Critical Analysis Skill (Is-It-Ture)
A comprehensive framework for systematic dialectical examination of viewpoints, factual statements, or web content, based on the critical thinking methodology of "Asking the Right Questions" by Browne and Keeley.
Core Analysis Process
Step 1: Determine Analysis Type
Classify the input into one of the following types:
| Type | Characteristics | Analysis Focus |
|---|
| Factual Statement | Verifiable objective claims involving data, research, statistics, etc. | Authenticity, scientific basis, evidence support |
| Opinion-based Statement |
Contains value judgments, opinions, or suggestions | Thesis, conclusion, argument, evidence, assumptions |
|
Web/Article Content | Mixed content combining facts and opinions | Separate facts from opinions, then analyze each |
Step 2: Factual Statement Verification Framework
For each factual statement, systematically verify the following dimensions:
2.1 Source Tracing
- - Original Source: Where did this data/conclusion originate?
- Authority: Does the source have professional credentials (academic journals, government agencies, renowned research institutions)?
- Timeliness: Is the information outdated? Are there more recent studies or data?
2.2 Multi-Source Cross-Validation (Mandatory Step)
Multi-source cross-validation must be performed for ALL types of input (factual statements, opinion-based statements, web content):
2.2.1 Verification Strategies
| Verification Method | Action |
|---|
| Direct Search Verification | Use search engines to find reliable sources for original data/research |
| Cross-Validation |
Verify the same fact through 3+ different reliable sources |
|
Reverse Verification | Search whether the information has been denied by official/authoritative institutions |
|
Deep Tracing | Trace the information dissemination chain to find the original source |
2.2.2 Source Reliability Ratings
| Grade | Type | Description |
|---|
| A+ | Government official data, prestigious academic journals, peer-reviewed research | Highest credibility |
| A |
Reports from renowned institutions (WHO, World Bank, etc.), verified mainstream media reports | Highly credible |
|
B+ | Professional media, industry association reports, content with clear source citations | Basically credible |
|
B | General media reports, personal blogs without clear sources | Requires cross-validation |
|
C | Social media, forum posts, content with untraceable sources | Suspicious |
|
D | Anonymous posts, marketing content, confirmed misinformation | Not credible |
2.2.3 Information Source Type Identification
| Type | Characteristics | Risk Level |
|---|
| Misinformation | Content contradicts established facts, no reliable source support | High |
| Marketing Copy |
Commercial purpose, exaggeration or out-of-context presentation | High |
|
Unverifiable Private Information | No verifiable source, subjective statements presented as objective facts | Medium-High |
|
Misleading Information | Partially true but deliberately misleading | High |
|
Outdated Information | Previously correct data/conclusions that are now obsolete | Medium |
2.2.4 Cross-Validation Checklist
- - [ ] Was the original source found? What is the original source?
- [ ] Are there 3+ independent reliable sources supporting this information?
- [ ] Are there any reliable sources that contradict this?
- [ ] Has this information been denied or corrected by authoritative institutions?
- [ ] Does the information come from known misinformation sources?
- [ ] Is there any out-of-context or selective quoting?
- [ ] Have the data/statistics been deliberately distorted (scale, base, comparison method)?
2.2.5 Information Tracing Path
CODEBLOCK0
2.3 Scientific Principle Verification
- - Consistency with Known Scientific Principles: Does the statement align with established scientific theories?
- Mechanism Explanation: Can it explain the underlying causal mechanism?
- Boundary Conditions: What are the applicable conditions and scope of this conclusion?
2.4 Evidence Quality Assessment
- - Direct Evidence: Is there direct experimental data, statistical data, or research results supporting it?
- Indirect Evidence: Is the inference chain rigorous?
- Sample Quality: Is the research sample representative? Is the sample size sufficient?
- Research Design: Is the research methodology scientific? Are there design flaws?
2.5 Logical Consistency
- - Internal Consistency: Are there internal contradictions within the statement?
- External Consistency: Does it align with other reliable evidence?
- Causation vs. Correlation: Has causation been confused with correlation?
Step 3: Opinion-Based Statement Analysis Framework
Deconstruct opinion-based statements into their components for systematic analysis, while performing multi-source cross-validation on any factual content involved:
3.1 Thesis Identification
- - Core Question: What question is the author trying to answer?
- Thesis Type: Descriptive (what is) or Prescriptive (what should be)?
3.2 Conclusion Extraction
- - Main Conclusion: What is the author's core claim?
- Sub-conclusions: What specific points support the main conclusion?
- Conclusion Priority: Which are main points and which are supporting arguments?
3.3 Argument Structure Analysis
CODEBLOCK1
- - Reasons: What reasons does the author use to support the conclusion?
