The Diffusion of Greenhouse Agriculture in Northern Thailand: Combining Econometrics and Agent‐Based Modeling
Classification
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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper studies the diffusion of greenhouse agriculture in a watershed in the northern uplands of Thailand by applying econometrics and agent‐based modeling in combination. Adoption has been rapid by farmers in the central valley of the watershed, while farmers at higher altitudes, lacking transferable land titles that could serve as mortgage collateral, have been unable to obtain loans for greenhouse investment. The objectives of the paper are both methodological and empirical. On the methodological side, it shows that econometrically estimated models of farm household behavior are useful to design and to parameterize an agent‐based model. On the empirical side, simulation results show that if mortgage collateral would not be required, then adoption in the upper part of the watershed could reach nearly 77% of farm households by 2020, as compared to about 36% under current conditions. Furthermore results suggest a significant increase in incomes related to the innovation and a substantially greater irrigation water use, especially in the central part. As bell pepper under greenhouses has replaced pesticide‐intensive chrysanthemum, it has declined average levels of pesticide use. Nevertheless, pesticide use is high and farmers are struggling to control pests, which raises questions about the long‐term sustainability of the innovation. Dans le présent article, nous avons analysé, à l'aide d'un modèle économétrique et d'un modèle multi‐agent, l'expansion de la culture en serre dans un bassin versant des hautes terres du Nord de la Thaïlande. Les agriculteurs de la vallée centrale du bassin versant ont adopté rapidement cette forme d'agriculture, tandis que les agriculteurs installés dans les hautes altitudes n’ont pu, faute de titres fonciers transférables pouvant servir de garantie, obtenir de prêts pour construire des serres. Les objectifs du présent article étaient à la fois méthodologiques et empiriques. Sur le plan méthodologique, notre étude a montré que les modèles de comportement des ménages agricoles estimés économétriquement sont utiles pour concevoir et paramétrer un modèle multi‐agent. Sur le plan empirique, les résultats de simulation ont montré que, si des garanties de prêt n’étaient pas exigées, 77 p. 100 des ménages agricoles adopteraient la culture en serre dans les hautes terres du bassin versant d'ici 2020, comparativement à environ 36 p. 100 dans les conditions actuelles. De nouveaux résultats ont indiqué que cette innovation ainsi qu’un usage accru de l'eau pour l'irrigation, particulièrement dans la partie centrale, pourraient générer une hausse substantielle des revenus. Depuis que la culture en serre du poivron vert a remplacé la culture du chrysanthème exigeante en pesticides, l'usage des pesticides a beaucoup diminué, mais demeure tout de même élevé. Les agriculteurs ont de la difficultéà lutter contre les ravageurs, ce qui soulève des questions sur la viabilitéà long terme de l'innovation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it