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Socio-Economic Factors Influencing Farmers’ Participation in Community Development Organizations in Obubra Local Government Area of Cross River State, Nigeria

2012· article· en· W1835327514 on OpenAlexvenueno aff
Augustine O. Angba, Paul Itari

Bibliographic record

VenueCanadian social science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsDistrustClanBusinessState (computer science)Local governmentLocal communityGovernment (linguistics)EnforcementSocial organizationMarketingEconomic growthPublic relationsSocioeconomicsPolitical sciencePublic administrationEconomicsSociologyLawSocial science

Abstract

fetched live from OpenAlex

This study was carried out to determine the factors that influence farmers’ participation in social organizations in Obubra LGA in Cross River State. To achieve this, a multistage random sampling technique was used to select five out of 27 clans. Two local organizations were randomly selected from each of the five clans and finally 6 members were also randomly selected from each of the organization, resulting in a total of 60 respondents. The results indicate that half of the respondents (50%) were young people (below 30 years) and they were majority (93.3%) Christians who mostly cultivate small farm holdings of less than 2ha. Majority (68.3) belonged to just one organization, while 20 percent belonged to two organizations. Majority (56.7%) also earned less than N4,000 per month. The members joined local organizations basically for economic benefits and farm supports. Their participation was affected by mutual distrust among members and lack of confidence in their leadership. They were also not sure of having expected organizational benefits. Chi-square (χ2) test result indicated a significant relationship between farm size, educational level, income and participation (P>0.05; 56.0, 9.623 and 7.607). Organizational environment that will encourage effective participation should be encouraged by ensuring due enforcement of organisation’s code of conduct, rules and regulations. Local organizations should also be used as a channel to assist farmers in micro-credit and input delivery. This will be made possible by ensuring good organizational leadership. Key words: Community; Development; organization and Participation Resume Cette etude a ete realisee afin de determiner les facteurs qui influencent la participation des agriculteurs dans les organisations sociales dans l’Obubra a l’Etat de Cross River. Pour ce faire, une technique d'echantillonnage a plusieurs degres au hasard a ete utilisee pour selectionner cinq des 27 clans. Deux organisations locales ont ete choisis au hasard dans chacune des cinq clans et enfin 6 membres ont egalement ete choisis au hasard dans chacune des organisation, resultant en un total de 60 repondants. Les resultats indiquent que la moitie des repondants (50%) etaient des jeunes (moins de 30 ans) et ils etaient la majorite (93,3%) qui pour la plupart chretiens cultivent de petites exploitations agricoles de moins de 2 ha. La majorite (68,3) appartenait a une seule organisation, tandis que 20 pour cent appartiennent a deux organisations. La majorite (56,7%) ont egalement gagne moins de N4, 000 par mois. Les membres qui ont rejoint les organisations locales essentiellement pour des avantages economiques et des soutiens agricoles. Leur participation a ete affectee par la mefiance mutuelle entre les membres et le manque de confiance en leurs chefs. Ils n'etaient pas non plus sur d'avoir les avantages escomptes de l'organisation. Chi-carre resultat du test (χ2) a montre une relation significative entre la taille des exploitations, le niveau d’instruction, le revenu et la participation (P> 0,05; 56,0, 9,623 et 7,607). Environnement organisationnel qui encouragera la participation effective devrait etre encouragee en veillant au respect du code en raison organisation de conduite, regles et reglements. Les organisations locales devraient aussi etre utilise comme un canal pour aider les agriculteurs dans la livraison de micro-credit et d’intrants. Ce sera rendue possible en veillant a une bonne leadership organisationnel. Mots cles: Communaute; Le developpement; l’organisation et la participation

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.025
GPT teacher head0.267
Teacher spread0.242 · 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".

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Citations5
Published2012
Admission routes1
Has abstractyes

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