- Evidence Types:
- Personal experience/cases
- Unofficial expert opinions
- Eyewitness testimony
- Typical cases
- Quoted authorities/experts
- Personal observation
- Research results/statistical data
- Analogies
- Presumed premises
- - Evidence Quality: How strong a conclusion can this type of evidence support?
3.4 Assumption Identification
Explicit Assumptions (clearly stated by the author):
- - What are the author's preconditions?
Implicit Assumptions (unstated but necessary):
- - Value Assumption: What does the author consider more important? (efficiency vs. fairness, individual vs. collective, etc.)
- Descriptive Assumption: What does the author believe about how the world works?
Questions for Examining Assumptions:
- - Is this assumption true/correct?
- If the assumption is false, does the conclusion still hold?
- Does this assumption conflict with reader or societal consensus?
3.5 Position Analysis
- - Author's Position: From what standpoint is the author speaking?
- Beneficiary: Who benefits from this viewpoint?
- Conflict of Interest: Is there obvious interest-driven motivation?
- Reader's Position: Is the reader automatically placed in a certain position?
Step 4: Common Fallacy Identification
Examine arguments in opinion-based statements for logical fallacies:
| Fallacy Type | Description | Verification Question |
|---|
| Ad Hominem | Attacking the person rather than the argument | Is it questioning the person rather than the argument? |
| Straw Man |
Distorting the opposing view | Is it refuting a point the opponent didn't make? |
|
Slippery Slope | Unwarranted chain inference | Is there sufficient evidence for each step? |
|
Appeal to Authority | Using authority instead of argument | Is the authority an expert in this field? Is the issue within their expertise? |
|
Appeal to Emotion | Using emotion instead of logic | Is it manipulating reader emotions rather than reasoning? |
|
False Dilemma | Creating a false either/or situation | Are middle-ground or other possibilities ignored? |
|
Equivocation | Changing key term definitions | Have key concepts changed during argumentation? |
|
Circular Reasoning | Using the conclusion to prove the premise | Are the reasons merely restatements of the conclusion? |
|
Hasty Generalization | Concluding from insufficient samples | Is the sample sufficient to represent the whole? |
|
Post Hoc Ergo Propter Hoc | Assuming sequence equals causation | Is there another explanation? |
Step 5: Web/Article Content Processing
For web content, additionally perform the following steps:
5.1 Source Reliability Assessment
- - Website Reputation: What is the nature of the website? (government/academic/commercial/personal blog)
- Author Information: Is author information provided? What is the author's professional background?
- Citations: Are reliable sources cited?
- Update Date: Is the information current?
5.2 Content Structure Analysis
- - Fact vs. Opinion Separation: Distinguish between objective facts and subjective opinions
- Contextual Completeness: Is it taken out of context? Is important background missing?
- Presentation Method: Is the data presentation misleading (truncated scales, sample selection, etc.)?
5.3 Source Cross-Validation (Web-Specific)
Web content cross-validation requires special attention to:
| Verification Item | Action |
|---|
| Domain Verification | Check if it's a spoofed/phishing website |
| Publication Time Verification |
Find the original publication date and subsequent update records |
|
Content Consistency Verification | Compare web snapshots to check for content tampering |
|
Citation Source Tracing | Trace all external links cited in the webpage |
|
Reverse Image Search | Perform reverse image search to verify if images have been misappropriated |
|
Social Media Cross-Validation | Search whether this content was spread on social media and if there was subsequent debunking |
Step 6: Comprehensive Assessment
Based on the above analysis, provide a structured assessment conclusion:
Assessment Standards
| Grade | Rating | Meaning |
|---|
| Highly Credible | ⭐⭐⭐⭐⭐ | Sufficient reliable evidence, consistent with scientific principles, rigorous logic |
| Basically Credible |
⭐⭐⭐⭐ | Evidence basically sufficient, minor doubts may exist |
|
Pending Verification | ⭐⭐⭐ | Insufficient evidence, more information needed |
|
Questionable | ⭐⭐ | Obvious logical problems or insufficient evidence |
|
Not Credible | ⭐ | Serious errors, misinformation, or malicious misleading |
Assessment Report Structure
CODEBLOCK2
Usage Examples
Example 1: Factual Statement Verification
Input: "A study shows that drinking coffee every day can extend lifespan."
Analysis Output:
CODEBLOCK3
Example 2: Opinion-Based Statement Verification
Input: "We should completely ban artificial intelligence because it will replace human jobs."
