Our Journey to Becoming Ethnographers: An Exploration of Rhetorical Structures as Lived Experience
Bibliographic record
Abstract
This article, originally written as a performative piece, presents the experiences and perceptions of five graduate students and one professor as they reflect on and write about becoming ethnographers throughout a graduate-level research course. Data sources include reflective journals, synthesis papers, and academic literature. Following the completion of the course, the group came together and applied grounded theory to analyze the data and write collectively about their experiences, feelings, and insights on ethnographic work. They present the data as a readers theatre that incorporates portions of a children's book with the group's reflections. Like authors of other academic literature the group discusses the challenges and benefits of ethnographic research. Their collaborative writing reflects their polyvocality as they negotiated their journeys toward becoming ethnographers.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.016 | 0.032 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".