much as we would like it not to be.