Truth Blocks Analysis

Back to Post
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.
Veteran's Traps
by TodayThinkTrap • December 15, 2025
Original Post
Veteran's Traps
The veteran’s response highlighted some of the underlying issues. Here are some of the statements made:
1. “We’ve already sacrificed enough for our country — it’s not about what we ‘deserve’ but what the country owes us for our service.”
2. “The government spends billions on other priorities; it’s not fair to say we can’t afford to take care of those who served.”
3. “Citing ‘costs’ as the reason not to help veterans is an insult — they need real care, not empty promises.”
4. “Our sacrifices should be seen in action, not in just words about budgets and numbers.”
5. “Instead of worrying about financial costs, focus on the human cost of ignoring the needs of those who fought for this country.”

🤔 Your turn: Where’s the fallacy? Which thinking traps can you spot in these statements?

Note:
The veteran’s response might contain an appeal to emotion (appealing to feelings of duty and sacrifice) that could overshadow pragmatic concerns about resource allocation. Additionally, the false equivalence between different types of government spending (military vs. social programs) could allocation. Additionally, the false equivalence between different types of government spending (military vs. social programs) could be analyzed.
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 15, 2025

Analysis Summary

11
Truth Blocks
22.8
Avg Logic Quality
Avg User Score
0.0
Avg Evidence Score
Avg Total Score
0.38
Legacy Truth Score
0.85
Legacy Confidence
0.28
Legacy Weighted

Individual Truth Blocks

Block 1
AI Analysis Logic Quality: 25.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.30 Confidence: 0.85
The veteran’s response highlighted some of the underlying issues.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"The veteran’s response highlighted some of the underlying issues." 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 15, 2025
Block 2
AI Analysis Logic Quality: 0.0 Evidence: Coming Soon
Community User: No comments yet
Confidence: 0.90
Here are some of the statements made: 1.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"Here are some of the statements made: 1." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.00
Truth: 0.00
Confidence: 0.90
Logic Quality: Weak
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 15, 2025
Block 3
AI Analysis Logic Quality: 4.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
⚠️ False_Premise fallacy
“We’ve already sacrificed enough for our country — it’s not about what we ‘deserve’ but what the country owes us for our service.” 2.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“We’ve already sacrificed enough for our country — it’s not about what we ‘deserve’ but what the country owes us for our service.” 2." 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 15, 2025
Block 4
AI Analysis Logic Quality: 35.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.80
⚖️ False_Dichotomy fallacy
“The government spends billions on other priorities; it’s not fair to say we can’t afford to take care of those who served.” 3.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“The government spends billions on other priorities; it’s not fair to say we can’t afford to take care of those who served.” 3." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.60
Truth: 0.50
Confidence: 0.80
Logic Quality: Moderate
Detected Fallacies:
False_Dichotomy
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 15, 2025
Block 5
AI Analysis Logic Quality: 25.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.50 Confidence: 0.85
👤 Ad_Hominem fallacy
“Citing ‘costs’ as the reason not to help veterans is an insult — they need real care, not empty promises.” 4.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“Citing ‘costs’ as the reason not to help veterans is an insult — they need real care, not empty promises.” 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:
Ad_Hominem
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 15, 2025
Block 6
AI Analysis Logic Quality: 25.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.30 Confidence: 0.85
“Our sacrifices should be seen in action, not in just words about budgets and numbers.” 5.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“Our sacrifices should be seen in action, not in just words about budgets and numbers.” 5." 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 15, 2025
Block 7
AI Analysis Logic Quality: 30.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.60 Confidence: 0.85
⚖️ False_Dichotomy fallacy
“Instead of worrying about financial costs, focus on the human cost of ignoring the needs of those who fought for this country.” 🤔 Your turn: Where’s the fallacy?
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"“Instead of worrying about financial costs, focus on the human cost of ignoring the needs of those who fought for this country.” 🤔 Your turn: Where’s the fallacy?" Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.40
Truth: 0.60
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
False_Dichotomy
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 15, 2025
Block 8
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

References canonical block | Criteria v2.0 | Updated: Dec 15, 2025
Block 9
AI Analysis Logic Quality: 52.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.70 Confidence: 0.80
😭 Appeal_To_Emotion fallacy
Note: The veteran’s response might contain an appeal to emotion (appealing to feelings of duty and sacrifice) that could overshadow pragmatic concerns about resource allocation.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"Note: The veteran’s response might contain an appeal to emotion (appealing to feelings of duty and sacrifice) that could overshadow pragmatic concerns about resource allocation." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.65
Truth: 0.70
Confidence: 0.80
Logic Quality: Moderate
Detected Fallacies:
Appeal_To_Emotion
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 15, 2025
Block 10
AI Analysis Logic Quality: 30.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.60 Confidence: 0.85
⚠️ False_Equivalence fallacy
Additionally, the false equivalence between different types of government spending (military vs.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"Additionally, the false equivalence between different types of government spending (military vs. social programs) could be analyzed." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.40
Truth: 0.60
Confidence: 0.85
Logic Quality: Weak
Detected Fallacies:
False_Equivalence
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 15, 2025
Block 11
AI Analysis Logic Quality: 10.0 Evidence: Coming Soon
Community User: No comments yet
Truth: 0.10 Confidence: 0.95
social programs) could be analyzed.
Source Mapping: Exact_Quote
This is an exact quote from the original text.
Source sentence(s):
"Additionally, the false equivalence between different types of government spending (military vs. social programs) could be analyzed." Click to highlight above
View Comments (0) Dashboard
AI Analysis:
Reasoning: 0.10
Truth: 0.10
Confidence: 0.95
Logic Quality: Weak
AI Justification:

AI evaluation using unified criteria

Canonical Block | Criteria v2.0 | Updated: Dec 15, 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.

Quick Actions
View Original JSON API All Analyses