The Impact of the Unofficial Cattle Business on the Household Welfare of Cattle Traders of the Border Towns of Cameroon and Nigeria
Bibliographic record
Abstract
This paper examines the impact of the unofficial cattle business on the household welfare of cattle traders of the border towns of Cameroon and Nigeria and relates that impact to the household access to basic needs or services of life such as income, employment, food, shelter, education, potable water, electricity, and health care that have been extensively used in the literature as indicators for the attainment of well-being and freedom from the yoke of poverty in the society. It uses primary and secondary data on the trade activities and employs descriptive as well as inferential techniques of data analysis to capture the objectives of the inquiry. The findings of the paper show that despite the unofficial character and unnoticed impact of the business by the governments of Cameroon and Nigeria, the traders who partake in the business acknowledge to have enhanced their living conditions with it. Poverty reduction being implicitly or explicitly cited as a strategy for household welfare improvement by the government in Cameroon and Nigeria, the paper recommends the enforcement, review and continuation of the existing poverty reduction programs irrespective of the leadership choice in the countries.
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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 | 0.001 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".