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Record W2162297818 · doi:10.5539/jas.v3n4p233

Constraints to Integrated and Non – Integrated Fish Farming Activities in Ogun State, Nigeria

2011· article· en· W2162297818 on OpenAlex
B. G. Abiona, E. O. Fakoya, W.O. Alegbeleye, E.O. Fapojuwo, Stephen Oluseun Adeogun, AB Aromolaran

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.

venuePublished in a venue whose home country is Canada.
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

VenueJournal of Agricultural Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFisheries and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFish farmingAgricultureOgun stateAgricultural sciencePearson product-moment correlation coefficientFish <Actinopterygii>GeographyMathematicsStatisticsFisheryBiologyAquaculture

Abstract

fetched live from OpenAlex

The study examined constraints to integrated and non- integrated fish farming activities in Ogun State, Nigeria. Random sampling techniques was used to select 133 non - integrated fish farmers (NIFF) and 216 integrated fish farmers (IFF) (n = 349) from the study area. Data were analysed using chi-square and Pearson Product moment correlation. Results showed that 92.5% of NIFF was male compared to IFF (90.7%). Also, 96.8% of IFF and 79.7% of NIFF were married. The mean ages of sampled farmers were 44 years (NIFF) and 46 years (IFF) while the mean fish farming experiences were 4 years (NIFF) and 5 years (IFF). However, respondents’ major constraints to fish farming were exploitation by middlemen (88.9%), price fluctuation (92.8%), inadequate capital (87.9%) and epileptic power supply (77.4%). The chi-square analyses showed that knowledge of fish farming had significant association with respondents sex (?2 = 9.44, df = 2, p = 0.00), occupation (?2 = 25.5, df = 8, p = 0.01), Pearson correlation analyses showed significant relationship between farmers knowledge and age (r = 0.20, p = 0.00), fish farming experience (r = 0.17, p = 0.00), level of cosmopoliteness (r = 0.16, p = 0.00) and production constraints (r = -0.00, p = 0.00).

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 score0.909
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.211
Teacher spread0.194 · 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