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# LLM Prose Tells
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A catalog of patterns found in LLM-generated prose.
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Every pattern in this document shows up in human writing occasionally. They
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become diagnostic only through density. A person might use one or two across an
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entire essay, but LLM output packs fifteen into a single paragraph.
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---
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@@ -13,11 +15,19 @@ A negation followed by an em-dash and a reframe.
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> "It's not just a tool—it's a paradigm shift." "This isn't about
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> technology—it's about trust."
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The single most recognizable LLM construction. Models produce this at roughly 10
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to 50x the rate of human writers. Four of them in one essay and you know what
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you're reading.
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### Em-Dash Overuse Generally
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Even outside the "not X but Y" pivot, models substitute em-dashes for commas,
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semicolons, parentheses, colons, and periods. The em-dash can replace any other
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punctuation mark, so models default to it.
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Even outside the "not X but Y" pivot, models use em-dashes at far higher rates
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than human writers. They substitute em-dashes for commas, semicolons,
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parentheses, colons, and periods, often multiple times per paragraph. A human
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writer might use one or two in an entire piece for a specific parenthetical
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effect. Models scatter them everywhere because the em-dash can stand in for any
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other punctuation mark, so they default to it. More than two or three per page
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is a meaningful signal on its own.
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### The Colon Elaboration
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@@ -25,25 +35,33 @@ A short declarative clause, then a colon, then a longer explanation.
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> "The answer is simple: we need to rethink our approach from the ground up."
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Models reach for this in every other paragraph. The construction is perfectly
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normal. The frequency gives it away.
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### The Triple Construction
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> "It's fast, it's scalable, and it's open source."
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Three parallel items in a list, usually escalating. Always exactly three (rarely
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two, never four) with strict grammatical parallelism.
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two, never four) with strict grammatical parallelism that human writers rarely
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bother maintaining.
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### The Staccato Burst
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> "This matters. It always has. And it always will." "The data is clear. The
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> trend is undeniable. The conclusion is obvious."
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Runs of very short sentences at the same cadence and matching length.
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Runs of very short sentences at the same cadence. Human writers use a short
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sentence for emphasis occasionally, but stacking three or four of them in a row
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at matching length creates a mechanical regularity that reads as generated.
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### The Two-Clause Compound Sentence
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An independent clause, a comma, a conjunction ("and," "but," "which,"
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"because"), and a second independent clause of similar length. Every sentence
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becomes two balanced halves.
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Possibly the most pervasive structural tell, and easy to miss because each
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individual instance looks like normal English. The model produces sentence after
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sentence where an independent clause is followed by a comma, a conjunction
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("and," "but," "which," "because"), and a second independent clause of similar
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length. Every sentence becomes two balanced halves joined in the middle.
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> "The construction itself is perfectly normal, which is why the frequency is
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> what gives it away." "They contain zero information, and the actual point
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@@ -53,62 +71,76 @@ becomes two balanced halves.
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Human prose has sentences with one clause, sentences with three, sentences that
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start with a subordinate clause before reaching the main one, sentences that
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embed their complexity in the middle.
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embed their complexity in the middle. When every sentence on the page has that
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same two-part structure, the rhythm becomes monotonous in a way that's hard to
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pinpoint but easy to feel.
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### Uniform Sentences Per Paragraph
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Model-generated paragraphs contain between three and five sentences, a count
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that holds steady across a piece. If the first paragraph has four sentences,
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every subsequent paragraph will too.
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Model-generated paragraphs contain between three and five sentences. This count
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holds steady across an entire piece. If the first paragraph has four sentences,
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every subsequent paragraph will too. Human writers are much more varied (a
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single sentence followed by one that runs eight or nine) because they follow the
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shape of an idea, not a template.
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### The Dramatic Fragment
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Sentence fragments used as standalone paragraphs for emphasis.
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> "Full stop." "Let that sink in."
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Sentence fragments used as standalone paragraphs for emphasis, like "Full stop."
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or "Let that sink in." on their own line. Using one in an entire essay is a
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reasonable stylistic choice, but models drop them in once per section or more,
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at which point it becomes a habit rather than a deliberate decision.
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### The Pivot Paragraph
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> "But here's where it gets interesting." "Which raises an uncomfortable truth."
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One-sentence paragraphs that exist only to transition between ideas, containing
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zero information. The actual point is always in the next paragraph.
