An Assessment of Tree Plantation Activity among Smallholders in the District of Ranau, Sabah
Bibliographic record
Abstract
The study was conducted to assess the tree plantation activity among smallholders in the District of Ranau, Sabah. There were six range areas involved, namely Kundasang, Randagong, Nalapak, Lohan-Bongkud, Timbua and Perancangan. The objectives of the study have been to identify the type of tree species planted, the distribution of tree plantation areas, the planting practiced, and the perception of small holders towards tree plantation activity. Data were gathered by direct observation, interviews, questionnaire, as well as secondary data, which were collected from related agencies such as the Agricultural Department and the Rubber Industrial Board in Ranau. There were 47 observations of plantation areas recorded, and the farmers involved were interviewed. The study has identified that Hevea brasiliensis and Durio zibethinus of the agriculture crops' tree were the most types planted by the small holders. Species planted under the category of other selected plantation trees were Acacia sp. (40 %), Tectona grandis (29 %), Pinus sp. (18 %), Azadirachta excels, Neolamarckia cadamba, Octomeles sumatrana and Eucalyptus sp.(13 %). The species of Acacia sp., Tectona grandis, Octomeles sumatrana and Eucalyptus sp. were found at Randagong, Lohan-Bongkud, Timbua and Perancangan while Pinus sp. was mainly found at Kundasang. Azadirachta excelsa, Neolamarckia cadamba and Octomeles sumatrana were only found at Timbua, Lohan and Nalapak. The study has also revealed that the tree plantations among the small holders in Ranau were influenced by land areas owned by the farmer, and the willingness to wait for the long term outcome of the investment. Integrated planting among trees and various crops was applied in order to maximize the usage of the available land. The tree plantation under the category of agriculture crops was mainly for the purpose of economic income, while other selected plantation trees were cultivated for landscaping, long term investment and also for soil protection.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".