Ethnographic Film and Video on Hybrid Television
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
Academic ethnographers have been utilizing film, and more recently video, for a variety of research purposes including the collection, analysis, and dissemination of data. But ethnographic film and video are not the exclusive domain of university-based ethnographers or professionally trained ethnographic researchers. More and more ethnographic films and video documentaries are nowadays produced by filmmakers who aren’t necessarily interested in utilizing their work to advance anthropological, sociological, or other disciplines’ theoretical or substantive agendas. Interestingly, these documentaries often garner wider distribution and larger audiences than ethnographic films and videos made by academics, leading us to question the identity of ethnographic documentary and the potential of this genre to both advance ethnological knowledge and the sociocultural imagination. In this article, I examine this phenomenon focusing on nonacademic wide-distribution ethnographic documentaries available on cable and satellite TV, Netflix, and iTunes, reflecting on their content, style, distribution strategies, and their status as social scientific ethnographic representations.
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 | 0.017 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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