Effects of Selected Characteristics on General and Financial Record Keeping Practices of Small Producers in South Central Alabama
Bibliographic record
Abstract
Record keeping is important because it has several benefits such as enhancing performance, planning, organization, filing taxes, access to credit, and access to programs; however, many producers do not keep records. Thus, the study examined the effects of selected characteristics on general record keeping and financial record keeping practices by small producers. Data were collected from a purposive sample of producers from several counties in South Central Alabama and analyzed using descriptive statistics and binary logistic regression analysis. The results showed that a majority were part-time producers; males; over 55 years of age; had less than a 4-year college degree, and earned less than $40,000 in annual household income. Additionally, a majority had a farming experience of over 10 years; acreage owned of 30 acres or less; even a higher majority had acreage farmed of 30 acres or less (73 vs. 24%), and a third earned a profit of less than $5,000. Although over half kept general records, about a third, did not see the importance or the usefulness of record keeping in their operations. Not surprisingly, under 40% kept financial records, and are therefore not familiar with financial ratios. The binary logistic regression analyses showed that only gender had a statistically significant and negative effect on general record keeping; age had a statistically significant and negative effect on financial record keeping, and annual household income had a statistically significant and positive effect on financial record keeping. To sharpen knowledge and skills in record keeping of producers, workshops are recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".