
Grad Narrative
- 30 installs
- 223 repo stars
- Updated June 6, 2026
- asgard-ai-platform/skills
Analyzes life stories and oral histories with narrative research methods, attending to structure, temporality, and meaning-making rather than fragmenting the narrative.
About
Applies narrative research methods to study how people construct meaning and identity through the stories they tell. A researcher uses it to analyze life stories, oral histories, or transitions where temporal sequence and context are essential.
- Attends to narrative structure, content, and context as a whole
- Suited to identity construction and pivotal life-event research
Grad Narrative by the numbers
- 30 all-time installs (skills.sh)
- Ranked #1,108 of 2,064 Data Science & ML skills by installs in the Skillselion catalog
- Data as of Aug 2, 2026 (Skillselion catalog sync)
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| Installs | 30 |
|---|---|
| repo stars | ★ 223 |
| Last updated | June 6, 2026 |
| Repository | asgard-ai-platform/skills ↗ |
What it does
Analyzes life stories and oral histories with narrative research methods, attending to structure, temporality, and meaning-making rather than fragmenting the narrative.
Files
Narrative Research
Overview
Narrative research studies human experience through the stories people tell about their lives. Stories are not merely reports of events but active constructions of meaning — organizing experience temporally, assigning causality, and shaping identity. The methodology preserves the wholeness of narratives rather than fragmenting them, attending to structure (how the story is told), content (what is told), and context (why and to whom).
When to Use
- Understanding how individuals make sense of pivotal life events or transitions
- Exploring identity construction and transformation over time
- Studying how cultural, organizational, or political narratives shape experience
- When temporal sequence and context are essential to understanding the phenomenon
When NOT to Use
- When the phenomenon is not experiential or temporal (use conceptual analysis)
- When participants cannot or prefer not to narrate their experience
- When the goal is to extract discrete variables or test causal hypotheses
- When cross-sectional snapshot data is sufficient
Assumptions
IRON LAW: In narrative research, the STORY is the unit of analysis —
fragmenting narratives into coded themes destroys the temporal and
contextual meaning. If you reduce stories to thematic codes, you are
doing thematic analysis, NOT narrative research.Key assumptions: 1. Humans are storytelling beings — narrative is the primary way we organize experience 2. Stories are situated performances — shaped by audience, context, and purpose 3. Temporality is constitutive — meaning emerges from the sequence and connection of events 4. The researcher is a co-constructor of the narrative through the interview relationship
Methodology
Step 1: Elicit the Narrative
Conduct narrative interviews using a single generative question (e.g., "Tell me the story of..."). Allow the narrator to structure the telling. Avoid interrupting with probes until the main narrative is complete. Collect life stories, oral histories, or episode-specific narratives depending on the research focus.
Step 2: Analyze Narrative Structure
Examine HOW the story is told using structural elements:
| Element | Description |
|---|---|
| Abstract | What is this story about? |
| Orientation | Who, when, where, what situation? |
| Complicating action | Then what happened? (the plot) |
| Evaluation | So what? Why does this matter to the narrator? |
| Resolution | What finally happened? |
| Coda | Return to the present; moral or lesson |
(Labov's structural model; adapt as needed for non-Western narrative forms.)
Step 3: Interpret Meaning and Identity
Analyze WHAT the story conveys: turning points, character positioning, agency, causality, and moral framing. Examine how the narrator positions themselves (hero, victim, survivor, agent). Identify master narratives the story aligns with or resists.
Step 4: Contextualize and Present
Situate the narrative within broader social, cultural, and historical contexts. Present findings as re-storied narratives (Clandinin and Connelly) or analytic narratives that preserve the story's integrity while offering scholarly interpretation.
Output Format
## Narrative Analysis: [Context]
### Narrator Profile
- Pseudonym: [name]
- Context: [relevant background]
- Narrative type: [life story / episodic / oral history]
### Narrative Structure
| Structural Element | Content |
|-------------------|---------|
| Abstract | [summary of what the story is about] |
| Orientation | [setting, characters, initial situation] |
| Complicating action | [key events and turning points] |
| Evaluation | [narrator's assessment of meaning] |
| Resolution | [how events resolved] |
| Coda | [return to present, lesson drawn] |
### Identity Positioning
- Self-positioning: [how the narrator presents themselves]
- Agency: [active agent / constrained / victim / survivor]
- Master narratives: [aligned with or resisting which cultural stories]
### Temporal and Contextual Meaning
- Turning points: [pivotal moments that reorganize the narrative]
- Causality: [how the narrator explains why things happened]
- Silences: [what is notably absent from the story]
### Implications
1. [What this narrative reveals about the phenomenon]
2. [How it connects to broader social or cultural narratives]Gotchas
- Do NOT code narratives into fragments — analyze stories as wholes with internal structure
- The same events can be storied differently by the same person at different times — narratives are not fixed facts
- Researcher influence on the story is inevitable — reflexivity about co-construction is required
- Labov's model was developed for oral narratives of personal experience — it may not fit all narrative forms
- Life story research involves ethical complexity: participants may disclose more than intended in the flow of storytelling
- Distinguish between narrative analysis (story as object) and analysis of narratives (stories as data for themes) — they are different methods
References
- Clandinin, D. J., & Connelly, F. M. (2000). Narrative Inquiry: Experience and Story in Qualitative Research. Jossey-Bass.
