NY Rep. Mike Lawler’s race now a ‘toss-up’ as Dems target battleground district that could flip Congress

Open the full analysis → Read the original article at New York Post →

Flags are about wording, sourcing and context, not whether it’s true or which side is right. How we check

Wording

7%of the article’s sentences use a rhetorical technique

Tap a technique to see where it’s used.

What these techniques mean

Loaded Language Emotionally charged words that push a reaction instead of giving information.Show the first one ↓

Name Calling A label used to mock or discredit instead of an argument.Show the first one ↓

Black-and-White Fallacy Two options presented as the only ones, when there are more.Show the first one ↓

ClaimsCheck the factual claims in this article →

What the model flagged

underlined: technique found; pick one to highlight its words tap a technique for why

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Loaded LanguageWhy ›

Emotionally charged words chosen to trigger a reaction rather than convey facts.

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Name CallingWhy ›

Derogatory labels used to discredit a person or group rather than address their arguments.

“unlike Mike, who spends his time cozying up to the corporations” … “Cait isn't taking a single vote for granted”

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Black-and-White Fallacy · “unlike Mike, who spends his time cozying up to the corporations”, “Cait isn't taking a single vote for granted”Why ›

The sentence implicitly presents only two options: Mike who is corrupt and beholden to special interests, versus Cait who is virtuous and grassroots, leaving no middle ground.

Read the original ↗ · Open the full analysis →

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Analyzed 2026-07-31 19:23 UTC. Articles are sometimes updated after publication — if a quote here isn't in the current version, the piece has changed since.

Analyzed automatically with Semblen's fine-tuned model. These are rhetorical techniques, not political tilt — and finding one is not a claim that the article is false. Findings include language the outlet is quoting rather than asserting: we flag techniques wherever they appear, so check each quote against the original. The model has known false positives on strong-but-legitimate language, so treat each finding as a prompt to read closely, not a verdict. How articles are chosen →