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Record W4289532002 · doi:10.1215/22011919-9712467

Boreal Plants That Enchant

2022· article· en· W4289532002 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Humanities · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsAthabasca University
Fundersnot available
KeywordsEthnographyIndigenousValue (mathematics)Environmental ethicsGeographySociologyEcologyEthnologyArchaeologyBiologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract This article describes moments of plant-induced enchantment during community-based environmental monitoring and ethnographic research in Treaty No. 8 sakâwiyiniwak territories. These multispecies ethnographic encounters while collaborating with Elders and friends from Fort McKay First Nation and Bigstone Cree Nation describe how sakâwiyiniwak ecological care is rooted in kinship. Moments of enchantment, or intense moments of noticing and “plant-thinking,” inspire new appreciation of the boreal forest and the many familiar plants that grow within it, illuminating the magic of muskeg tea, frog’s pants, and aspen. Written in the style of lively ethnography, this article focuses on plants of sakâwiyiniwak ceremonial, nutritional, and medicinal use. These plants are often overlooked or are described as nuisance weeds, despite being indigenous plants, by settlers whose decisions and natural resource extraction activities have a direct effect on the survival and well-being of these plants and larger ecosystems. Enchantment brings attention to the deep-seated settler biases against certain types of plants that are common or abundant or, more specifically, not of current commercial value.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.000

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.

Opus teacher head0.038
GPT teacher head0.262
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it