‘Moderate’ Dem gubernatorial candidate embraced DEI budget tool, Green New Deal-style policies
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What the model flagged
Analyzed 2026-08-25 04:04 UTC. Articles are sometimes updated after publication — if a quote below isn't in the current version, the piece has changed since.
Findings may include language the outlet is quoting rather than asserting. We flag manipulation techniques wherever they appear, including inside quotations — so check each quote against the original before drawing a conclusion about the outlet.
Name Calling 85%
Francesca Hong is labeled 'socialist' and Hasan Piker is labeled 'far-left' — derogatory political labels used to discredit rather than describe policy positions — for example: 'socialist Francesca Hong' and 'far-left streamer Hasan Piker'
“socialist Francesca Hong”
“far-left streamer Hasan Piker”
Loaded Language 65%
The phrase 'far-left flank' is an emotionally charged political label designed to frame progressive policies as extreme rather than as a neutral descriptor — for example: 'far-left flank'
“far-left flank”
Card Stacking 80%
The sentence selectively lists negative fiscal outcomes (tax hikes, higher sales taxes) alongside the unverified characterization of the Net Zero policy as a 'scam', presenting partisan framing as equivalent to factual claims without qualification — for example: listing verified tax increases alongside 'scam' characterization
“largest property tax hike in 15 years”
“paid higher sales taxes”
“Green New Deal 'Net Zero' scam”
Appeal To Prejudice 80%
The question is framed to invoke Wisconsinites' in-group identity and pride to steer them toward a predetermined conclusion — for example: Wisconsinites should ask themselves
“Wisconsinites should ask themselves”
Bandwagon Appeal 75%
The phrase implies a collective, unanimous rejection by Wisconsin residents, pressuring conformity through implied crowd consensus — for example: a big Wisconsin 'heck no'
“a big Wisconsin 'heck no'”
Analyzed automatically with Biasly's fine-tuned model. These are manipulation techniques, not political tilt — and finding one is not a claim that the article is false. 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 →