The Rise and Decline of Cocoa Production and its Economic Implication on the Cocoa Farmers in Ondo State, Nigeria
Bibliographic record
Abstract
This project is concerned with the economic implication of the rise and decline of cocoa production on the people of Ondo State, Nigeria.A lot of scholarly works exist on cocoa industry in the study area, but to the best of my knowledge, this is the first work to examine the rise and decline of cocoa and how it has affected the life of people of Ondo Sate.The Post independence cocoa boom of 1960s brought a new hope into the life of cocoa farmers in Ondo State, while the period 1980 was historical in the cocoa sector of the state.It was historic in the sense that the period coincided with the mass production and exploration of crude oil in Nigeria.This development had negative economic implication on the people of the state.Because of the large population of the state, three cocoa settlements were randomly selected for this study i.e Ile-Oluji, Idanre and Bagbe.These settlements were selected because they were known to be the largest producer of cocoa in the state.The methodology adopted for this work is historical approach.Hence, the study is based on primary and secondary sources.The primary sources comprise of oral interview, newspapers, government gazettes, while relevant books were consulted as useful secondary sources.The study conclude that cocoa was an important cash crop which brought positive changes into the life of people and government of Ondo state before the exploration and production of crude oil in commercial quantities in Nigeria.
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 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) | 0.002 | 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".