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Record W2898651751 · doi:10.24043/isj.372

Sustainable development? Salmon aquaculture and late modernity in the archipelago of Chiloé, Chile

2016· article· en· W2898651751 on OpenAlexaffvenue
Jonathan R. Barton, Álvaro Román

Bibliographic record

VenueIsland Studies Journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsUniversity of Prince Edward Island
FundersFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasComisión Nacional de Investigación Científica y Tecnológica
KeywordsLivelihoodArchipelagoModernityPovertySustainabilityAquaculturePopulationDevelopment economicsGeographyEconomic growthPolitical scienceFisheryEconomicsSociologyEcologyBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Chiloé is an archipelago that has, since the 1980s, become one of the motors of the Chilean economy. Salmon aquaculture swiftly transformed the tradition of isolation and poverty that had defined the local identity and livelihoods. This is now changing due to the rapid experience of modernity. This modernity is driven by transnational capital and largescale state intervention in the promotion of salmon aquaculture and its current central role in defining development in the islands. While this sector has generated private and public employment and infrastructure, there has also been an important shift in the expectations and aspirations of the local population, towards increased hybridization and also a mercantilization of island culture. The success of salmon production reveals that the conditions of isolation can be transformed, and even benefits reaped from integration into the modern world–globalised, capitalist and rational, rather than traditional– however it also entails risks for the sustainability of fragile socio-ecological systems, including the existence of traditional and alternative livelihoods.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.295
Teacher spread0.268 · 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

Citations39
Published2016
Admission routes2
Has abstractyes

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