Sustained by First Nations: European newcomers' use of Indigenous plant foods in temperate North America
Bibliographic record
Abstract
Indigenous Peoples of North America have collectively used approximately 1800 different native species of plants, algae, lichens and fungi as food. When European explorers, traders and settlers arrived on the continent, these native foods, often identified and offered by Indigenous hosts, gave them sustenance and in some cases saved them from starvation. Over the years, some of these species – particularly various types of berries, such as blueberries and cranberries (Vaccinium spp.), wild raspberries and blackberries (Rubus spp.), and wild strawberries (Fragaria spp.), and various types of nuts (Corylus spp., Carya spp., Juglans spp., Pinus spp.), along with wild-rice (Zizania spp.) and maple syrup (from Acer saccharum) – became more widely adopted and remain in use to the present day. Some of these and some other species were used in plant breeding programs, as germplasm for hybridization programs, or to strengthen a crop's resistance to disease. At the same time, many nutritious Indigenous foods fell out of use among Indigenous Peoples themselves, and along with their lessened use came a loss of associated knowledge and cultural identity. Today, for a variety of reasons, from improving people's health and regaining their cultural heritage, to enhancing dietary diversity and enjoyment of diverse foods, some of the species that have dwindled in their use have been “rediscovered” by Indigenous and non-Indigenous Peoples, and indications are that their benefits to humanity will continue into the future.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".