Section 94 of the Land Code B.E. 2497: Legal Issues Concerning Illegal Acquisition, Disposal, and Retention of Land by Foreigners
Bibliographic record
Abstract
In practice, many foreigners have managed to acquire land in Thailand through nominee structures or proxy companies, despite legal prohibitions. Even when such unlawful acquisitions are discovered, Section 94 of Thailand’s Land Code B.E. 2497 does not penalize the conduct but instead allows foreigners to dispose of the land and retain both their initial investment and any resulting profit. This Independent Research Paper investigates Section 94 of Thailand’s Land Code B.E. 2497, a provision that permits foreigners who have unlawfully acquired land to dispose of it and retain the proceeds. Despite the formal prohibition on foreign land ownership, Section 94 effectively enables financial gain from illegal acquisitions, undermining core principles of Thai legal doctrine, including those related to void juristic acts, unjust enrichment, and good faith, while providing little to no deterrent effect. The study begins with an examination of the historical and doctrinal foundations of Thailand’s restrictions on foreign landholding. It then provides a detailed analysis of statutory provisions, regulatory practices, and Supreme Court jurisprudence, highlighting interpretive contradictions and enforcement limitations. Using a comparative methodology, the paper examines the legal frameworks of Australia, Canada, and the Philippines to explore alternative approaches to handling the proceeds from unlawful foreign land ownership. These jurisdictions offer a range of responses, from absolute forfeiture to partial restitution, reflecting varying normative commitments to land sovereignty, deterrence, and legal coherence. The findings reveal that Thailand’s current legal regime permits unjust financial benefit and lacks sufficient deterrence mechanisms. In response, the paper proposes a five-pillar reform strategy consisting of legislative amendment of Section 94, enhanced judicial oversight, anti-nominee regulation, land transparency infrastructure, and proportional sanctions. Ultimately, the study concludes that Thailand should realign its land laws with constitutional intent and the original purpose of land ownership restrictions. A more enforceable legal framework drawn from comparative best practices that are tailored to Thailand’s specific conditions is essential to preserve legal integrity, reinforce national sovereignty, and restore public trust.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".