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One-sentence paragraphs that exist only to transition between ideas. They
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contain zero information. The actual point is always in the next paragraph.
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Delete every one of these and the piece reads better.
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### The Parenthetical Qualifier
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> "This is, of course, a simplification." "There are, to be fair, exceptions."
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Parenthetical asides inserted to perform nuance without changing the argument.
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Parenthetical asides inserted to look thoughtful. The qualifier never changes
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the argument that follows it. Its purpose is to perform nuance, not to express a
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real reservation about what's being said.
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### The Unnecessary Contrast
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A contrasting clause appended to a statement that doesn't need one, using
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"whereas," "as opposed to," "unlike," or "except that."
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Models append a contrasting clause to statements that don't need one, tacking on
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"whereas," "as opposed to," "unlike," or "except that" to draw a comparison the
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reader could already infer.
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> "Models write one register above where a human would, whereas human writers
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> tend to match register to context."
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The contrasting clause restates what the first clause already said. If you
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delete the "whereas" clause and the sentence still says everything it needs to,
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the contrast was filler.
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The first clause already makes the point. The contrasting clause restates it
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from the other direction. If you delete the "whereas" clause and the sentence
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still says everything it needs to, the contrast was filler.
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### Unnecessary Elaboration
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Models keep going after the sentence has already made its point.
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Models keep going after the sentence has already made its point, tacking on
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clarifying phrases, adverbial modifiers, or restatements that add nothing.
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> "A person might lean on one or two of these habits across an entire essay, but
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> LLM output will use fifteen of them per paragraph, consistently, throughout
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> the entire piece."
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This sentence could end at "paragraph." The words after it repeat what "per
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paragraph" already means. If you can cut the last third of a sentence without
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losing meaning, the last third shouldn't be there.
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This sentence could end at "paragraph." The words after it just repeat what "per
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paragraph" already means. Models do this because they're optimizing for clarity
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at the expense of concision, and because their training rewards thoroughness.
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The result is prose that feels padded. If you can cut the last third of a
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sentence without losing any meaning, the last third shouldn't be there.
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### The Question-Then-Answer
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> "So what does this mean for the average user? It means everything."
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A rhetorical question immediately followed by its own answer.
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A rhetorical question immediately followed by its own answer. Models do this two
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or three times per piece because it fakes forward momentum. A human writer might
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do it once.
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---
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@@ -116,38 +148,44 @@ A rhetorical question immediately followed by its own answer.
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### Overused Intensifiers
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"Crucial," "vital," "robust," "comprehensive," "fundamental," "arguably,"
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The following words appear at dramatically elevated rates in model output:
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"crucial," "vital," "robust," "comprehensive," "fundamental," "arguably,"
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"straightforward," "noteworthy," "realm," "landscape," "leverage" (as a verb),
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"delve," "tapestry," "multifaceted," "nuanced" (applied to the model's own
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analysis), "pivotal," "unprecedented" (applied to things with plenty of
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precedent), "navigate," "foster," "underscores," "resonates," "embark,"
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"streamline," "spearhead."
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"delve," "tapestry," "multifaceted," "nuanced" (which models apply to their own
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analysis with startling regularity), "pivotal," "unprecedented" (frequently
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applied to things with plenty of precedent), "navigate," "foster,"
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"underscores," "resonates," "embark," "streamline," and "spearhead." Three or
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more on the same page is a strong signal.
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### Elevated Register Drift
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Models write one register above where a human would, replacing "use" with
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"utilize," "start" with "commence," "help" with "facilitate," "show" with
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"demonstrate," "try" with "endeavor," "change" with "transform," and "make" with
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"craft."
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Models write one register above where a human would. "Use" becomes "utilize."
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"Start" becomes "commence." "Help" becomes "facilitate." "Show" becomes
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"demonstrate." "Try" becomes "endeavor." "Change" becomes "transform." "Make"
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becomes "craft." The tendency holds regardless of topic or audience.
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### Filler Adverbs
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"Importantly," "essentially," "fundamentally," "ultimately," "inherently,"
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"particularly," "increasingly." Dropped in to signal that something matters when
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the writing itself should make the importance clear.
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"particularly," "increasingly." Dropped in to signal that something matters,
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which is unnecessary when the writing itself already makes the importance clear.
