A Financial Analysis of Homestead Native Chicken Raising: A Climate-Smart Agriculture Option Adopted in the Province of Koh Kong, Cambodia
Bibliographic record
Abstract
In 2018, the International Institute for Rural Reconstruction (IIRR) and the Cambodian Center for Study and Development for Agriculture (CEDAC) under the Asian Development Bank’s Cambodia Biodiversity Conservation Corridors Project (BCC) implemented the Community Development Funds Project in the Koh Kong and Mondul Kiri provinces which included the capacity building activity on improving native chicken production for smallholder farmers specifically, broiler production, and hatchery. This study supported by the International Research and Development Center (IDRC) analyzed the financial benefits gained by households in the Koh Kong province from this climate smart agriculture approach to small scale poultry production. When native chickens were raised for meat purposes (broiler production), the total net income received by the households amounted to USD 6,286.00 in 2019, and USD 8,003.00 in 2020. As the volume of sales increased, the average net income showed an increasing trend while the production cost per kilogram of broiler sold decreased. The study also revealed that profitability was highest among households that sold more than 100 kg of broilers compared to other households with lesser sales volume (using the Operating Profit Margin Ratio as a gauge). Hatchery operators earned a total net income of USD 10,136.00 in 2019 which increased to USD 13,604.00 in 2020. Broiler production and hatchery operation can be useful climate resilient enterprises to supplement the household income while complementing the existing economic activities of the village households such as growing crops and raising small livestock. Local food systems are enriched in the process and agrobiodiversity of small livestock is conserved through their sustainable use. This native chicken project was also gender fair and of special relevance to women in the communes.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".