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Record W3175563944 · doi:10.1002/pan3.10235

Traditional food or biocultural threat? Concerns about the use of tilapia fish in Indigenous cuisine in the Amazonia of Ecuador

2021· article· en· W3175563944 on OpenAlexaff
Verónica Santafe-Troncoso, Philip A. Loring

Bibliographic record

VenuePeople and Nature · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversity of GuelphUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousTilapiaPromotion (chess)EthnobiologyAmazon rainforestTourismOreochromisBushmeatGeographyTraditional knowledgeQualitative researchEnvironmental planningSociologyFisheryEnvironmental resource managementPolitical scienceFish <Actinopterygii>EcologySocial scienceWildlifeBiologyAnthropology

Abstract

fetched live from OpenAlex

Abstract This article contributes to streams of knowledge related to biocultural diversity, food tourism and the cultural impacts of introduced species. Specifically, it explores the concerns that arise from the promotion of tilapia fish Oreochromis niloticus in Indigenous cuisine along a touristic route in the Amazon region of Ecuador. Although the environmental impacts of tilapia in the Amazon ecosystem have been largely documented, reports of cultural impacts are still scarce. This research addresses this gap by applying a biocultural approach, which provides a more systemic and pluralistic view of this introduced species in the local food systems of this region. This qualitative research used semi‐structured interviews, observations, a workshop and the analysis of restaurant menus to understand the complexity of the tilapia issue in this case. The results report the factors influencing the promotion of tilapia fish as traditional food, how locals perceive this promotion and its impacts on local culture and biocultural conservation, and locals’ proposals to mitigate these impacts. The discussion section uses a biocultural ethics approach to analyse these results. We focus on stakeholders' perspectives and actions to address the tilapia issue in their region while navigating their multiple ways of valuing their human–environment relations and adapting to uncertain scenarios.

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 score0.413
Threshold uncertainty score0.970

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 studies0.0000.000
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 head0.052
GPT teacher head0.244
Teacher spread0.192 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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