Breathing in the Mud: Tensions in Narrative Interviewing
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
This article explores important questions around the often taken for granted approach to interviewing within narrative inquiry. When I applied an interview approach that emphasized the dialogical, performative, and social, tensions were provoked that muddied my assumptions and equilibrium. By sharing my story, I invite readers to reflect upon the researcher's role in interviewing. I address tensions that arose between (a) presence and performance, (b) equality and power, (c) leading and following, (d) insider and outsider, (e) influence and neutrality, and (f) trust and responsibility. I come to describe the craft of co-constructing stories with another as breathing in the mud—a dynamic process in which the researcher moves between the tensions of getting stuck in one moment and finding brilliant presence in the next. Discussion focuses on how a researcher might use tensions as catalysts that ignite clarity and advance how narrative interviewing is enacted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.133 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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