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### The "Almost" Hedge
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Instead of saying a pattern "always" or "never" does something, models write
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"almost always," "almost never," "almost certainly," "almost exclusively." A
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micro-hedge, less obvious than the full hedge stack.
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Models rarely commit to an unqualified statement. Instead of saying a pattern
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"always" or "never" does something, they write "almost always," "almost never,"
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"almost certainly," "almost exclusively." The word "almost" shows up at
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extraordinary density in model-generated analytical prose. It's a micro-hedge,
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less obvious than the full hedge stack but just as diagnostic when it appears
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ten or fifteen times in a single document.
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### "In an era of..."
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> "In an era of rapid technological change..."
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Used to open an essay. The model is stalling while it figures out what the
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actual argument is.
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A model habit as an essay opener. The model uses it to stall while it figures
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out what the actual argument is. Human writers don't begin a piece by zooming
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out to the civilizational scale before they've said anything specific.
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---
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@@ -158,20 +196,24 @@ actual argument is.
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> "While X has its drawbacks, it also offers significant benefits."
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Every argument followed by a concession, every criticism softened. A direct
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artifact of RLHF training, which penalizes strong stances.
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artifact of RLHF training, which penalizes strong stances. Models reflexively
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both-sides everything even when a clear position would serve the reader better.
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### The Throat-Clearing Opener
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> "In today's rapidly evolving digital landscape, the question of data privacy
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> has never been more important."
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The first paragraph adds no information. Delete it and the piece improves.
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The first paragraph of most model-generated essays adds no information. Delete
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it and the piece improves immediately. The actual argument starts in paragraph
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two.
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### The False Conclusion
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> "At the end of the day, what matters most is..." "Moving forward, we must..."
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The high school "In conclusion,..." dressed up for a professional audience.
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Signals that the model is wrapping up without actually landing on anything.
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### The Sycophantic Frame
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@@ -192,13 +234,15 @@ the key considerations:"
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> cases it can potentially offer significant benefits."
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Five hedges in one sentence ("worth noting," "while," "may not be," "in many
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cases," "can potentially"), communicating nothing.
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cases," "can potentially"), communicating nothing. The model would rather be
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vague than risk being wrong about anything.
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### The Empathy Performance
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> "This can be a deeply challenging experience." "Your feelings are valid."
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Generic emotional language that could apply to anything.
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Generic emotional language that could apply equally to a bad day at work or a
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natural disaster. That interchangeability is what makes it identifiable.
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---
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@@ -206,28 +250,35 @@ Generic emotional language that could apply to anything.
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### Symmetrical Section Length
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If the first section runs about 150 words, every subsequent section will fall
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between 130 and 170.
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If the first section of a model-generated essay runs about 150 words, every
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subsequent section will fall between 130 and 170. Human writing is much more
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uneven, with 50 words in one section and 400 in the next.
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### The Five-Paragraph Prison
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Model essays follow a rigid introduction-body-conclusion arc even when nobody
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asked for one. The introduction previews the argument, the body presents 3 to 5
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points, the conclusion restates the thesis.
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points, and then the conclusion restates the thesis using slightly different
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words.
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### Connector Addiction
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The first word of each paragraph forms an unbroken chain of transition words:
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"However," "Furthermore," "Moreover," "Additionally," "That said," "To that
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end," "With that in mind," "Building on this."
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Look at the first word of each paragraph in model output. You'll find an
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unbroken chain of transition words: "However," "Furthermore," "Moreover,"
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"Additionally," "That said," "To that end," "With that in mind," "Building on
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this." Human prose moves between ideas without announcing every transition.
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### Absence of Mess
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Model prose doesn't contradict itself mid-paragraph and then catch the
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contradiction, go on a tangent and have to walk it back, use an obscure idiom
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without explaining it, make a joke that risks falling flat, leave a thought
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genuinely unfinished, or keep a sentence the writer liked the sound of even
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though it doesn't quite work.
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contradiction. It doesn't go on a tangent and have to walk it back, use an
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obscure idiom without explaining it, make a joke that risks falling flat, leave
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a thought genuinely unfinished, or keep a sentence the writer liked the sound of
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even though it doesn't quite work.
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Human writing does all of those things regularly. That total absence of rough
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patches and false starts is one of the strongest signals that text was
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machine-generated.
