To examine the factors that affect the growth of small agribusinesses in Ghana : a case study of poultry industry
Bibliographic record
Abstract
Abstract The once flourishing small-scale poultry industry in Ghana has over the past two decades undergone a severe deterioration as a result of fortunes that has diverted the industry from near self-sufficiency in the early 1990s to a net importer of poultry products. Since the later part of 1990s the Ghana market has followed a steep and uncontrolled influx of cheap poultry meat from subsidized poultry producers from advanced countries (Osei, unpublished) including USA and EU, not to mention countries such as Brazil and Canada. A multiplicity of factors have accounted for the decline and mortalities of the domestic poultry industry. These include unfair competition from subsidized poultry producers from advanced countries, unfavourable and indifferent government policy direction, escalating costs of production, inefficient methods of production, lack of funds and credit, inadequate knowledge in poultry management, socio-cultural factors, lack of information needs on the part of small-scale poultry farmers, inadequate access to market, lack of processing facilities, and high rates of perishability. Therefore, the present study examines the factors that affect the growth of the small agribusiness in Ghana, focusing mainly on the small-scale poultry industry. The purpose of the study is to provide guidelines and recommendations for improving poultry farming at the level of small-scale poultry farmers in Ghana through the organized social movement (new generation cooperative movement). The study further seeks to solicit government interventions through political arguments so as to sustain and strengthen the failing small-scale poultry industry in Ghana. The purpose of the organized social movement is to bundle competencies and resources that are more valuable in joint effort than when kept separate by the small-scale poultry farmers in racing against competitors who are driving them out of business. This is due to an on-going severe competition as a result of unprotected market and political bias of trade liberalization, structural adjustment policies and deregulations on the part of the government. A sample of 120 poultry farmers was selected by a stratified random sampling approach. This was followed by 75 stakeholders through a snowball approach and data was collected by using a semi-structured interviews. The findings of the study shows that the organized social movement (SM) of small-scale poultry farmers, provision of government subsidies, placing a ban or increase tariffs on imports of poultry meat, access to cheap loans, provision of infrastructure, access to incentives and awards, training and education of poultry farmers, advertising campaign, and dissemination of information, had positive and significant impact on the competitiveness and growth of the small-scale poultry industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".