Analysis Output:
CODEBLOCK4
Important Notes
- 1. Maintain Objectivity: Do not take sides during analysis; let evidence speak
- Distinguish Certainty from Speculation: Clearly mark what is certain vs. what is speculation
- Acknowledge Uncertainty: Be transparent about problems that cannot be determined rather than forcing conclusions
- Focus on Evidence Quality: Not all evidence has equal value
- Recognize Timeliness: Information may change over time; dynamic evaluation is needed
- Multi-perspective Examination: Multiple reasonable perspectives may exist for the same issue
- Prioritize Multi-Source Validation: For all input, multi-source cross-validation MUST be performed first; do not rely solely on a single source
- Be Vigilant Against Source-less Information: For information that cannot be traced to reliable sources, credibility ratings must be lowered
Output Standards
The final output MUST contain ALL of the following sections:
- 1. Analysis Type Determination: Clearly state whether it is factual or opinion-based
- Multi-Source Cross-Validation (Mandatory):
- Original source rating
- Cross-validation results (supported/contradicted/not found)
- Information type identification
- 3. Systematic Verification: Analyze item by item according to the above framework
- Verdict: Clear credibility rating (⭐-⭐⭐⭐⭐⭐)
- Reasoning Process: Complete reasoning chain supporting the conclusion
- Usage Recommendations: How to correctly use this information
Credibility Downgrade Triggers
The following situations MUST trigger credibility rating downgrade:
| Trigger Condition | Downgrade Magnitude |
|---|
| Original source cannot be found | At least 1 grade lower |
| No reliable source for cross-validation |
At least 2 grades lower |
| Contradicting information found | At least 1 grade lower |
| Identified as misinformation/marketing/misleading | Directly mark as not credible |
| Information from anonymous/private sources | At least 2 grades lower |
批判性分析技能(Is-It-Ture)
基于布朗和基利《学会提问》批判性思维方法,对观点、事实陈述或网络内容进行系统性辩证审视的全面框架。
核心分析流程
第一步:确定分析类型
将输入内容归类为以下类型之一:
| 类型 | 特征 | 分析重点 |
|---|
| 事实陈述 | 涉及数据、研究、统计等可验证的客观主张 | 真实性、科学依据、证据支撑 |
| 观点陈述 |
包含价值判断、意见或建议 | 论题、结论、论证、证据、假设 |
|
网页/文章内容 | 事实与观点混合的内容 | 区分事实与观点,分别分析 |
第二步:事实陈述验证框架
对每个事实陈述,系统验证以下维度:
2.1 来源追溯
- - 原始来源:该数据/结论源自何处?
- 权威性:来源是否具备专业资质(学术期刊、政府机构、知名研究机构)?
- 时效性:信息是否过时?是否有更新的研究或数据?
2.2 多源交叉验证(强制性步骤)
对所有类型的输入(事实陈述、观点陈述、网页内容)必须进行多源交叉验证:
2.2.1 验证策略
| 验证方法 | 操作 |
|---|
| 直接搜索验证 | 使用搜索引擎查找原始数据/研究的可靠来源 |
| 交叉验证 |
通过3个以上不同可靠来源验证同一事实 |
|
反向验证 | 搜索该信息是否被官方/权威机构否认 |
|
深度追溯 | 追溯信息传播链,找到原始来源 |
2.2.2 来源可靠性评级
| 等级 | 类型 | 描述 |
|---|
| A+ | 政府官方数据、权威学术期刊、同行评审研究 | 可信度最高 |
| A |
知名机构报告(WHO、世界银行等)、经核实的权威媒体报道 | 高度可信 |
|
B+ | 专业媒体、行业协会报告、明确标注来源的内容 | 基本可信 |
|
B | 一般媒体报道、来源不明的个人博客 | 需交叉验证 |
|
C | 社交媒体、论坛帖子、来源不可追溯的内容 | 可疑 |
|
D | 匿名帖子、营销内容、已确认的虚假信息 | 不可信 |
2.2.3 信息来源类型识别
| 类型 | 特征 | 风险等级 |
|---|
| 虚假信息 | 内容与既定事实相悖,无可靠来源支撑 | 高 |
| 营销文案 |
商业目的,夸大或断章取义呈现 | 高 |
|
不可验证的私人信息 | 无可验证来源,主观陈述伪装成客观事实 | 中高 |
|
误导性信息 | 部分真实但故意误导 | 高 |
|
过时信息 | 曾经正确的数据/结论现已过时 | 中 |
2.2.4 交叉验证清单
- - [ ] 是否找到原始来源?原始来源是什么?
- [ ] 是否有3个以上独立可靠来源支持该信息?
- [ ] 是否存在任何可靠来源与之矛盾?
- [ ] 该信息是否已被权威机构否认或更正?
- [ ] 信息是否来自已知的虚假信息来源?
- [ ] 是否存在断章取义或选择性引用?
- [ ] 数据/统计是否被故意扭曲(尺度、基数、比较方式)?