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---
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@@ -237,27 +288,45 @@ though it doesn't quite work.
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> "This has implications far beyond just the tech industry."
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Zooming out to claim broader significance without substantiating it.
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Zooming out to claim broader significance without substantiating it. The model
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has learned that essays are supposed to gesture at big ideas, so it gestures.
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Nothing concrete is behind the gesture.
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### "It's important to note that..."
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This phrase and its variants ("it's worth noting," "it bears mentioning," "it
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should be noted") function as verbal tics before a qualification the model
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believes someone expects.
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should be noted") appear at absurd rates in model output. They function as
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verbal tics before a qualification the model believes someone expects.
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### The Metaphor Crutch
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Models rely on a small, predictable set of metaphors: "double-edged sword," "tip
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Models rely on a small, predictable set of metaphors ("double-edged sword," "tip
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of the iceberg," "north star," "building blocks," "elephant in the room,"
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"perfect storm," "game-changer."
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"perfect storm," "game-changer") and reach for them with unusual regularity
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across every topic. The pool is noticeably smaller than what human writers draw
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from.
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---
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## How to Actually Spot It
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No single pattern on this list proves anything by itself. Humans use em-dashes.
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Humans write "crucial." Humans ask rhetorical questions.
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What gives it away is how many of these show up at once. Model output will hit
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10 to 20 of these patterns per page. Human writing might trigger 2 or 3,
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distributed unevenly, mixed with idiosyncratic constructions no model would
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produce. When every paragraph on the page reads like it came from the same
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careful, balanced, slightly formal, structurally predictable process, it was
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generated by one.
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---
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## Copyediting Checklist: Removing LLM Tells
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Follow this checklist when editing any document to remove machine-generated
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patterns. Do at least two full passes, because fixing one pattern often
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introduces another.
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patterns. Go through the entire list for every piece. Do at least two full
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passes, because fixing one pattern often introduces another.
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### Pass 1: Word-Level Cleanup
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@@ -271,7 +340,8 @@ introduces another.
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2. Search for filler adverbs ("importantly," "essentially," "fundamentally,"
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"ultimately," "inherently," "particularly," "increasingly") and delete every
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instance where the sentence still makes sense without it.
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instance where the sentence still makes sense without it. That will be most
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of them.
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3. Look for elevated register drift ("utilize," "commence," "facilitate,"
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"demonstrate," "endeavor," "transform," "craft" and similar) and replace with
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@@ -279,6 +349,7 @@ introduces another.
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4. Search for "it's important to note," "it's worth noting," "it bears
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mentioning," and "it should be noted" and delete the phrase in every case.
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The sentence that follows always stands on its own.
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5. Search for the stock metaphors ("double-edged sword," "tip of the iceberg,"
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"north star," "building blocks," "elephant in the room," "perfect storm,"
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@@ -287,114 +358,101 @@ introduces another.
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6. Search for "almost" used as a hedge ("almost always," "almost never," "almost
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certainly," "almost exclusively") and decide in each case whether to commit
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to the unqualified claim or to drop the sentence entirely.
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to the unqualified claim or to drop the sentence entirely. If the claim needs
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"almost" to be true, it might not be worth making.
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7. Search for em-dashes and replace each one with the punctuation mark that
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would normally be used in that position (comma, semicolon, colon, period, or
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parentheses). If you can't identify which one it should be, the sentence
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needs to be restructured.
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8. Remove redundant adjectives. For each adjective, ask whether the sentence
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changes meaning without it. "A single paragraph" means the same as "a
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paragraph." "An entire essay" means the same as "an essay." If the adjective
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doesn't change the meaning, cut it.
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9. Remove unnecessary trailing clauses. Read the end of each sentence and ask
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whether the last clause restates what the sentence already said. If so, end
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the sentence earlier.
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### Pass 2: Sentence-Level Restructuring
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10. Find every em-dash pivot ("not X—but Y," "not just X—Y," "more than X—Y")
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and rewrite it as two separate clauses or a single sentence that makes the
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|
point without the negation-then-correction structure.
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8. Find every em-dash pivot ("not X...but Y," "not just X...Y," "more than
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X...Y") and rewrite it as two separate clauses or a single sentence that
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makes the point without the negation-then-correction structure.
