People and Plants in Nunatsiavut (Labrador, Canada): Examining Plants as a Foundational Aspect of Culture in the Subarctic
Bibliographic record
Abstract
This paper emphasizes the cultural value of plants in Nunatsiavut (Labrador, Canada), a self-governing Inuit region in the Subarctic. Via interviews with community members, we describe the links between plant usage and culture to understand the direct ways that plants are utilized for food, construction, gardening, and medicine, and to then link these uses to deeper cultural significance among three communities in Nunatsiavut (Hopedale, Postville, and Rigolet). Many plants were common amongst communities with a total of 66 taxa identified. About 75% of taxa were reported in at least two communities, corresponding to 95% of all responses. Edible plants were the most common reported usage, with emphasis on berry-producing taxa such as blueberry shrubs. Our study shows that a diversity of plants (i) support cultural activities; (ii) act as markers for historical events; (iii) highlight intergenerational exchange and valuing of plant knowledge; (iv) express the deep awareness that people have for their local environment; and (v) a medium for the expression of traditional values. The similarities in the plant responses among the communities suggest a shared body of plant knowledge. Our study supports the great cultural importance of plants in northern communities. Supplementary Information: The online version contains supplementary material available at 10.1007/s12231-021-09530-7.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".