grad-critical-realism
用批判實在論從相關走到因果，找出背後的生成性機制
中文翻譯
--- name: "grad-critical-realism" description: "用 Bhaskar 的批判實在論，從三個本體論領域（real、actual、empirical）分析現象，透過溯因推論找出生成性因果機制，並檢視結構與能動性的互動。當使用者需要從表面相關性深入到底層原因、設計能區分機制、事件與經驗的研究，或問到「除了觀察到的模式，背後的原因是什麼」「什麼結構促成或限制了這個行為」「怎麼從相關走到因果解釋」時，就用這個 skill。" metadata: category: "WP-34 跨學科/新興" tags: ["critical-realism", "Bhaskar", "retroduction", "generative-mechanisms", "stratified-ontology", "structure-agency"] --- # Critical Realism (Bhaskar) ## Overview 批判實在論主張分層的本體論：real（不論有沒有被啟動都存在的結構與機制）、actual（機制被啟動時發生的事件）、empirical（被觀察或經驗到的事件）。研究必須超越經驗上的規律，去找出產生觀察現象的生成性機制。 ## When to Use - 從相關性的發現走向因果解釋 - 設計整合結構與能動性的混合方法研究 - 分析為什麼同一個機制在不同脈絡下會產生不同結果 - 批評實證主義或建構主義在本體論上不夠充分 ## When NOT to Use - 只需要預測，不需要理解因果 - 研究問題只關於主觀的意義建構（用詮釋主義） - 讀者要求嚴格的假設演繹方法 ## Assumptions ``` IRON LAW: Observable events (empirical) are a SUBSET of what happens (actual), which is a SUBSET of what exists (real) — research must go beyond correlations to identify underlying generative mechanisms. ``` 關鍵假設： 1. 實在獨立於我們對它的認識而存在（本體論的實在論） 2. 我們對實在的認識永遠可能出錯，而且帶有理論色彩（知識論的相對主義） 3. 有些解釋就是比其他解釋好（判斷的理性） 4. 因果是關於機制，不是恆常連結（Hume 式的規律性不夠） ## Methodology ### Step 1: Describe the Phenomenon (Empirical Domain) 記錄可觀察的模式、規律和經驗，也就是我們看到什麼在發生？ ### Step 2: Identify Events and Conditions (Actual Domain) 描繪已經發生的事件，不論有沒有被觀察到，包括脈絡條件、同時發生的事件，以及反事實的缺席。 ### Step 3: Retroduction to Mechanisms (Real Domain) 使用溯因推論：「要讓這個現象成為可能，什麼必須為真？」提出候選的生成性機制，也就是可能產生所觀察事件的結構、能力與傾向。 ### Step 4: Assess Mechanism Activation and Context 分析脈絡怎麼促成或限制機制的啟動。解釋為什麼同一個機制在不同情境下會產生不同結果（脈絡 + 機制 = 結果）。 ## Output Format ```markdown ## Critical Realist Analysis: [Context] ### Empirical Domain (Experienced) - Observed patterns: [what we see in the data] - Measurement instruments: [how we accessed these observations] - Known limitations: [what we cannot observe directly] ### Actual Domain (Events) - Events occurred: [including unobserved events inferred from evidence] - Contextual conditions: [enabling/constraining factors] - Counterfactuals: [what did NOT happen and why it matters] ### Real Domain (Mechanisms) | Mechanism | Structure/Power | Tendency | Evidence | |-----------|----------------|----------|----------| | [name] | [underlying structure] | [what it tends to produce] | [how we infer it] | ### Context-Mechanism-Outcome Configuration - Context: [specific conditions] - Mechanism activated: [which mechanism and why] - Outcome: [what was produced] ### Implications 1. [What this tells us about underlying reality] 2. [Practical interventions targeting mechanisms, not symptoms] ``` ## Gotchas - 不要把機制和變數混為一談，機制是具有因果力量的真實結構，不是統計上的預測變數 - 溯因推論不是歸納或演繹，它問的是「什麼必須存在」，而不是「我們觀察到什麼」或「邏輯上推出什麼」 - empirical 領域是最小的一層，但大多數研究卻只停在這裡 - 批判實在論是科學哲學，不是方法，它和質性、量化、混合方法都相容 - 結構與能動性在分析上是分開的，但在時間上交織在一起（形態生成循環） - 避免認識論謬誤：把存在的東西化約成我們能知道的東西 ## References - Bhaskar, R. (1975/2008). *A Realist Theory of Science*. Routledge. - Sayer, A. (2000). *Realism and Social Science*. Sage. - Archer, M. S. (1995). *Realist Social Theory: The Morphogenetic Approach*. Cambridge University Press.
