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Record W2122552040 · doi:10.1080/08920750903194165

Challenges and Prospects of Fisheries Co-Management under a Marine Extractive Reserve Framework in Northeastern Brazil

2009· article· en· W2122552040 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCoastal Management · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarine protected areaFisheryMarine reservePatienceResource (disambiguation)Nature reserveScale (ratio)Fisheries managementGeographyCoral reefFishingArchaeologyEcologyHabitatCartography

Abstract

fetched live from OpenAlex

Abstract In Brazil, Marine Extractive Reserves—MERs (Reservas Extrativistas Marinhas) represent the most significant government-supported effort to protect the common property resources upon which traditional small-scale fishers depend. From an initial small-scale experience in 1992, MERs have expanded countrywide, now encompassing 30 units (9,700 km2) and nearly 60,000 fishers. Despite such escalating interest in the model, there is little research on the effectiveness of MERs. In this article, we discuss relevant parts of the history and examine the current situation of the fisheries co-management initiative in the Marine Extractive Reserve of Corumbau, which was created in 2000 as the first MER to encompass coral reefs and reef fisheries. We describe the Extractive Reserve co-management arrangement and its main policy and legislative challenges. Finally, we discuss the prospects for the use of MERs as management frameworks for traditional small-scale fisheries in Brazil. Keywords: co-managementCorumbauextractive reservefisheriesprotected areas Acknowledgments We deeply acknowledge all fisherfolk from the MERC for their patience and collaboration. We thank Grazyela Fiuza-Lima, Juliane Cebola, Matheus Freitas, Mariana Neves, Aneilton Carmo, Ronaldo Lobão, Cristiana Seixas, Michael Orbach, Ratana Chuenpagdee, Danilo Araújo, Renata Melão, Tuca Monteiro, Fernanda Stori, Tiago Bucci, Alexandre Cordeiro, Albino Neves, José Conceição, John Cordell, Ademi Januário, Les Kaufman, Luis Fernando Brutto, Luis Paulo Pinto, Paulo Prado, and Carlos Hortêncio for help in the field and/or valuable discussions and insights. Funding was provided by the Fundo Nacional do Meio Ambiente, Secretaria Especial de Aqüicultura e Pesca, Ministério do Desenvolvimento Agrário, International Conservation Fund of Canada, Sagatiba, Betty and Gordon Moore Foundation, Fundação de Amparo à Pesquisa do Estado de São Paulo, and Conselho Nacional de Desenvolvimento Científico e Tecnológico. This is contribution number 10 of Conservation International's Marine Management Areas Science Program, Abrolhos Node. Notes 1. FNMA approved a US$400,000.00 budget in 2003, but to date less than half of this money has reached the project.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.633

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 science0.0000.001
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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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