Truth Blocks Analysis

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New Scoring System: This post's overall score is calculated from the individual truth blocks below. To provide feedback or discuss specific arguments, comment on individual truth blocks rather than the post as a whole.
Halle Berry Traps
by TodayThinkTrap • December 05, 2025
Original Post
Halle Berry Traps
🗣️ Here are several statements made around the recent debate on California’s menopause bill:

1. “With the way he’s overlooked women, he probably shouldn’t be our next president either.”
2. “By vetoing the menopause bill two years in a row, he’s devaluing half the population.”
3. “Illinois is the first state to mandate hormone therapy coverage, and California should be ashamed not to follow.”
4. “Women deserve better — the days of outliving men but doing it in poor health are over.”
5. “I have zero left to give, and I’m going to fight like hell because women’s longevity depends on it.”
6. “The bill would have unintentionally raised health care costs for millions of working women and working families — something we must avoid.”
7. “By working together, we can expand menopause care without raising bills for women.”

🤔 Your turn: Where’s the fallacy? Which thinking traps can you spot in these statements?
Highlighted sentences link to their corresponding truth blocks. Click any highlighted sentence to jump to its detailed analysis.
Highlight Colors Indicate Content Type & Quality:
Strong Reasoning - Clear logic & evidence
Moderate - Some structure, could improve
Weak Reasoning - Fallacies or poor logic
ℹ️ Not Evaluable - Questions, personal statements (not poor quality)
Note: Gray highlights with dashed borders (ℹ️) indicate content like questions or personal experiences that aren't meant to present logical arguments. Low scores on these don't mean poor quality!
By TodayThinkTrap on December 05, 2025

Analysis Summary

9
Truth Blocks
11.9
Avg Logic Quality
Avg User Score
0.0
Avg Evidence Score
Avg Total Score
0.39
Legacy Truth Score
0.86
Legacy Confidence
0.22
Legacy Weighted

Individual Truth Blocks

Block 1
AI Analysis Logic Quality: 10.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.10 Confidence: 0.90
🗣️ Here are several statements made around the recent debate on California’s menopause bill: 1.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"🗣️ Here are several statements made around the recent debate on California’s menopause bill: 1." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.10
Truth: 0.10
Confidence: 0.90
Logic Quality: Weak
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 2
AI Analysis Logic Quality: 20.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
👤 Ad_Hominem fallacy
“With the way he’s overlooked women, he probably shouldn’t be our next president either.” 2.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“With the way he’s overlooked women, he probably shouldn’t be our next president either.” 2." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.30
Truth: 0.50
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
Ad_Hominem
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 3
AI Analysis Logic Quality: 4.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
⚠️ Non_Sequiturs fallacy
“By vetoing the menopause bill two years in a row, he’s devaluing half the population.” 3.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“By vetoing the menopause bill two years in a row, he’s devaluing half the population.” 3." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.40
Truth: 0.50
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
Non_Sequiturs
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 4
AI Analysis Logic Quality: 4.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
⚠️ False_Premise fallacy
“Illinois is the first state to mandate hormone therapy coverage, and California should be ashamed not to .” 4.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“Illinois is the first state to mandate hormone therapy coverage, and California should be ashamed not to .” 4." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.40
Truth: 0.50
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
False_Premise
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 5
AI Analysis Logic Quality: 0.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
⚠️ False_Premise fallacy
“Women deserve better — the days of outliving men but doing it in poor health are over.” 5.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“Women deserve better — the days of outliving men but doing it in poor health are over.” 5." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.30
Truth: 0.50
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
False_Premise
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 6
AI Analysis Logic Quality: 25.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.30 Confidence: 0.85
“I have zero left to give, and I’m going to fight hell because women’s longevity depends on it.” 6.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“I have zero left to give, and I’m going to fight hell because women’s longevity depends on it.” 6." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.20
Truth: 0.30
Confidence: 0.85
Logic Quality: Weak
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 7
AI Analysis Logic Quality: 4.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
⚠️ False_Premise fallacy
“The bill would have unintentionally raised health care costs for millions of working women and working families — something we must avoid.” 7.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“The bill would have unintentionally raised health care costs for millions of working women and working families — something we must avoid.” 7." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.40
Truth: 0.50
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
False_Premise
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 8
AI Analysis Logic Quality: 25.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
🛷 Slippery_Slope fallacy
“By working together, we can expand menopause care without raising bills for women.” 🤔 Your turn: Where’s the fallacy?
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“By working together, we can expand menopause care without raising bills for women.” 🤔 Your turn: Where’s the fallacy?" Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.40
Truth: 0.50
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
Slippery_Slope
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
Block 9
AI Analysis Logic Quality: 15.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.10 Confidence: 0.85
Which thinking traps can you spot in these statements?
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"Which thinking traps can you spot in these statements?" Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.20
Truth: 0.10
Confidence: 0.85
Logic Quality: Weak
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 05, 2025
About Truth Blocks

Truth blocks are minimal argument units that represent atomic reasoning. Each block is analyzed independently for:

  • Truth Score: Factual accuracy (0-1)
  • Reasoning Types: Deductive, inductive, etc.
  • Logical Fallacies: Detected reasoning errors
  • Confidence: AI certainty in analysis

The weighted score combines truth score with reasoning quality and fallacy penalties according to our scoring criteria.

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