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Record W4385065151 · doi:10.1007/s10745-023-00427-8

Untangling Biocultural and Socioeconomical Drivers of African Plum Tree (Dacryodes edulis) Local Nomenclature Along a Rural-Urban Gradient in Central Cameroon

2023· article· en· W4385065151 on OpenAlexfundno aff
Taïna Lemoine, Aurore Rimlinger, Jérôme Duminil, Christian Leclerc, Vanesse Labeyrie, Mélanie Tsogo, Stéphanie M. Carrière

Bibliographic record

VenueHuman Ecology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
FundersUniversité de LausanneAgence Universitaire de la FrancophonieAgence Nationale de la RechercheAgropolis Fondation
KeywordsGeographyEthnic groupDiversity (politics)NomenclatureUrbanizationTasteDomesticationConsumption (sociology)SocioeconomicsEcologyBiologySociologySocial scienceAnthropologyTaxonomy (biology)

Abstract

fetched live from OpenAlex

Abstract In Cameroon, the African plum tree ( Dacryodes edulis [G. Don] H. J. Lam) is widely cultivated for its fruits, which contribute significantly to household food security and economy. In order to analyze the links between the social and ecological systems that result in the remarkable fruit diversity, we focused on how the important varietal diversity of African plums was perceived and named by tree owners. We conducted semi‑structured interviews in Center-Cameroon with 142 people belonging to the Beti ethnic group, in urban (Yaoundé), peri-urban and rural areas, and analyzed the data qualitatively and quantitatively. Along this urbanization gradient linking production to consumption regions, 158 different translated names were recorded. Most names (80%) were cited once, but some names based on fruit size and taste were common across the gradient. Although the highest total number of names was recorded in the rural site, many different names were also found along the urban–rural gradient. We did not detect difference in the number of named African plums between respondents with different characteristics. The local classification of African plums among the Beti was structured predominantly according to morphological and organoleptic criteria, but also to symbolic and practical criteria. African plums’ names were based on people’s fruit preferences, that favor large, oily, and blue to black fruits, and disregard pink-colored watery plums. This study is an entry point to explore the rising trade and thus ongoing domestication of the African plum tree from an often neglected perspective, that of local nomenclature.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.975

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 studies0.0000.001
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 head0.013
GPT teacher head0.211
Teacher spread0.197 · 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.

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

Citations5
Published2023
Admission routes1
Has abstractyes

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