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Record W3082249711 · doi:10.3390/su12177120

The Practice of Co-Production through Biocultural Design: A Case Study among the Bribri People of Costa Rica and Panama

2020· article· en· W3082249711 on OpenAlexafffund
Mariana Rodríguez

Bibliographic record

VenueSustainability · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCocoa and Sweet Potato Agronomy
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsLivelihoodProduction (economics)SustainabilityCo-creationValue (mathematics)Process (computing)SociologyTraditional knowledgeIntangible cultural heritageCultural heritageKnowledge managementBusinessGeographyIndigenousMarketingAgricultureEcologyComputer scienceEconomics

Abstract

fetched live from OpenAlex

Research in co-production has given rise to a rich scientific literature in sustainability science. The processes by which co-production occurs are not well documented. Here, I present my work with the Bribri people to undertake a biocultural design project. Biocultural design is a process that begins with understanding participants’ aspirations to support their livelihoods. The process is collaborative, imagining ideas and executing products and services by drawing upon the capabilities of the participant’s biocultural heritage. In the Bribri territory, the biocultural heritage associated with cacao agroforestry systems is considered significant for Bribri livelihoods. Bribri people’s aspirations to grow cacao go beyond increasing cacao yields and include the respect for cultural teachings and social relationships. The participants of this project designed cacao value-added products (e.g., cacao jam, cacao butter) and services (e.g., showcase farm) by identifying viable ways to execute their ideas. Biocultural design offers a guide to co-imagine and co-execute ideas to solve specific problems and contributes to the practice of co-production by offering an approach that recognizes the value of science, while respecting the knowledge, aspirations and values of other actors.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.327
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.025
GPT teacher head0.278
Teacher spread0.253 · 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

Labeled directly by 2 models reading the full record.

Science and technology studies

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

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

Citations6
Published2020
Admission routes2
Has abstractyes

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