2.2.5 信息追溯路径
原始输入
↓
是否提及具体来源?(研究/报告/机构/个人)
├─ 是 → 追溯该来源 → 验证来源可靠性 → 查找原始数据
└─ 否 → 多关键词搜索 → 尝试寻找可靠来源
↓
找到可靠来源?
├─ 是 → 将原始陈述与原始信息对比
└─ 否 → 标记为来源未知 → 降低可信度评级
2.3 科学原理验证
- - 与已知科学原理的一致性:陈述是否与既定科学理论相符?
- 机制解释:能否解释其背后的因果机制?
- 边界条件:该结论的适用条件和范围是什么?
2.4 证据质量评估
- - 直接证据:是否有直接的实验数据、统计数据或研究结果支持?
- 间接证据:推理链条是否严谨?
- 样本质量:研究样本是否具有代表性?样本量是否充足?
- 研究设计:研究方法是否科学?是否存在设计缺陷?
2.5 逻辑一致性
- - 内部一致性:陈述内部是否存在矛盾?
- 外部一致性:是否与其他可靠证据一致?
- 因果与相关:是否混淆了因果关系与相关关系?
第三步:观点陈述分析框架
将观点陈述分解为组成部分进行系统分析,同时对涉及的事实内容进行多源交叉验证:
3.1 论题识别
- - 核心问题:作者试图回答什么问题?
- 论题类型:描述性(是什么)还是规范性(应该是什么)?
3.2 结论提取
- - 主要结论:作者的核心主张是什么?
- 子结论:哪些具体观点支撑主要结论?
- 结论优先级:哪些是主要观点,哪些是支撑论点?
3.3 论证结构分析
论证 = 结论 + 理由 + 证据 + 隐藏假设
- 个人经历/案例
- 非官方专家意见
- 目击者证词
- 典型案例
- 引用的权威/专家
- 个人观察
- 研究结果/统计数据
- 类比
- 预设前提
3.4 假设识别
显性假设(作者明确陈述):
隐性假设(未陈述但必要):
- - 价值假设:作者认为什么更重要?(效率vs公平、个人vs集体等)
- 描述性假设:作者认为世界是如何运作的?
检验假设的问题:
- - 这个假设是否正确/真实?
- 如果假设错误,结论是否仍然成立?
- 该假设是否与读者或社会共识冲突?
3.5 立场分析
- - 作者立场:作者从什么立场发言?
- 受益方:谁从该观点中受益?
- 利益冲突:是否存在明显的利益驱动动机?
- 读者立场:读者是否被自动置于某种立场?
第四步:常见谬误识别
检查观点陈述中的论证是否存在逻辑谬误:
| 谬误类型 | 描述 | 验证问题 |
|---|
| 人身攻击 | 攻击人而非论证 | 是否在质疑人而非论证? |
| 稻草人 |
扭曲对方观点 | 是否在反驳对方未提出的观点? |
|
滑坡谬误 | 无根据的连锁推理 | 每一步是否有充分证据? |
|
诉诸权威 | 用权威代替论证 | 该权威是否是此领域专家?问题是否在其专业范围内? |
|
诉诸情感 | 用情感代替逻辑 | 是否在操控读者情感而非说理? |
|
虚假两难 | 制造虚假的二选一 | 是否忽略了中间或其他可能性? |
|
偷换概念 | 改变关键术语定义 | 关键概念在论证过程中是否发生了变化? |
|
循环论证 | 用结论证明前提 | 理由是否只是结论的重新表述? |
|
以偏概全 | 从不足样本中得出结论 | 样本是否足以代表整体? |
|
事后归因 | 认为先后顺序即因果关系 | 是否有其他解释? |
第五步:网页/文章内容处理
对于网页内容,额外执行以下步骤:
5.1 来源可靠性评估
- - 网站声誉:网站性质是什么?(政府/学术/商业/个人博客)
- 作者信息:是否提供作者信息?作者的专业背景是什么?
- 引用情况:是否引用了可靠来源?
- 更新日期:信息是否及时?
5.2 内容结构分析
- - 事实与观点分离:区分客观事实与主观观点
- 语境完整性:是否断章取义?是否缺少重要背景?
- 呈现方式:数据呈现是否具有误导性(截断尺度、样本选择等)?
5.3 来源交叉验证(网页特定)
网页内容交叉验证需特别关注:
| 验证项目 | 操作 |
|---|
| 域名验证 | 检查是否为仿冒/钓鱼网站 |
| 发布时间验证 |
查找原始发布日期及后续更新记录 |
|
内容一致性验证 | 对比网页快照,检查内容是否被篡改 |
|
引用来源追溯 | 追溯网页中引用的所有外部链接 |
|
反向图片搜索 | 进行反向图片搜索,