Bibliographic record
Abstract
We use an interactive website and ethnographic film to contextualize the history of the commodification of insects as traditional food, natural dye, and trendy tourist fare in Oaxaca, Mexico. We are a three-person interdisciplinary team of amateur filmmakers, consisting of anthropology faculty, undergraduate student and alumna, who met through our work with our institution’s Digital Humanities Institute. We incorporate photography, film, and archival research to explore insect uses and imaginaries which take many forms in Oaxaca, a state boasting the greatest cultural, linguistic, and biological diversity in Mexico. This presentation describes research-driven visual methods examining current political economies surrounding the commodification of insects. Pfister’s research uses anthropological and humanistic approaches to explore Oaxaca’s rich cultural and culinary history and contrast it with colonial and EuroAmerican ambivalence toward insects. Our multimedias explore various ways that globalized and climatic changes impact our participants economically, socially, and ecologically, and how their lived experiences might be representative of broader post-colonial tensions and realities (Pfister and Gaytán 2024). Papernest is an interactive website, hosting a gallery of images, film clips and ideas related to human-insect relationships. We use images and participatory methods to engender resonances and contradictions between long-standing traditions and newly-emerging narratives surrounding insects – these reactions range from shock and disgust, to energies toward “rediscovery” of trendy Mexican “super foods” (Katz and Lazos 2016) and natural dyes with longstanding cultural significance in Oaxaca. Project accessible at https://papernest.domains.unf.edu/.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.907 | 0.801 |
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".