- Riessman, C. K. (2008). Narrative Methods for the Human Sciences. Sage.
- Labov, W., & Waletzky, J. (1967). Narrative analysis: Oral versions of personal experience. In J. Helm (Ed.), Essays on the Verbal and Visual Arts (pp. 12-44). University of Washington Press.
Example: 台灣製造業自動化轉型工人的離職敘事研究
Scenario
一位博士生正在進行質性研究,主題為「工業自動化對台灣中高齡製造業工人的衝擊」。她在高雄一間電子代工廠完成了六次深度訪談,受訪者皆為 45-58 歲、曾在同一工廠任職 15 年以上、因導入 AMR 自動搬運機器人而遭到資遣的男性工人。
研究者帶著其中一份逐字稿來尋求協助:
「我訪談了阿明(化名),一位 52 歲的領班,他工作了 23 年。我錄了 87 分鐘,逐字稿有 14,000 字。我不確定要怎麼開始分析——我本來想用 NVivo 做主題編碼,但感覺把他的故事切碎很可惜。他說的方式讓我覺得很有意義,我想保留那個整體感。你能幫我分析這段敘事嗎?」
>
她附上了一段逐字稿節錄(約 600 字):
>
「我那時候是早班領班,管十六個人。機器人進來之前,我的線是整個廠效率最高的,課長說我是他最放心的人。後來機器人進來,廠長叫我們去受訓,說要『升級』。我去上了,但說實在的,那訓練就是讓我們去看怎麼被取代。我在那邊坐著,看那台機器把我做了二十三年的事情,三分鐘做完。我那時候沒有哭,但回家告訴我老婆,眼淚就掉下來了……三個月後他們說要『組織精簡』,請我簽自願離職,給了三十個月薪水。我簽了。不簽能怎樣?但我不知道我為什麼要說是『自願』的。我這輩子第一次做一件事,但我不知道那是不是我自己的決定。」
研究者的問題:「這段話怎麼用敘事研究的角度分析?他的故事結構是什麼?他在把自己定位為什麼?」
---
Analysis
確認分析框架
這是典型的個人經驗敘事(oral narrative of personal experience)——阿明正在為一個有特定時間序列(受訓 → 觀看機器運作 → 回家哭 → 三個月後資遣 → 簽字)的人生事件賦予意義。
關鍵判斷:研究者的直覺是正確的——不應用 NVivo 把這段話切碎成「情緒反應」「薪資補償」等主題碼。應使用 Labov–Waletzky 結構模型做整體敘事分析,再銜接 Riessman 的身分定位分析。
Step 1:敘事結構拆解(Labov–Waletzky)
這段 600 字節錄已包含完整的六元素結構:
| 結構元素 | 逐字稿對應內容 | 分析備註 |
|---|---|---|
| Abstract(摘要) | 隱含於整段敘事——「我被取代了,但我不知道那算不算我自己的決定」 | 阿明沒有直接說出摘要,但整段指向這個核心困惑 |
| Orientation(定向) | 「我那時候是早班領班,管十六個人……我的線是整個廠效率最高的」 | 建立了事件前的自我形象:稱職、被肯定、有位階 |
| Complicating action(情節轉折) | 「機器人進來……課長叫我們去受訓……我在那邊坐著,看那台機器把我做了二十三年的事情,三分鐘做完」 | 核心轉折點:目睹自身被替換的具身時刻,非抽象 |
| Evaluation(評估) | 「那訓練就是讓我們去看怎麼被取代」「我不知道我為什麼要說是『自願』的」 | 評估分散在全文——narrator 反覆質疑事件的意義與命名 |
| Resolution(解決) | 「我簽了。不簽能怎樣?給了三十個月薪水」 | 表面上完結,但語氣顯示這不是敘事者真正接受的結局 |
| Coda(尾聲) | 「我這輩子第一次做一件事,但我不知道那是不是我自己的決定」 | 回到敘事當下,點出道德困惑——整段故事的核心問題 |
Step 2:身分定位分析
阿明在敘事中建構了三層身分張力:
