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Record W2902238812 · doi:10.5539/jsd.v11n6p259

Certified Organic Farming: Awareness of Export Oriented Small-Scale Farmers in Sri Lanka

2018· article· en· W2902238812 on OpenAlexvenueno aff
S. M. C. B. Karalliyadda, Tsuji Kazunari

Bibliographic record

VenueJournal of Sustainable Development · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationBusinessMarketingOrganic certificationGovernment (linguistics)Scale (ratio)Descriptive statisticsGeneral partnershipOrganic farmingContract farmingAgricultureAgricultural scienceProduction (economics)EconomicsFinanceManagement

Abstract

fetched live from OpenAlex

This study aimed at investigating Sri Lankan small-scale Certified organic (CO) farmers’ awareness on their adopted organic standards, the third-party certification body, internal control system, Fairtrade certification, and conditions of contracts with coordinating organizations. A cross sectional survey was conducted among a randomly selected sample of 202 CO farmers who were linked with five coordinating organizations. Primary data was collected using a structured questionnaire along with key informant discussions and field observations. Data were analyzed using descriptive statistics to generate simple summaries and tendencies. According to the results, CO farmers are organized as farmer organizations that were initiated as out-grower groups of coordinating organizations. All CO farmers were unaware of the adopted organic standard. The majority were unaware of the third-party certification body (83%), and the internal control system (81.7%). This perhaps due to their exclusion in managing certification related aspects. Thus, showed submissive decision-making behavior. However, many of them were aware of Fairtrade certification (56.4%) as it provides a wide spectrum of additional benefits covering production, marketing, and farmers’ welfare. Farmers were also aware of their contracts (verbal or written) with coordinating firms (62.2%) but hardly conscious of their conditions. In some contracts, conditions were unfairly distributed among stakeholders. Therefore, the study recommends enhancing small-scale farmers knowledge not only the production aspects but also certification, quality assurance, administration, and marketing as well. Meanwhile, mediating the partnership among stakeholders by a government body is also recommended to avoid power abuses among stakeholders.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.255
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

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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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