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Record W2791206757 · doi:10.24901/rehs.v39i153.392

A medio siglo de manejo pesquero en el noroeste de México, el futuro de la pesca como sistema socioecológico

2018· article· es· W2791206757 on OpenAlexaff
Andrés M. Cisneros‐Montemayor, Miguel Ángel Cisneros‐Mata

Bibliographic record

VenueRelaciones Estudios de Historia y Sociedad · 2018
Typearticle
Languagees
FieldEnvironmental Science
TopicEnvironmental and Cultural Studies in Latin America and Beyond
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyPhilosophy

Abstract

fetched live from OpenAlex

El manejo pesquero en el noroeste de México debe reconocer plenamente a la pesca como parte de un sistema socio-ecológico. Este estudio describe la evolución y situación del manejo, incluyendo la dinámica entre instituciones de manejo y organizaciones conservacionistas, resaltando oportunidades y retos para alcanzar la sustentabilidad ecológica y social. En este contexto, el reconocimiento de la pesca artesanal como actividad social además de económica, facilitaría la evolución de los esquemas de gobernanza y manejo para empatarlos con los objetivos sociales. Ello permite abordar de lleno temas de suma importancia, incluyendo los retos de las comunidades pesqueras indígenas, o los impactos anticipados del cambio climático. El conocimiento científico y la experiencia acumulados en cinco décadas representan una gran capacidad para desarrollar estrategias novedosas para transitar hacia la sustentabilidad del sistema. El éxito de este proceso dependerá de la habilidad de consolidar una visión unificada sobre los beneficios deseados, en especial para las comunidades pesqueras.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.262
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2018
Admission routes1
Has abstractyes

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