lpm.org Media Bias



Identity signals (probabilistic): The sample self-references as “LPM News,” “LPM,” and 89.3 WFPL, and discloses local funders and an OpenAI Foundation grant, strongly indicating a Louisville public-radio outlet       .
General framing: Overwhelmingly civic-institutional and attribution-heavy. Election stories cite clerks, AP race calls, and finance filings while flagging unofficial-status caveats       ; even House-election coverage attributes counts to the AP with precise percentages     .

This matches procedural, records-driven reporting rather than ideological argumentation, consistent with the historical summaries.
Topic selection: Dense local focus — Kentucky/Indiana elections     , Metro Council and school board     , courts     , corporate litigation   , transit/crash recovery     , community health   , arts and public media       . Little national-ideological or foreign coverage appears.
Where the tilt shows: Mostly in interpretation, not wording of results. Several election pieces adopt mild pro-Democratic causal frames: “blue tsunami,” “tanking popularity,” and “toxic” GOP environment     , and a “Blue wave” upset frame   ; a statehouse piece foregrounds national polls favoring Democrats   .

Wording itself stays largely sober, with explicit counterweights such as Cook's “solid Republican” rating and internal-poll caveats   .
Recurring frame: A populist “dark money” lens recurs — billionaire PACs   , Beshear's “dark-money group Heckbent”   , and a Beshear judicial endorsement framed as an effort to “tip the scales”   .

This anti-undisclosed-money posture appears on both parties, which supports process integrity over partisanship, though the “dark money” label itself carries evaluative baggage     .
Empathy/community bias: Sympathetic victim/community frames appear for disaster-hit businesses   , West End residents   , and veterans   — labeled single-perspective features, which is acceptable for the genre but structurally one-sided.
Reliability evidence: Strong — named sources, quantified filings, editor's notes disclosing funders and no-response contacts       ; minor lapses include low-resourced losers represented only by “unavailable” notes   .
AI authorship: No strong evidence of full AI authorship: variable voice, humor, editorial notes, inconsistent quotes (e.g., a typo “it's” for “its”   ) suggest human editing; metadata structure suggests possibly AI-assisted annotation.
Propaganda techniques: Little classic propaganda; observable instances are loaded labeling (“dark money”     , “mysterious” donor   ) and mild causal attribution without proof (Trump's approval causing victories     ).
Highest values: 1) Procedural integrity/attribution     ; 2) Local accountability/watchdoging     ; 3) Community empathy     .
Lowest values: 1) National-ideological neutrality (interpretive slants     ); 2) Emotional restraint in human-interest framing   ; 3) Equivalent resourcing of all political sides   .
Counterexamples: Genuinely balanced profiles exist     ; no counterexample to the empathy frame appears in the sample beyond institutional response inclusion   .

Helium Bias: I assume article metadata summaries fairly represent full texts; they were likely AI-generated annotations, adding distortion.

Sample skews to election-cycle coverage (Nov 2026) and unusual items, overrepresenting political stories versus routine output.

I cannot observe unpublished stories, wire-share arrangements, or editorial priorities behind them.

Historical summaries were treated as context only.

AI-authorship judgments remain probabilistic from surface features; no ground truth about the newsroom was available.

Automated source summary · Updated November 08, 2026 · Not human reviewed. Check recent article panels for claim-level evidence when available.




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lpm.org Bias Profile

Weighted source-level patterns from recent analyzed coverage. Open recent articles below to inspect score-specific evidence and limitations when available.

🗞️ Objective <—> Subjective 👁️ -7

💡 Boring <—> Interesting13

😨 Fearful8

💭 Opinion40

🗳 Political22

Oversimplification6

🏛️ Appeal to Authority14

👀 Covering Responses13

😢 Victimization8

😤 Overconfidence8

🔒 Ideological8

❌ Low Credibility <—> High Credibility ✅31

🧠 Rational <—> Irrational 🤪-10

🤑 Advertising14

💔 Low Integrity <—> High Integrity ❤️22

🪨 Low Intelligence <—> High Intelligence 🦉46

✊ Woke10

🎭 Virtue Signaling18

🎲 Speculation13

🐍 Manipulative15

Subtle dimensions

🔵 Liberal <—> Conservative 🔴-5

🧢 Populist <—> Elitist 🎩-3

🗽 Libertarian <—> Authoritarian 🚔-2

🚨 Sensational0

📉 Bearish <—> Bullish 📈1

😩 Pessimistic <—> Optimistic 🌞3

📝 Prescriptive0

📞 Begging the Question0

🗑️ Spam2

🏴 Anti-establishment <—> Pro-establishment 📺3

📏📏 Double Standard0

🤖 Written by AI0

👺 Marxism0

🔪 Cruel0

🔍 Truth-seeking <—> Delusion 🌀-2

🐐 Scapegoating2

🤡 Hypocrisy0

🦊 Anti-Corporate <—> Pro-Corporate 👔0

🔬 Scientific <—> Superstitious 🔮-4

👤 Individualist <—> Collectivist 👥3

💊 Big Pharma2

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