Maybe I'm not understanding what the original user was testing here, but it seems like the finding is that different inputs result in a statistically significant difference in output length? Seems pretty unsurprising?
This feels like the original author is over anthropomorphizing LLMs, and expecting them to interpret prompts the way humans would, but it seems obvious that changing the prompt results in a slightly different context window, which results in a slightly different response distribution? Similarly, if you changed whether the bit about time of year was at the beginning or the end of the prompt, I would expect a statistically different distribution of response lengths.