Assessing the Financial Health Status of Small Scale Poultry Businesses in Delta State, Nigeria
Bibliographic record
Abstract
The study investigated the financial health status of small scale poultry businesses in Delta State, Nigeria using Altman’s Z-score model. The empirical study was undertaken to assess the solvency and hence future survivability of small scale poultry enterprises in the State. Financial data were extracted from three years (2010 – 2012) financial statements of 125 small scale poultry farms purposively selected from farms operating in the State and incorporated with the Nigerian Corporate Affairs Commission as limited liability agribusinesses. Descriptive statistics which include computed financial ratios, frequency distributions, percentages and tables were applied to analyze the content of the financial statements and Altman’s Z-scores’ were computed for each sampled farm for the three year period. The study shows that in 2010, 47.8 percent of farm enterprises had Z-scores between minus 0.60 to 1.55. In 2011 and 2012, 44.8 percent and 42.4 percent, respectively of the farms had Z-scores between negative 0.60 and 1.55. The study further indicates that 28 percent, 27 percent and 30.4 percent in 2010, 2011 and 2012, respectively, of the sampled farms had computed Z-scores between 2.64 and 4.79 farms. The study recommends the use of Altman’s Z-score by small scale investors as a technique for monitoring the financial health of their agribusinesses to prevent the ugly consequences of bankruptcy and liquidation.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".