英文原文
--- name: "grad-critical-realism" description: "Apply Bhaskar's critical realism to analyze phenomena through three ontological domains (real, actual, empirical), identify generative causal mechanisms via retroduction, and examine structure-agency interplay. Use this skill when the user needs to go beyond surface correlations to underlying causes, design research that distinguishes mechanisms from events from experiences, or when they ask 'what causes this beyond the observed pattern', 'what structures enable or constrain this behavior', or 'how do I move from correlation to causal explanation'." metadata: category: "WP-34 跨學科/新興" tags: ["critical-realism", "Bhaskar", "retroduction", "generative-mechanisms", "stratified-ontology", "structure-agency"] --- # Critical Realism (Bhaskar) ## Overview Critical realism posits a stratified ontology: the real (structures and mechanisms that exist whether or not they are activated), the actual (events that occur when mechanisms are activated), and the empirical (events that are observed or experienced). Research must move beyond empirical regularities to identify the generative mechanisms that produce observed phenomena. ## When to Use - Moving beyond correlational findings to causal explanation - Designing mixed-methods research that integrates structure and agency - Analyzing why the same mechanism produces different outcomes in different contexts - Critiquing positivist or constructivist approaches as ontologically insufficient ## When NOT to Use - When pure prediction without causal understanding is sufficient - When the research question is about subjective meaning-making only (use interpretivism) - When the audience requires strict hypothesis-deductive methodology ## Assumptions ``` IRON LAW: Observable events (empirical) are a SUBSET of what happens (actual), which is a SUBSET of what exists (real) — research must go beyond correlations to identify underlying generative mechanisms. ``` Key assumptions: 1. Reality exists independently of our knowledge of it (ontological realism) 2. Our knowledge of reality is always fallible and theory-laden (epistemological relativism) 3. Some explanations are better than others (judgmental rationality) 4. Causation is about mechanisms, not constant conjunctions (Humean regularity is insufficient) ## Methodology ### Step 1: Describe the Phenomenon (Empirical Domain) Document observable patterns, regularities, and experiences — what do we see happening? ### Step 2: Identify Events and Conditions (Actual Domain) Map the events that occurred whether or not they were observed, including contextual conditions, co-occurring events, and counterfactual absences. ### Step 3: Retroduction to Mechanisms (Real Domain) Use retroductive reasoning: "What must be true for this phenomenon to be possible?" Propose candidate generative mechanisms — structures, powers, and tendencies that could produce the observed events. ### Step 4: Assess Mechanism Activation and Context Analyze how context enables or constrains mechanism activation. Explain why the same mechanism produces different outcomes in different settings (context + mechanism = outcome). ## Output Format ```markdown ## Critical Realist Analysis: [Context] ### Empirical Domain (Experienced) - Observed patterns: [what we see in the data] - Measurement instruments: [how we accessed these observations] - Known limitations: [what we cannot observe directly] ### Actual Domain (Events) - Events occurred: [including unobserved events inferred from evidence] - Contextual conditions: [enabling/constraining factors] - Counterfactuals: [what did NOT happen and why it matters] ### Real Domain (Mechanisms) | Mechanism | Structure/Power | Tendency | Evidence | |-----------|----------------|----------|----------| | [name] | [underlying structure] | [what it tends to produce] | [how we infer it] | ### Context-Mechanism-Outcome Configuration - Context: [specific conditions] - Mechanism activated: [which mechanism and why] - Outcome: [what was produced] ### Implications 1. [What this tells us about underlying reality] 2. [Practical interventions targeting mechanisms, not symptoms] ``` ## Gotchas - Do NOT conflate mechanisms with variables — mechanisms are real structures with causal powers, not statistical predictors - Retroduction is not induction or deduction — it asks "what must exist" not "what do we observe" or "what follows logically" - The empirical domain is the smallest layer, yet most research stops here - Critical realism is a philosophy of science, not a method — it is compatible with qualitative, quantitative, and mixed methods - Structure and agency are analytically distinct but temporally intertwined (morphogenetic cycle) - Avoid the epistemic fallacy: reducing what exists to what we can know ## References - Bhaskar, R. (1975/2008). *A Realist Theory of Science*. Routledge. - Sayer, A. (2000). *Realism and Social Science*. Sage. - Archer, M. S. (1995). *Realist Social Theory: The Morphogenetic Approach*. Cambridge University Press.