Bibliographic record
Abstract
About a decade ago, I founded the Asta-Ja Framework which identifies Eight Ja—the Nepali letter “Ja,”—meaning Jal (water), Jamin (land), Jungle (forest), Jadibuti (medicinal and aromatic plants), Janashakti (manpower), Janawar (animlas), Jarajuri (crop plants), and Jalabayu (climate), and proposes their sustainable conservation, development, and utilization for fast-paced socio-economic transformation of Nepal. It is a scientific, holistic, systematic, self-reliance, and multidisciplinary grassroots-based framework for conservation, development and utilization of Asta-Ja resources. For its practical application, I proposed eight principles: 1) community awareness, 2) policy decision making, 3) community capacity-building, 4) interrelationships and linkages, 5) comprehensive assessment, 6) sustainable technologies and practices, 7) institutions, trade and governance, and 8) sustainable community development and socio-economic transformation. The first decade of its implementation in Nepal characterized with a vigorous community outreach, strong membership drive, sound policy advocacy, heavy engagement of high-level government officials and dignitaries, community capacity-building, disaster relief works, and cutting-edge research and development. Future direction for its effective implementation include: 1) institutional strengthening, 2) coordination with governmental agencies and other stakeholders in planning and management of Asta-Ja resources, 3) expedited research and development on Asta-Ja resources, 5) formation of Asta-Ja Consortium, 6) development of a comprehensive Asta-Ja Data Portal, and 7) the establishment of Asta-Ja Think Tank.
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.
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 itClassification
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".