Episodic Narrative Interview: Capturing Stories of Experience With a Methods Fusion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Episodic narrative interview is an innovative, phenomenon-driven research method that was developed by integrating elements from several qualitative approaches in a methods fusion. Episodic narrative interview draws on critically oriented theoretical foundations and principles of experience-centered narrative and includes features from narrative inquiry, semistructured interview, and episodic interview. The purpose of episodic narrative interview is to better understand a phenomenon by generating individual stories of experience about that phenomenon. As such, an episodic narrative interview participant provides nested narrative accounts of their experiences with a social phenomenon, within the context of a bounded situation or episode. In this article, the author details the foundations of the episodic narrative interview approach and describes how the method is designed and implemented. The significance of episodic narrative interview is also explored, especially in terms of the ways in which it produces tightly focused, phenomenon-centered narratives that are reflective of particular bounded circumstances.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it