Farmland tenure and transaction costs: Public and collectively owned land vs conventional coordination mechanisms in France
Bibliographic record
Abstract
Abstract To preserve farmland in industrialized countries, public initiatives or initiatives from nongovernmental organizations increasingly rely on Long‐term and Full Rights Acquisitions of land (LFRAs). The objective of this article is to help assess whether those actions provide profitable access to land use for lessee farms. We compare the economic implications for farms of this mode of access to land use with the two other main modes: conventional lease arrangements and purchasing transactions. The analysis focuses on the transaction costs relative to the cost of exchange, that is, including purchase/rental price, and to the financial benefits of the transaction. We use original data on costs provided by a survey of farmers within a French region. Our results suggest that the ex ante transaction costs incurred by farmers involved in LFRAs, as a percentage of the exchange cost of accessing land use, are lower than those in purchasing transactions and higher than those in conventional lease arrangements. The difference between the two types of lease arrangements is due to negotiation costs, which are doubled in LFRAs. In conclusion, making the involvement of tenant farmers in the construction of LFRAs more effective would allow these initiatives to better achieve their goals.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".