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Record W4312757857 · doi:10.5751/es-13539-270446

Old trees, sprouts, and seeds of the cloud forest: the voices of the campesinos

2022· article· en· W4312757857 on OpenAlexvenueno aff
Raquel Romero Puentes, Manuel Rodríguez

Bibliographic record

VenueEcology and Society · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsCloud forestThreatened speciesBiodiversityGeographyEcosystem servicesAgroforestryEcosystemAmazon rainforestEcologyEnvironmental scienceBiologyMontane ecology

Abstract

fetched live from OpenAlex

The purpose of this study was to address the relationship between campesinos and nature. Using a case study in the Tropical Andes, we focused on the relationships between elders, adults, and children and the cloud forest. Tropical montane cloud forests (TMCFs) are among the most diverse and most threatened ecosystems worldwide. They offer a vast number of ecosystem services to society at local, regional, and global scales. Some of these ecosystem services and the relationships between the TMCF and campesinos were studied in the rural community of Sion in Colombia’s Eastern Andes. Sion’s campesinos have built traditional ecological knowledge about TMCF and its benefits; however, this knowledge is being lost along with TMCF biodiversity. The campesinos, especially the elders, know that ecosystem services flow has changed over time and perceive reduced water and wood provision, as well as a reduction in the quantity of medicinal plants, flora, and fauna. The relationships between the forest and the people of Sion are not unidirectional; they are relations of coexistence and reciprocity, as reflected in the participants’ narratives. To help maintain biodiversity, Sion’s campesinos plant native species close to their homes and voluntarily help to conserve TMCF areas. These practices reflect people’s identity and rootedness to the forest and to the village. Efforts toward TMCF conservation, such as restoration and designation of protected areas, should include the conservation of both biological and cultural diversity.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.005
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.169
Teacher spread0.163 · 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 designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

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