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Record W3212344483 · doi:10.1111/aman.13658

Adopting a Root: Documenting Ecological and Cultural Signatures of Plant Translocations in Northwestern North America

2021· article· en· W3212344483 on OpenAlexaff
Nancy J. Turner, Chelsey Geralda Armstrong, Dana Lepofsky

Bibliographic record

VenueAmerican Anthropologist · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsSimon Fraser UniversityUniversity of Victoria
Fundersnot available
KeywordsIndigenousTraditional knowledgeEcologyGeographyEthnobotanyHistoryEthnologyEnvironmental ethicsBiologyMedicinal plants

Abstract

fetched live from OpenAlex

ABSTRACT In recent years, there has been an increasing recognition of the role humans play in the structure, composition, and function of ecosystems. Ethnoecological documentation of traditional management systems of Indigenous Peoples in northwestern North America has contributed significantly to this rethinking. A less well‐recognized but foundational part of traditional management of this region is the practice of transplanting plants and plant propagules to expand the range and accessibility of culturally valued plants. In part, the lack of recognition of such translocations has to do with difficulties in identifying evidence of such actions from the past. Here, we summarize various lines of evidence, including that from ethnographic and ethnohistoric records, languages, oral traditions, phytogeography, and archaeology, to document the widespread and long‐standing extent of plant translocation practices among Indigenous Peoples of northwestern North America. Furthermore, we demonstrate how such practices have helped shape contemporary native plant communities throughout the region. Recognizing these past contributions to current ecological contexts honors Indigenous heritage and Indigenous Peoples’ long‐term relationships with their biological worlds. [ translocation, transplanting, ethnobotany, traditional resource management, northwestern North America ]

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 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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2021
Admission routes1
Has abstractyes

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