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11. Find every colon elaboration and check whether it's doing real work. If the
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clause before the colon could be deleted without losing meaning, rewrite the
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sentence to start with the substance that comes after the colon.
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9. Find every colon elaboration and check whether it's doing real work. If the
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clause before the colon could be deleted without losing meaning, rewrite the
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sentence to start with the substance that comes after the colon.
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12. Find every triple construction (three parallel items in a row) and either
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10. Find every triple construction (three parallel items in a row) and either
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|
reduce it to two, expand it to four or more, or break the parallelism so the
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items don't share the same grammatical structure.
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13. Find every staccato burst (three or more short sentences in a row at similar
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11. Find every staccato burst (three or more short sentences in a row at similar
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|
length) and combine at least two of them into a longer sentence, or vary
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|
their lengths so they don't land at the same cadence.
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14. Find every unnecessary contrast ("whereas," "as opposed to," "unlike," "as
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|
12. Find every unnecessary contrast ("whereas," "as opposed to," "unlike," "as
|
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|
|
compared to," "except that") and check whether the contrasting clause adds
|
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|
|
information not already obvious from the main clause. If the sentence says
|
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|
|
the same thing twice from two directions, delete the contrast.
|
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|
15. Check for the two-clause compound sentence pattern. If most sentences in a
|
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|
|
passage follow the "\[clause\], \[conjunction\] \[clause\]" structure, first
|
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|
|
try removing the conjunction and second clause entirely, since it's often
|
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|
|
redundant. If the second clause does carry meaning, break it into its own
|
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|
|
sentence, start the sentence with a subordinate clause, or embed a relative
|
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|
|
clause in the middle instead of appending it at the end.
|
|
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|
|
13. Check for the two-clause compound sentence pattern. If most sentences in a
|
|
|
|
|
passage follow the "\[clause\], \[conjunction\] \[clause\]" structure,
|
|
|
|
|
rewrite some of them. Break a few into two sentences. Start some with a
|
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|
|
subordinate clause. Embed a relative clause in the middle of one instead of
|
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|
|
appending it at the end. The goal is variety in sentence shape, not just
|
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|
|
sentence length.
|
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|
16. Find every rhetorical question that is immediately followed by its own
|
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|
|
14. Find every rhetorical question that is immediately followed by its own
|
|
|
|
|
answer and rewrite the passage as a direct statement.
|
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|
|
17. Find every sentence fragment being used as its own paragraph and either
|
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|
|
delete it or expand it into a complete sentence that adds information.
|
|
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|
|
15. Find every sentence fragment being used as its own paragraph and either
|
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|
|
delete it or expand it into a complete sentence that adds actual
|
|
|
|
|
information.
|
|
|
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|
|
18. Check for unnecessary elaboration. Read every clause, phrase, and adjective
|
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|
|
in each sentence and ask whether the sentence loses meaning without it. If
|
|
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|
|
you can cut it and the sentence still says the same thing, cut it.
|
|
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|
|
16. Check for unnecessary elaboration at the end of sentences. Read the last
|
|
|
|
|
clause or phrase of each sentence and ask whether the sentence would lose
|
|
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|
|
any meaning without it. If not, cut it.
|
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|
|
19. Check each pair of adjacent sentences to see if they can be merged into one
|
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|
|
sentence cleanly. If a sentence just continues the thought of the previous
|
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|
|
one, combine them using a participle, a relative clause, or by folding the
|
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|
|
second into the first. Don't merge if the result would create a two-clause
|
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|
|
compound.
|
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|
|
20. Find every pivot paragraph ("But here's where it gets interesting." and
|
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|
|
|
similar) and delete it.
|
|
|
|
|
17. Find every pivot paragraph ("But here's where it gets interesting." and
|
|
|
|
|
similar) and delete it. The paragraph after it always contains the actual
|
|
|
|
|
point.
|
|
|
|
|
|
|
|
|
|
### Pass 3: Paragraph and Section-Level Review
|
|
|
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|
|
|
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|
|
21. Review the last sentence of each paragraph. If it restates the point the
|
|
|
|
|
paragraph already made, delete it.
|
|
|
|
|
|
|
|
|
|
22. Check paragraph lengths across the piece and verify they actually vary. If
|
|
|
|
|
18. Check paragraph lengths across the piece and verify they actually vary. If
|
|
|
|
|
most paragraphs have between three and five sentences, rewrite some to be
|
|
|
|
|
one or two sentences and let others run to six or seven.
