Collecting Sensorial Litter: Ethnographic Reflexive Grappling With Corporeal Complexity
Bibliographic record
Abstract
In this three-part narrative paper, I put forward “collecting sensorial litter” as an innovative method for helping ethnographers reflexively grapple with complicated corporeality during fieldwork. First, I highlight the continued need for experimentation with body-based reflexive methods that can help capture the messiness of ethnographers’ experiences, especially for sensuous, embodied forms of ethnography. Second, I use theories of intensity and embodiment to conceptualize the “too intense experiences” that are refuse/d by ethnographers’ bodies (e.g., fleeting, whirling emotions; spatial disorientations). Third, I draw upon my fieldwork to illustrate that such experiences are not lost when refuse/d, but manifest symbolically and materially as “sensorial litter.” I detail my methodological process for: A) identifying B) re-claiming and C) reflexively considering three pieces of sensorial litter. I argue the value of collecting sensorial litter includes enhancing self-communication, attending to uncomfortable power relations, and rendering visible critical data (perhaps) inadvertently thrown away in research.
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 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 | 0.046 | 0.016 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".