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Record W1756841019 · doi:10.1139/cjfr-2012-0514

Cultural importance of white pine (<i>Pinus strobus</i>L.) to the Kitcisakik Algonquin community of western Quebec, Canada

2013· article· en· W1756841019 on OpenAlexaffvenueabout
Yadav Uprety, Hugo Asselin, Yves Bergeron

Bibliographic record

VenueCanadian Journal of Forest Research · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
Fundersnot available
KeywordsWhite (mutation)GeographyKeystone speciesWildlifeEcologyHabitatForest managementAgroforestryForestryBiology

Abstract

fetched live from OpenAlex

Trees and forests have always played a significant role in the cultural and spiritual lives of societies. Understanding the cultural importance of tree species is necessary to develop socially acceptable forest management and restoration strategies. White pine (Pinus strobus L.) used to be abundant in northeastern North America, including on the ancestral territory of the Kitcisakik Algonquin community (western Quebec, Canada). The community is calling for restoration and sustainable management of white pine on their ancestral territory. As a first step towards this goal, key informant interviews were used to document the cultural importance of white pine to the Kitcisakik community. White pine was perceived as an important component of traditional life, providing several goods and services. White pine is featured in legends, is used as a medicine, provides habitat for flagship wildlife species, and is a prominent part of cultural landscapes. White pine is a cultural keystone species for the Kitcisakik Algonquin community. Local people point to extensive logging as the reason behind white pine decline on the ancestral territory. They suggest that mixed plantations should be used in a culturally adapted restoration strategy.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.002
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.269
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations45
Published2013
Admission routes3
Has abstractyes

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