The ethnographic B movie: Centering the uncertain, absurd and low quality in collaborative filmmaking
Bibliographic record
Abstract
This paper discusses an experimental modality of ethnographic filmmaking that my interlocutor/collaborator and I came to call the ‘ethnographic B movie’. I explore what I mean by the term and describe its use as novel approach to collaborative multimodal research. I argue that this approach – which encourages unprofessionalism, low quality, absurdity and caprice – provides an opportunity to centre research contexts, ontologies and epistemologies on the fringes or margins of conventional anthropological content, thought and context. Through situating the approach within ideas of arts-based research or research-creation the ethnographic B movie becomes a way to take the process of filmmaking as ethnography for the sake of an open and co-imaginative world. In the ethnographic B movie as filmic approach and representational frame, communicable meaning and narrative coherence are substituted for the spirit of co-creation, and interlocutor-driven content.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".