DATASET A — SEMI-STRUCTURED INTERVIEW

I: Can you start by telling me a bit about your background — what you did professionally, what you're doing now?

X: Thirty-two years in thermal engineering. Mostly industrial — power plants, large-scale heat exchange systems. Retired four years ago, which I thought would mean more golf and less reading, but it turned out to be the opposite. I have more time to actually look into things properly now. Which is both a blessing and, my wife would say, a curse.

I: What kinds of things have you been looking into?

X: All sorts, really. Energy policy, quite a lot. Some economics. And the climate debate, I suppose, more than anything. Not because I set out to — it sort of pulled me in. I started reading about energy transition planning and realised I had serious questions about some of the assumptions underneath it. Engineering questions, not political ones. At least that's how it started.

I: What do you mean by engineering questions?

X: Well — when you model a complex thermal system, you have to be very honest about your uncertainty ranges. You have cascading variables, feedback interactions, and the further out you project, the wider your error bars get. That's just the nature of it. What I found when I started reading the underlying science — not the summaries, the actual papers — was that the uncertainty ranges are much wider than what gets communicated publicly. The headlines say things like "temperatures will rise by 2.7 degrees by 2100." But if you go to the actual model outputs, there are scenarios ranging from under one degree to over five. That's not a prediction. That's a distribution. And policy is being built on the midpoint as if it were a fact.

I: Do you think the scientists themselves are aware of that gap?

X: Some of them, absolutely. And I want to be careful here because I don't think most of them are — I don't want to use the word dishonest, because I don't think that's right. I think there are structural pressures that operate almost invisibly. When you apply for funding, you write in terms of urgency and impact. When you communicate findings, institutions simplify. By the time it reaches a journalist, three layers of interpretation have already happened. I've seen the same thing in engineering procurement — the original technical spec becomes unrecognisable by the time it reaches the client brief. It's not malice, it's institutional processing.

I: Has your thinking on this changed over time?

X: It's become more — nuanced, I'd say. When I first started reading critically, I was probably more strident. I thought: this is straightforwardly wrong, why can't people see it? Now I think it's more complicated than that. There are things that concern me genuinely. The pace of glacier retreat in some regions is faster than the models predicted, which is — that's worth taking seriously. I'm not dismissing that. What I'm pushing back on is the leap from observation to catastrophism. Those are two different things and they get run together constantly.

I: When you talk to people about this — friends, family — how do those conversations go?

X: Depends on the person. My son is a secondary school teacher and he gets quite upset, actually. Not angry, more — worried about me, I think. Like I've gone down a rabbit hole. Which I understand. I've looked at myself from the outside and I know how it can appear. The problem is that the moment you express any scepticism, even very specific technical scepticism, you get put in a category. And once you're in that category, nothing you say is evaluated on its merits anymore. It becomes about who you are, not what the argument is.

I: What category do you mean?

X: Denier. Which is a word I find — I find it does a lot of work. It moves the conversation from epistemology to morality. It's not "your argument is wrong because of X" — it's "you are a bad person for asking the question." And I think that's a problem for science as a culture, regardless of who's right on the object-level question. My son would say I'm being defensive. Maybe he's right. I genuinely don't know anymore.

I: Is there anything about the mainstream position that you think is correct, or that you've updated toward?

X: The urban heat island effect is real and I think it's underappreciated — cities are genuinely warming faster than surrounding areas and some of that is being attributed to global trends when it's actually local infrastructure. That's a legitimate finding. The general direction of warming I don't dispute. The question is magnitude, timescale, and attribution — and on those questions I think we're less certain than the public discourse suggests. But — and this is something I've had to sit with — I'm also aware that I'm not a climate scientist. My engineering background gives me certain tools, but it also has limits. I try to hold that.

I: What would change your mind?

X: That's a good question and I've thought about it. I think if the models consistently outperformed their uncertainty ranges for twenty or thirty years — if the predictions proved accurate at the specific level — that would be significant. What I see at the moment is a lot of post-hoc adjustment and retrospective reframing. "We didn't predict this event specifically but it's consistent with our models" — well, with wide enough uncertainty bands, almost anything is consistent with the models. I want to see genuine predictive specificity. That's what separates science from narrative.