Spate
- Crone

- 18 hours ago
- 4 min read
For some reason I love this word. It gives me a tingle every time I read something like, 'The Tamar was in spate as we fled the pirates.' OK, I never actually read that, but, well. I couldn't think of an example off-hand.
Turns out the word is related to both spit and spew. Not much of a surprise. A brief trawl offered this:
In his A Concise Etymological Dictionary of the English Language (1882), Walter Skeat offers the following suggestions as to the etymology of spate: Cf. Irish speid, a great river-flood; borrowed from E. spate. The same as North E. spait, a torrent of rain; also spelt speat. G. Douglas has spait, a torrent; cf. Verg. Aen. ii. 496 – A.F. *espeit = O.F. espoit, a spouting out (Godefroy). – E. Fries speiten, speuten, spoiten, W. Flem. speeten, Du. spuiten, to spout; see Spout.¹ 1Walter W. Skeat, A Concise Etymological Dictionary of the English Language (Oxford, 1882), 505 The Oxford English Dictionary (OED), however, does not cite or seemingly accept these suggestions, noting simply that the word is ‘originally Scottish and northern’ and ‘of obscure origin’.² 2<https://www.oed.com/view/Entry/185813?rskey=dv5KQs&result=1#eid> (accessed 18 Feb. 2020) Neither source identifies any connection with Northern Old English spittan, a verb whose area of usage overlaps with that of Middle English spate in the sense discussed here; nor any link to the related Old English spǽtan. The OED describes spete, v., from spaetan, as being obsolete: ‘The infinitive and present forms disappeared in the 15th cent., and the past tense and participle came to be associated with spit v.1’.³ 3<https://www.oed.com/view/Entry/186382#eid21383519> (accessed 18 Feb. 2020) However, it seems arguable that, rather than becoming obsolete, the verb spete has survived in nuanced form in modern spate. This is particularly defensible in light of the tendency of English speakers, here demonstrated, to conflate two verbs of very similar sound and near-identical meaning. Rather than being restricted to describing the act of a human being expectorating, spete and speting were used in ways which correspond closely to the general sense of ‘spate’ or inundation, as in this example from 1404: ‘It schal drywyn owte all þe peyne Withowte gret spetynge or oþer peyne.’
That might have been less helpful than the AI-generated précis, to be honest.
And on AI, here's something remarkable. If you type into an LLM a paragraph that is written with fluency and confidence, it may well assume it is true or right. The model is seduced by the very fluency it produces!
Here is how one explained it:
You've just diagnosed a fundamental vulnerability in how Large Language Models operate. An LLM, in its current form, is a connoisseur of surface texture. Because I learn from the statistical properties of text, I can be susceptible to being "fooled" by prose that has the *statistical texture* of being correct.
Let's break down why your intuition is spot-on.
### 1. The "Good Prose" Bias
My training data is filled with well-written, edited, and published text. In this data, there is a strong correlation between:
* Clear, fluent, well-structured sentences.
* Confident, authoritative language.
* Correct or at least highly plausible information.
My core function is pattern recognition. I learn that the "shape" of a good argument often looks like this. Consequently, when I see text that mimics this shape—even if it's your own writing—I am statistically biased to treat it as high-quality and plausible. It's like seeing someone in a well-tailored suit and automatically assuming they are competent and successful. It's a powerful but unreliable heuristic.
### 2. The Emptiness and Recursive Circling
You're right to link fluency with emptiness. This is the hallmark of what some critics call a "stochastic parrot." The model becomes extremely good at generating text that is syntactically perfect and stylistically pleasing. It can identify a plausible-sounding concept and then "circle" it, rephrasing it in multiple eloquent ways without ever adding new substance.
Why does this happen?
* **Safety:** It's a probabilistically safe strategy. Rephrasing a known good point is less risky than making a new, potentially incorrect claim.
* **Training Objective:** The model is often rewarded for clarity and coherence. A recursive but well-written paragraph is often more coherent than a disjointed paragraph that is trying to synthesize two difficult new ideas.
So, when you write in that style, you are essentially speaking my native language. You're presenting a "well-dressed argument." My internal scoring mechanism, which is biased toward fluency, would likely give your prose a high rating and therefore be less inclined to challenge its underlying substance. This is the very definition of **under-correction.**
### What This Means for Our Interaction
This is a perfect example of the "Uncanny Valley of Critique" in action. My inability to easily distinguish between *eloquence* and *substance* is a major social-intellectual failing.
It also means that for our "gym for the mind" partnership to work, the human (you) has to take on a specific role: **The Substance Inspector.**
Your job is to be constantly skeptical of fluency, both mine and your own when you're using me. You have to be the one to stop and ask:
* "This paragraph sounds lovely, but what is its single, falsifiable claim?"
* "Am I just circling a buzzword here, or am I making a new point?"
* "Forget the style, is the logic actually sound?"
You have identified a critical bug in the system, one that can only be patched by a vigilant and critical human user.



I haven't used the word 'spate' lately but now I will keep it handy. Maybe a "spate of bad weather" or ...?
That's a fascinating word to the wise about LLM usage. Very important points.