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Record W1850352686 · doi:10.5539/ass.v11n18p1

Enhancing Capacity Building in Seaweed Cultivation System among the Poor Fishermen: A Case Study in Sabah, East Malaysia

2015· article· en· W1850352686 on OpenAlexvenueno aff
Rosazman Hussin, Suhaimi Md Yasir, Velan Kunjuraman, Aisah Hossin

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Government (linguistics)BusinessCapacity buildingEstateEnvironmental planningEconomic growthGeography

Abstract

fetched live from OpenAlex

Community development issues in the context of sustainable development has been given serious attention fromall parties namely government and private sectors. In this case study, a member of the community who wants tosucceed in their life through development programmes should have positive attitude and take steps to developthemselves, while being supported by the government. This paper discusses the establishment of capacitybuilding programmes among a poor rural community. The main objective of these programmes is to enhance thesocio-economic status of the community through seaweed cultivation. Based on this, capacity buildingprogrammes were conducted for enhancing the level of community participation and high skills for the long termin the process of modern sustainable seaweed cultivation. The study was conducted between 2011 and 2013.Interviews were carried out with local fishermen and data were analysed using qualitative analyses techniques.The findings revealed that, the introduction of seaweed cultivation using the Estate Mini System and ClusterSystem under the initiative by the Department of Fisheries Sabah exposed the community to new technologiessuch as using varieties of seeds, seeds and nursery management, fertilizing and tying of seeds, the activity ofsolar drying and using the casino table technique in the process of seaweed cultivation. The study is significantfor the fishermen experiencing the process of lifelong learning and who can enhance their knowledge andsurvival skills in their respective fields of employment. Moreover, capacity building programmes could changethe mind-set of the community to be more open and receive the new approaches in the production of seaweedcultivation.

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)0.002
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 score0.240
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.243
Teacher spread0.223 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

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