On the Productivity of Public Forests: A Stochastic Frontier Analysis of Mississippi School Trust Timber Production
Bibliographic record
Abstract
This paper presents the results of a stochastic frontier analysis on the technical efficiency of school trust timber production in Mississippi. The state of Mississippi has a 200‐year history of managing public trust lands designated to generate funds for public schools. Local school boards became the trustees of sixteenth section lands in the 1970s and have since supervised substantial increases in timber receipts. The majority of the timber management services are contracted to the Mississippi Forestry Commission (MFC)—a state agency responsible for, among other things, overseeing sixteenth section timber management. The school districts and the MFC are legally required to maximize revenue from these lands. However, school districts are also legally permitted to outsource forestry services to private vendors and do so on a regular basis by recommendation from the MFC. This paper finds that the average technical efficiency of the sixteenth section lands is 46%, and there is a positive and statistically significant increase in total timber receipts when a higher proportion of management services are outsourced. Le présent article présente les résultats d'une analyse frontière stochastique de l'efficacité technique de la production de matières ligneuses sur les lots réservés aux écoles publiques dans l'État du Mississippi. Cet État possède deux cents ans d'histoire en gestion de terres publiques destinées au financement des écoles publiques. Les conseils scolaires locaux sont devenus les administrateurs des lots numéro 16 dans les années 1970 et gèrent depuis des augmentations substantielles de revenus tirés de la forêt. La majorité des services de gestion des matières ligneuses sont confiés à la Mississippi Forestry Commission (MFC), agence d'État chargée, entre autres, de la gestion de la matière ligneuse des lots numéro 16. Les arrondissements scolaires et la MFC sont légalement tenus de maximiser les revenus de ces lots. Les arrondissements scolaires peuvent, en vertu de la loi, confier les services forestiers à des entreprises privées, ce qu'ils font régulièrement sur recommandation de la MFC. Les résultats du présent article ont montré une efficacité technique moyenne des lots numéro 16 de 46% et une augmentation statistiquement significative et positive des revenus totaux tirés de la forêt lorsqu'une grande partie des services de gestion étaient impartis.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".