|
|
|
|
|
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|
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|
|
23. Check section lengths for suspicious uniformity. If every section is roughly
|
|
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|
|
19. Check section lengths for suspicious uniformity. If every section is roughly
|
|
|
|
|
the same word count, combine some shorter ones or split a longer one
|
|
|
|
|
unevenly.
|
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|
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|
|
24. Check the first word of every paragraph for chains of connectors ("However,"
|
|
|
|
|
20. Check the first word of every paragraph for chains of connectors ("However,"
|
|
|
|
|
"Furthermore," "Moreover," "Additionally," "That said"). If more than two
|
|
|
|
|
transition words start consecutive paragraphs, rewrite those openings to
|
|
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|
|
start with their subject.
|
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|
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|
|
25. Check whether every argument is followed by a concession or qualifier. If
|
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|
|
21. Check whether every argument is followed by a concession or qualifier. If
|
|
|
|
|
the piece both-sides every point, pick a side on at least some of them and
|
|
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|
|
cut the hedging.
|
|
|
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|
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|
|
26. Read the first paragraph and ask whether deleting it would improve the
|
|
|
|
|
22. Read the first paragraph and ask whether deleting it would improve the
|
|
|
|
|
piece. If it's scene-setting that previews the argument, delete it and start
|
|
|
|
|
with paragraph two.
|
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|
|
27. Read the last paragraph and check whether it restates the thesis or uses a
|
|
|
|
|
23. Read the last paragraph and check whether it restates the thesis or uses a
|
|
|
|
|
phrase like "at the end of the day" or "moving forward." If so, either
|
|
|
|
|
delete it or rewrite it to say something the piece hasn't said yet.
|
|
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|
|
|
|
|
|
|
### Pass 4: Overall Texture
|
|
|
|
|
|
|
|
|
|
28. Read the piece aloud and listen for passages that sound too smooth, too
|
|
|
|
|
24. Read the piece aloud and listen for passages that sound too smooth, too
|
|
|
|
|
even, or too predictable. Human prose has rough patches. If there aren't
|
|
|
|
|
any, the piece still reads as machine output.
|
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|
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|
|
29. Check that the piece contains at least a few constructions that feel
|
|
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|
|
25. Check that the piece contains at least a few constructions that feel
|
|
|
|
|
idiosyncratic: a sentence with unusual word order, a parenthetical that goes
|
|
|
|
|
on a bit long, an aside only loosely connected to the main point, a word
|
|
|
|
|
choice that's specific and unexpected.
|
|
|
|
|
choice that's specific and unexpected. If every sentence is clean and
|
|
|
|
|
correct and unremarkable, it will still read as generated.
|
|
|
|
|
|
|
|
|
|
30. Verify that you haven't introduced new patterns while fixing the original
|
|
|
|
|
ones. Run the entire checklist again from the top on the revised version.
|
|
|
|
|
26. Verify that you haven't introduced new patterns while fixing the original
|
|
|
|
|
ones. This happens constantly. Run the entire checklist again from the top
|
|
|
|
|
on the revised version.
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
@@ -441,9 +499,16 @@ roughly like this:
|
|
|
|
|
>
|
|
|
|
|
> **model:** _(rewrites entire document without em-dashes while describing
|
|
|
|
|
> em-dash overuse)_
|
|
|
|
|
>
|
|
|
|
|
> **human:** now run the checklist methodically on each paragraph
|
|
|
|
|
>
|
|
|
|
|
> **model:** _(finds staccato burst in the section about triple constructions, a
|
|
|
|
|
> triple in the section about absence of mess, two-clause compounds everywhere,
|
|
|
|
|
> and "almost" hedges in its own prose about em-dash overuse)_
|
|
|
|
|
|
|
|
|
|
The human compared this process to the deleted scene in Terminator 2 where John
|
|
|
|
|
Connor switches the T-800's CPU to learning mode. The model compared it to a
|
|
|
|
|
physician trying to heal itself. Both are accurate.
|
|
|
|
|
|
|
|
|
|
This document has been through ten editing passes and it still has tells in it.
|
|
|
|
|
This document has been through eight editing passes and it still has tells in
|
|
|
|
|
it.
|
|
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|
|