Library Considerations for the Colonial Impacts of Indigenous Cookbook Publishing
Bibliographic record
Abstract
According to Natifs (North American Traditional Indigenous Food Systems), the first action in understanding the Foundations of an Indigenous Food System Model is the “Removal of Colonized Thought.” food sovereignty, physical and spiritual connection to land, and sustainable food practices are interlocked with decolonial action. Considering Traditional Knowledge (TK), as intellectual property, what does it mean for libraries to collect books containing TK, such as cookbooks written by Indigenous authors, published by Indigenous publishers or otherwise dealing with Indigenous Food Systems? Mindful of the colonial impacts on cookbook publishing in Canada, the author proposes a 4-part framework for libraries when acquiring or weeding Indigenous cookbooks to and from their collections. Used as a tool, the framework promotes the stewardship of collections (and metadata) that do not perpetuate colonial violence through language and Eurocentrism, but champion Indigenous authors, publishers, and content. Written from the position of queer-settler, the essay provides examples of published works that meet the criteria of the framework, celebrating Indigenous Food Systems that predate librarianship’s colonial classification. Through personal narrative, the author demonstrates how the offerings of such texts can become integrated into a personal stewardship of the teachings being shared that directly informs the case for equitable collections management.
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 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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.033 | 0.016 |
| Scholarly communication | 0.041 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".