History, Local Wisdom “Ima Kokiriwo” Coconut Based Agroforestry and Land Use Policy in North Halmahera
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
For the people of North Halmahera, coconuts represent a crucial agricultural commodity, yet information related to this topic remains relatively limited.This research aims to explore the history, level of adoptability, and the process of coconut processing, including the role of government policies related to land use.Phenomenological methods and snowball sampling were employed in the research, especially in data collection through interviews, observation, and focus group discussions (FGDs).The data were analyzed using the triangulation method, combined with literature studies, and the level of perception was measured using a Likert scale and quantitative analysis.The results revealed that coconut plantations were first independently cultivated by the Dutch in 1896, while Zending began cultivation between 1902 and 1910.The harvesting and processing of coconuts into copra adhered to the local wisdom principle "Ima Kokiriwo," which signifies working together in groups.The pattern of land use is predominantly (92%) mixed dryland farming, with an annual addition of land area of 3.3 hectares typically occurring in dryland agricultural cover types.The findings of this research support local government policies, particularly those related to the development of coconut cultivation based on traditional wisdom principles.Wise land use and sustainable agroforestry system programs have been effective in increasing land and coconut fruit productivity in North Halmahera, despite post-harvest processing not yet significantly augmenting household income.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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