Living community cookbook: transdisciplinary collaboration for constructing recipes with biocultural value
Bibliographic record
Abstract
This research aims to delve into food knowledge and practices concerning the ecological management of food resources, spanning procurement, transformation, and consumption processes, through the lens of creating a cookbook as a tool for decolonizing food knowledge and practices. The impetus for crafting a cookbook alongside an indigenous community in northwestern Mexico stems from the dynamic process of exchanging ecological and food knowledge, where the following questions are posed: What foundational knowledge and essential ingredients underlie the community's food system? And how might the cookbook serve as a catalyst for knowledge exchange and transdisciplinary collaboration? Adopting a qualitative approach, the research employs participatory methodology, involving workshops with women from the Kumiai community of San José de la Zorra, Baja California, Mexico. These workshops aim to spotlight the diversity of foods sourced from the collection of wild species/seasonal crops and to glean insights into the perspectives on food culture from the region. As a result, the study unveils ingredients cultivated and gathered across different seasons, offering a glimpse into the community’s rich food knowledge. A design proposal is articulated to craft recipes that not only respect the essence of the community’s way of life but also resonate with the profound connection people have to the territory. Moreover, the research delves into the significance of decolonizing cookbooks by amplifying indigenous food knowledge and reclaiming narratives from a biocultural perspective. The cookbook emerges as a tool for igniting dialogue about food in relation with the social-ecological context of indigenous and rural communities in northwestern Mexico. Furthermore, it proposes that this model can be adapted to other contexts, needs, and preferences, thereby effectively linking food and territory while challenging dominant culinary narratives.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".