Soldier who questioned killings in Afghanistan was branded ‘Taliban-loving apologist’, inquiry hears ⁠64%

By Rosie Shead⁠82% Ellie Crabbe⁠82%

7/14/2026, 12:53:55 AM

BS Summary: This article contains 5 faulty reasoning types, including Post Hoc (False Cause), Confirmation Bias, and Negativity Bias, with Framing Effect as the most egregious example at 21.4% saturation with 33 hits. Analysis detected 115 faulty-reasoning hits from 154 analyzed words, generating a BS Score of 60.1% and a BS Rank of ⁠64% (5,495 of 15,282 articles). This article is worse (more manipulative) than 64.00% of the article peer group.

Christopher Green, an Army Reserve soldier, testified at the Afghanistan Inquiry that he was called a “Taliban-loving apologist” after questioning UK special forces over the killing of three farmers in 2012. 
Green, who served in Afghanistan, raised concerns after local elders reported the deaths in Rahim village, despite initial claims that the men were Taliban commanders. 
He stated that his unit's intelligence team found no evidence to suggest the farmers were anything other than civilians, casting doubt on the special forces' justification for the killings. 
The inquiry heard that the mother of the deceased farmers received an “assistance payment” of £3,634 from the UK Government, which Green interpreted as an “admission of guilt” for killing the wrong people. 
The ongoing Afghanistan Inquiry is investigating allegations of unlawful killings by UK special forces between 2010 and 2013 and claims of a subsequent cover-up. 
Confirmation Bias
16.2%
Anchoring Bias
0%
Availability Heuristic
0%
Representativeness Heuristic
0%
Hindsight Bias
0%
Overconfidence Bias
0%
Framing Effect
21.4%
Loss Aversion
0%
Status Quo Bias
0%
Sunk Cost Effect
0%
Optimism Bias
0%
Pessimism Bias
0%
Negativity Bias
7.8%
Self-Serving Bias
0%
Fundamental Attribution Error
0%
Actor-Observer Bias
0%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
0%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
0%
Primacy Effect
0%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
0%
False Dilemma
0%
Slippery Slope
0%
Circular Reasoning
0%
Hasty Generalization
0%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
0%
Begging the Question
0%
Post Hoc (False Cause)
21.4%
Tu Quoque
0%
Burden of Proof
0%
Appeal to Nature
0%
Composition/Division
0%
Anecdotal
0%
No True Scotsman
0%
Ambiguity (Equivocation)
0%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
0%
Quote-first Misdirection
7.8%
Biased Writer Voice
0%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
0%

154 words analyzed.

Speakers

1speaker19%attributed speech125writer words
Voice mapSelect a segment to jump to its words
Selected voice

Christopher Green

0%flagged-word coverage
29 attributed words100% of attributed speech56% writer coverage
Quote-first Misdirection-9.6 pts
Writer 9.6%Christopher Green 0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.