ЛЕС В СРАВНИТЕЛЬНОМ ПРАВЕ: ГЕРМАНИЯ, КИТАЙСКАЯ НАРОДНАЯ РЕСПУБЛИКА, КАНАДА, НИГЕРИЯ, ТУРЦИЯ
Bibliographic record
Abstract
Forest governance around the globe has been making positive progress in the sense of resource management in the last decade. However, differences in legal systems and policies cause some difficulties in advancing towards the common goal of forest sustainability. This study is aimed to contribute resources sustainability by comparing forest laws in different legal systems so, as to get good governance and practice examples. The legal systems discussed have been determined as Romano-Germanic (Civilian), Anglo-Saxon, Islamic, and Socialist law. To represent these legal systems Germany, Canada, Nigeria, the People’s Republic of China, and Türkiye have been selected. Forest laws of those countries examined and discussed for definition of forest, ownership types, and protection. It has been concluded different legal systems has an important effect on forest perception and the spatial area of forests. The sustainability approach in the Chinese Forest Law has more positive effects on the forest when compared to other laws. That kind of perception of forest law may lead better forest governance and could be the best example for the rest of the world. За последнее десятилетие во многих странах мира достигнут значительный прогресс в управлении лесными ресурсами. Вместе с тем, различия в правовых системах и лесной политике создают определенные трудности на пути достижения общей цели - устойчивого управления лесами в глобальном аспекте. Цель данного исследования - анализ устойчивого использования лесных ресурсов путем сравнения лесного законодательства в различных правовых системах для получения примеров надлежащего управления и лесохозяйственных практик. В статье обсуждаются романо-германское (гражданское), англосаксонское, исламское и социалистическое лесные законодательства на примере правовых систем, применяемых в Германии, Канаде, Нигерии, Китайской Народной Республике и Турции. Лесные законы анализируются и обсуждаются на предмет определения понятия леса, типов собственности и вопросов лесозащиты. Сделан вывод, что различные правовые системы оказывают важное влияние на восприятие леса и площадь лесов. Подход к устойчивому развитию, закрепленный в Законе о лесах Китая, оказывает более положительное воздействие на леса по сравнению с законами других сравниваемых стран. Такое восприятие лесного законодательства может способствовать улучшению управления лесами и стать лучшим примером для остального мира.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".