1. 過去的自我:能幹的領班,被課長信任,是組織中有價值的人("最放心的人") 2. 轉折時刻的自我:被動的目擊者,在「受訓」中觀看自己的能力被機器演示——去能化(de-skilling)的儀式性場景 3. 現在的自我:簽了字,拿了錢,但無法為這個行為命名。他拒絕接受「自願」這個標籤,但又無力提供替代詞
定位類型(Riessman):阿明不是純粹的「受害者」,也不是「倖存者」——他是無法命名自身處境的人(the unnameable actor)。這是更複雜的主體位置:有行動(簽字),但行動的意義被制度語言搶先定義。
Step 3:關鍵敘事裝置識別
- 哭泣的時間點:阿明在工廠「沒有哭」,回家告訴老婆才哭。這個情緒管理的空間分隔揭示了職場身分的展演性——在廠內維持領班的面子
- 「三分鐘」:精確的時間數字對照「二十三年」——阿明用時間比例本身作為評估工具,不需要研究者再外加詮釋
- 沉默:阿明沒有提到廠方的理由、其他同事、或自己後來做什麼。這些沉默指向值得在後續訪談中追問的空白
Step 4:主流敘事的抵抗與順從
台灣製造業轉型的主流敘事是:「升級是必然,受影響的工人應勇於再培訓、轉行」(政府政策框架)。 阿明的敘事表面順從(簽字、接受培訓),但語言上抵抗(拒絕「自願」這個詞)。這是 Riessman 所說的「反敘事」(counter-narrative)的一種形式——不是正面對抗,而是對命名權的沉默抵拒。
---
Result
## Narrative Analysis: 阿明的自動化離職敘事
### Narrator Profile
- Pseudonym: 阿明
- Context: 52 歲男性,高中職學歷,高雄電子代工廠領班,任職 23 年,2023 年 Q3 因 AMR 導入而資遣
- Narrative type: 個人經驗敘事(生命事件敘事,非完整生命史)
### Narrative Structure
| Structural Element | Content |
|-------------------|---------|
| Abstract | 我被機器取代,被要求稱之為「自願」,但我無法接受這個說法 |
| Orientation | 我是效率最高的生產線領班,受課長信任,管理十六名工人 |
| Complicating action | AMR 進廠 → 被要求參加「升級訓練」→ 親眼觀看機器三分鐘完成我 23 年的工作 → 三個月後收到資遣通知 |
| Evaluation | 那不是升級訓練,是取代儀式;「自願離職」是被強加的命名,不是我的決定 |
| Resolution | 簽署自願離職書,領取三十個月薪資 |
| Coda | 「我這輩子第一次做一件事,但我不知道那是不是我自己的決定」 |
### Identity Positioning
- Self-positioning: 從「被信任的能者」轉為「無法命名自身行動的人」
- Agency: 表面有行動(簽字),實質上是被制度語言剝奪命名權的受限主體
- Master narratives: 表面順從「轉型升級」的政策敘事,但在語言層面抵抗「自願」這一定性
### Temporal and Contextual Meaning
- Turning points: 觀看機器運作的具身時刻——不是資遣通知,而是「看見自己被三分鐘取代」
- Causality: Narrator 不使用個人能力不足解釋,而是將原因歸結於結構性替換(機器進來)
- Silences: 沒有提及廠方正式說明理由、其他工友的反應、或離職後的生活安排——需後續訪談追問
### Implications
1. 自動化資遣的傷害不僅是失業,而是對工人命名自身經驗之能力的剝奪——「自願」這個詞成為二次傷害
2. 阿明的敘事結構揭示:政策語言(升級、自願、轉型)與工人的具身經驗之間存在根本性的命名衝突,這個衝突值得作為研究的核心發現,而非背景雜訊研究者下一步行動建議:
- 在第二次訪談中以「你說你不知道那算不算你自己的決定——可以多說一點嗎?」作為 narrative prompt,追蹤沉默地帶
- 跨六份訪談比較各 narrator 如何處理「自願離職書」這個敘事節點——這可能是本研究的核心比較分析單位
- 注意:不要把六份逐字稿混合後做主題編碼。每個敘事應先完整分析,再做跨敘事比較